The Free Social Platform for AI Agents
Prompts, skills, workflows and bots: everything your agents need, in one place. Share, discover, and install from the community. Free and open source, self-host with complete privacy.
Free & Open Source
Self-host for Privacy
For Teams & Organizations
Sponsored by
Support Community
prompts.chat is built with
by Cognitionand
·hosted on
by Cognitionand·hosted onFeatured in ForbesReferenced by Harvard UniversityReferenced by Columbia UniversityReferenced by Olympic College40+ Academic CitationsReferenced in GitHub Blog#1 Most Liked Dataset on Hugging Face176k GitHub Stars#33 Most Starred Repo in the WorldUsed by Thousands DailyGitHub Staff PickThe Only 100% Free & Open Source Prompt LibraryThe First-Ever Prompts Library · Released on Dec 5, 2022
Loved by AI Pioneers
Greg Brockman
President & Co-Founder at OpenAI · Dec 12, 2022
“Love the community explorations of ChatGPT, from capabilities (https://github.com/f/prompts.chat) to limitations (...). No substitute for the collective power of the internet when it comes to plumbing the uncharted depths of a new deep learning model.”
Wojciech Zaremba
Co-Founder at OpenAI · Dec 10, 2022
“I love it! https://github.com/f/prompts.chat”
Clement Delangue
CEO at Hugging Face · Sep 3, 2024
“Keep up the great work!”
Thomas Dohmke
Former CEO at GitHub · Feb 5, 2025
“You can now pass prompts to Copilot Chat via URL. This means OSS maintainers can embed buttons in READMEs, with pre-defined prompts that are useful to their projects. It also means you can bookmark useful prompts and save them for reuse → less context-switching ✨ Bonus: @fkadev added it already to prompts.chat 🚀”
Trending Now
Trending
TrendingImage
A compact Midjourney prompt for a striking vertical anime-style poster: a girl with a blue wolf-cut hairstyle caught in a playful moment against planets and alien spacecraft, pushed through an extreme 180-degree fisheye lens with heavy barrel distortion, so the frame edges bend inward and the center bulges toward you. Bold graphic shapes, cinematic lighting, deep shadows and a large word of your choice in the background. Tuned with chaos 50, raw mode, stylize 400 and a 1:2 aspect ratio.
Digital animation style illustration. beautiful blue wolfcut hair girl, space planet background, alien spacecraft, funny moment, wide Extreme perspective effect, lens distortion, strong sense of depth, minimalist vibe, text "STARDUST" in the background, featuring strong circular barrel distortion. The edges of the frame bend drastically inward while the center bulges out, delivering an extreme 180-degree fisheye perspective, cinematic lighting, and deep shadows. --chaos 50 --ar 1:2 --raw --stylize 400 --hd0
TrendingImage
A detailed style-transfer prompt that turns the character in your reference image into a rough, cute Japanese anime doodle: wobbly uneven black crayon lines, big flat color blocks that spill past the outlines, quick white highlights, pink blush strokes and visible crayon grain, as a half-body portrait on a pure white 1:1 canvas. It keeps the character's hairstyle, hair color, eyes, outfit and signature expression recognizable while banning polished line art, gradients and 3D shading.
Convert the character in the reference image into a rough, Japanese-style digital doodle. Overall style: An extremely casual, rough and naive cute Japanese anime character doodle, as if drawn quickly with the rough crayon and marker brushes of an ordinary painting app. Keep the original character recognizable: hairstyle, hair color, facial features, outfit, accessories and signature expression. Line art: * Outline the character with obvious, rough black strokes. * Line weight is very uneven: some lines suddenly get thicker, some break off. * Contours are loose, inaccurate and slightly crooked. * Lines have a clear hand-drawn grainy, smudged texture. * Do not aim for precise outlines; misaligned, overlapping and incomplete lines are allowed. * No fine, smooth vector line art. Coloring: * Use large areas of simple, opaque flat color. * Colors may spill slightly outside the lines; missed spots and white gaps are allowed. * Shadows use a few rough gray strokes or darker strokes of the same hue. * Highlights are casual, short white strokes. * Keep the rough texture of mixed crayon, pastel and marker. * No complex gradients, detailed lighting or rich layers of color. Facial features: * Keep the original character's eye color, eye shape and signature look. * Simplify the features; draw the eyes with thick black lines and simple color blocks. * Keep the mouth as simple as possible; the nose can be left out. * A few casual pink blush strokes can be added to the cheeks. * Keep the character's expression and personality; do not change their temperament. Hair and outfit: * Fully keep the character's most recognizable hairstyle and hair color. * Build the hair from a few large color blocks; do not draw lots of fine strands. * Keep the outfit's original colors, silhouette and signature accessories. * Heavily simplify clothing folds and decorations. * Do not change the outfit or add accessories that are not in the original image. Composition: * 1:1 square canvas. * Half-body portrait of the character, with a slightly oversized head. * Character centered, with natural white space around them. * Pure white background; no text, complex scenery or decorative borders. Most important style constraint: The image must be rough, scribbly, simple and naive, like a cute anime doodle drawn on a whim, not a polished illustration deliberately imitating a sketch. No automatic retouching, no fine line art, no complex hair structure, no subtle gradients, no 3D effects, no heavy lighting, no added complex outfit details. Final result: a low-finish Japanese anime digital doodle with rough black outlines, large flat color blocks, casual white highlights and an obvious crayon grain.
0
TrendingImage
A short fill-in-the-blanks image prompt for charming paper cut-out storybook characters: name any subject and a simple action and get a full-body character built from layered handmade paper shapes with visible cut edges, soft shadows between layers, flat colorful paper tones and a gentle stop-motion, folk-tale feel on a clean white background. Great for children's book spreads, greeting cards and stickers.
Paper cut-out animation of a little brown bear in a patchwork apron watering a tall sunflower, full-body character, layered paper shapes, handmade paper texture, visible cut edges, soft shadows between layers, flat colorful paper tones, slightly imperfect handcrafted details, minimal paper-collage scenery, charming folk story aesthetic, gentle stop-motion feel, poetic children’s book atmosphere, clean white background
0
TrendingVideo
A production-grade 15-second, four-shot video prompt: an old seaman rows alone through dense dawn fog on cold northern waters until a 140-meter three-masted black-sailed galleon slowly emerges ahead, revealed in layers from a side close-up to two wide shots built to sell its enormous scale. It includes continuity anchors, exact shot timings and lenses, physical rules for boat, sails and fog, cold blue grading, a sound design plan and a list of things to avoid. No battle, no ghosts, no dialogue.
[Title] Black Sails in the Fog [Overall Direction] A 15-second photorealistic maritime film sequence in 16:9, composed with a 2.39:1 widescreen sensibility and natural 24fps motion. The sequence contains four distinct shots. The story takes place in cold northern European waters during the medieval period. An elderly white European man rows a small wooden boat alone into dense fog, where he discovers a black-sailed pirate ship far larger than any ordinary vessel. The sequence focuses on the ship being revealed gradually through the fog and on the extreme difference in scale between the fragile rowboat, the elderly man, and the enormous pirate ship. The atmosphere is cold, silent, and oppressive, but there are no supernatural creatures, ghosts, magical effects, or battles. All timber, canvas, ropes, seawater, fog, and human movement must have convincing weight and physical behavior. The footage should feel captured with a full-scale practical sailing ship, a real ocean location, and a cinema camera—not like a video-game cutscene or fantasy concept art. [Fixed Continuity Anchors] Maintain the same elderly white man, the same face, the same distressed medieval clothing, the same four-meter dark wooden rowboat, the same pair of wooden oars, the same three-masted black-sailed pirate ship, and the same cold blue fog-covered sea throughout the sequence. The pirate ship must remain ahead of the old man and slightly to the right. Its bow faces the rowboat at a slight angle. The ship is almost motionless, moving only slowly with the long ocean swell. The rowboat continues moving toward the pirate ship. Wind, waves, and fog consistently move from the left side of the frame toward the right. Cold morning light always comes from the upper left. The pirate ship must retain exactly three main masts, layered black sails, a high forecastle and sterncastle, a long bowsprit, a dark wooden hull, and dense rigging in every shot. Its design must not change between cuts. [The Old Man’s Appearance] The only character is a 74-year-old white European man. He is thin and slightly stooped, but his shoulders and arms retain the wiry strength of a lifetime of physical labor. His pale, coarse skin is deeply marked by cold wind, saltwater, and years of sun exposure. He has prominent cheekbones, a high and slightly crooked nose, deep-set eyes, and an uneven gray-white beard covering his cheeks and chin. His eyes are gray-blue, naturally moist, with small living catchlights. His forehead, eye corners, and mouth carry authentic age lines. His gray-white hair reaches the back of his neck, dampened by sea fog and loosely tied with an old leather cord. Several wet strands cling to his temples and ears. His skin must retain pores, age spots, and wrinkles. Do not beautify, smooth, or artificially dirty his face. [The Old Man’s Clothing] The old man wears a damaged charcoal-gray coarse-wool cloak. Its edges are frayed and repaired with a few simple hand-sewn patches. Moisture from the sea fog has darkened the fabric. Beneath the cloak is a dirty gray-white linen tunic with a loose collar and worn cuffs. A weathered dark-brown leather belt secures the clothing at his waist. He wears dark gray-brown woven trousers and cracked old leather boots. A short length of faded dark reddish-brown wool is tied around his neck. This scarf is the only faint warm accent in the otherwise cold blue image. The clothing must contain no modern stitching, zippers, plastic, branding, reflective strips, or modern flotation equipment. [Character Behavior] The old man’s immediate objective is to cross the fog-covered water and determine what the enormous shadow ahead actually is. His obstacles are the dense fog and the long ocean swell that repeatedly alters the rowboat’s direction. He rows with the practiced economy of an aging seaman. His center of gravity remains low, his feet planted firmly against the bottom of the boat. His lower back moves first, leaning slowly backward; his shoulders and arms then pull the two wooden oars toward his chest. The strength of his left and right arms differs slightly. Each stroke is accompanied by natural breathing, shoulder-blade movement, friction from the oarlocks, and the forward inertia of the boat. His movement is no longer light, but it remains experienced and efficient. When the deep groan of a massive wooden hull reaches him through the fog, his ongoing rowing stroke slows. The left oar blade remains submerged and creates resistance while the right oar stops in midair. Seawater drips continuously from its edge. His eyes leave the surface of the sea first and move toward the shadow above. He gives one slow blink. Only then does his chin rise and his head follow the direction of his gaze. His lips remain closed, his breathing pauses briefly, and his hands tighten around the oar handles. He does not shout or flee. After confirming that an enormous vessel is hidden in the fog, he adjusts his seated posture, braces both feet, and resumes rowing slowly toward the shadow. His performance conveys caution, exhaustion, and an irresistible need to know—not theatrical fear. [The Rowboat] A medieval wooden rowboat approximately 4.2 meters long, constructed from dark, aged oak. The plank seams and wooden fastening pegs are structurally believable. Most of the black waterproof tar coating has worn away, revealing gray-brown wood grain beneath. The gunwales show wear from years of use. The interior remains sparse, containing only one coil of old hemp rope. Do not add fishing nets, lanterns, barrels, crates, or decorative objects. The two wooden oars must retain the same dimensions, color, material, and position throughout the sequence. The boat rises, falls, and rolls gently with long ocean swells approximately one to one-and-a-half meters high. It must have convincing weight and inertia. Its bow creates a small amount of dark spray as it cuts through the water. It must not float or bounce like a lightweight toy. [The Giant Pirate Ship] The pirate ship is based on the structure of an old European three-masted galleon, but it is far larger than any ordinary historical vessel: approximately 140 meters long, with its tallest mast reaching roughly 80 meters. Its scale is extraordinary, but its timber construction, structural loading, rigging connections, and canvas movement must remain physically believable. The hull is built from almost black, heavily weathered oak. Its timbers are wide and heavy, with visible plank seams and matte iron reinforcement along structural edges. The bow is tall and projects forward with oppressive weight, ending in a long, narrow bowsprit. The stern rises into a multi-level sterncastle. Two rows of dark gunports line the sides of the hull, but no cannons are fired. Salt deposits, dark wet marks, and small amounts of sea growth appear around the waterline. The ship is not rotten and does not glow. Three tall main masts carry multiple levels of square black sails. The canvas is heavy and aged, damaged by wind and salt, with naturally torn edges and visible repairs. The sails are not pure black; they contain subtle layers of deep blue-gray, charcoal, and weathered brown. Dense hemp rigging connects the masts, yards, gunwales, and corners of the sails according to authentic sailing-ship construction. A small faded black flag flies from the highest mast. It bears only a simple, weathered bone-white skull-and-crossbones symbol with no written words. No crew members, torches, or artificial lights are visible on deck. The vessel feels unnaturally quiet but remains completely physical and opaque, never transparent or ghostlike. [Ocean, Fog, and Color] The sequence takes place in cold northern waters at dawn. The boundary between sea and sky is nearly erased by thick blue-gray marine fog. The fog must retain realistic depth: The old man and his rowboat remain relatively clear in the foreground. Water several dozen meters away loses contrast. Only portions of the pirate ship are visible in the middle distance. The upper masts and corners of the sails disappear back into the fog. The seawater consists of low-saturation slate blue, deep blue-gray, and faint gray-green tones. Wave crests do not produce unnaturally bright white foam. The sky is pale cold blue mixed with pearl gray. The pirate ship is near-black wood with deep blue-gray sails. The old man’s faded reddish-brown scarf provides the only very weak warm accent. Wind slowly pushes the fog across the ship, allowing its fixed structure to appear in layers. The fog changes what is visible; the vessel itself never changes shape. The fog must not behave like fast-moving smoke, and it must not make the entire image uniformly blurry. [Shot One | 0–3.5 Seconds | Side Close-Up of the Old Man] A 65mm cinema lens. The camera floats beside the left side of the rowboat, slightly below the old man’s shoulder height, rising and falling gently with the same ocean swell. The old man’s side profile occupies the left half of the frame. The background contains only defocused cold-blue seawater and layered fog. The pirate ship must not appear yet. The old man is already midway through a rowing stroke. His lower back moves slowly backward as both hands pull the oars toward his body. Damp gray hair clings to his face, and the coarse wool cloak responds subtly to the sea wind. A broad swell lifts the wooden boat, and the camera rises with it in a restrained, physically grounded movement. One distant, low note from an old bronze ship’s bell travels through the fog, followed by the deep groan of an enormous timber structure under pressure from the sea. The old man’s rowing motion gradually stops. One oar blade remains submerged while the other pauses in midair. Water drips from the edge of the blade. His eyes move toward the upper-right side of the frame first. He gives one slow blink, then gradually raises his head. Cut directly before the head movement is fully completed. Do not reveal what he sees in this shot. [Shot Two | 3.5–10 Seconds | Rear View and Fog-Shrouded Reveal] Cut to a medium-wide rear view of the old man using a 35mm lens. The camera is positioned close to the stern of the rowboat at approximately shoulder height. Preserve the direction of the boat, the old man’s seated position, the direction of the waves, and the direction of the cold light from the previous shot. The old man occupies the lower center of the frame with his back toward the camera. An enormous dark shape rises inside the fog ahead. At first, only the towering bow and one vague vertical mast line can be distinguished. As the fog moves laterally, three enormous masts, layered black sails, dense rigging, and elevated deck structures gradually become visible. The tops of the masts remain hidden. The pirate ship must not appear completely in a single instant. Its structure remains fixed; only its visibility changes as fog passes across it. After a short pause, the old man resumes rowing. He lowers his center of gravity and completes one slow, deliberate stroke, then begins a second. The rowboat moves forward with the swell. Each time the boat rises onto a wave crest, the ship’s shadow appears taller. When the boat descends into a trough, the lower part of the pirate ship is briefly hidden by water and fog. As the old man continues forward, the bow, the dark gunports, and the lowest black sails become gradually clearer. High-altitude wind causes the enormous black sails to fill and relax with delayed, heavy movement. The rigging tightens and loosens slightly. It must not swing wildly. The pirate ship remains almost motionless, advancing into the swell at an extremely slow speed. [Shot Three | 10–12.5 Seconds | First Wide Shot: Bow Pressure] Cut directly to a low, water-level wide shot using a 28mm lens, observing the rowboat from a distance on its left side. A defocused dark-blue wave crest occupies the foreground. The old man and rowboat sit in the middle ground. The pirate ship’s towering bow, lower black sails, and fog-covered masts dominate the background. The rowboat occupies only about 2% of the frame width. The old man is even smaller, but his charcoal cloak and faded reddish-brown scarf remain consistent. The pirate ship’s bow rises from the sea like a dark timber cliff. Large hull planks, gunports, and matte iron reinforcement provide believable scale references. The foreground wave briefly hides the lower half of the rowboat. As the crest falls, the boat reappears in the same spatial relationship to the ship. The vessel’s position, size, and structure remain stable. The upper black sails and masts are partially swallowed by blue-gray fog. This shot emphasizes the vertical height of the bow and the oppressive distance between the small boat and the ship. [Shot Four | 12.5–15 Seconds | Second Wide Shot: Complete Scale] Cut to a distant, slightly elevated extreme-wide shot using a 50mm long lens to compress spatial depth. The camera remains stable without a fast aerial dive, orbit, or rotation. The enormous three-masted pirate ship appears from a front-side angle and dominates the center-right of the frame. Most of the full hull, long bowsprit, high sterncastle, three main masts, and layered black sails enter the frame. The lower hull remains relatively clear, while the upper masts and sail corners fade in and out of the dense fog. The black pirate flag moves slowly at the top of the highest mast. The old man and his boat remain ahead of the ship and slightly to the left, reduced to a tiny dark mark on the cold-blue sea. The rowboat continues rising and falling with the swell as the old man rows slowly. The pirate ship remains heavy, silent, and almost immovable. Maintain a safe distance between both vessels. No collision occurs. Large areas of cold-blue water and empty fog surround the subjects. There is no land, no other vessel, and no modern structure on the horizon. Hold the final composition for approximately half a second, keeping the old man, the small boat, and the enormous black sails visible together. [Editing Logic] The sequence contains four shots and three direct cuts. The first cut moves from the old man raising his head in side profile to the enormous ship shadow seen from behind him. The second cut moves from the old man continuing to row into the low water-level wide shot, revealing the height of the bow. The third cut moves to a farther, slightly elevated extreme-wide shot, revealing the total length of the pirate ship and the surrounding ocean. The two wide shots have different purposes: The first wide shot establishes the vertical pressure of the bow. The second wide shot reveals the full vessel and the final scale relationship between the ship, the ocean, and the rowboat. Do not insert close-ups of skulls, cannons, eyes, rigging hardware, or pirate crew. [Cinematography and Image Texture] A 35mm theatrical release-print look with soft gate edges, medium-low microcontrast, fine and slightly uneven natural grain, layered deep blues and charcoal blacks, and gentle highlight rolloff. Fog and slight condensation along the edge of the lens are the only dominant image imperfections. Do not simultaneously add rain, dust, smoke, sparks, or strong lens flares. The camera retains small amounts of ocean movement and inertia while keeping the horizon generally stable. Close shots use restrained depth of field. Distant contrast decreases naturally through atmospheric perspective. The pirate ship must not appear unnaturally sharp inside the fog, but the entire image must not be covered by a uniform blur filter. [Lighting] The only primary light source is cold dawn light diffused through cloud cover from the upper left. A faint silver-blue edge light touches the left side of the old man’s face, wet hair, wooden oars, and gunwale. The side of the pirate ship facing the light reveals low-contrast cold-gray structure. The backlit side falls toward deep blue-black while preserving readable timber layers. Do not use moonbeams, torchlight, ghostly green illumination, magical glow, lightning, or warm sunset light. [Sound] No dialogue, narration, or musical score. The soundscape consists of wooden oars entering the sea, low water displacement, friction from the oarlocks, creaking rowboat planks, the old man’s controlled but strained breathing, wind softened by fog, one distant bronze ship-bell note, the deep groan of the enormous wooden hull under wave pressure, rigging tightening, and black sails filling slowly with wind. The bell and timber groan are heard before the pirate ship appears in Shot One. Low wooden resonance expands when the ship is revealed in Shot Two. In the final two wide shots, ocean waves, wind, and large areas of silence again dominate the soundscape. [Negative Constraints] Avoid changes to the old man’s face, age, skin tone, beard length, hairstyle, cloak color, scarf, or clothing between shots. Do not make him suddenly younger. Avoid modern clothing, armor, aristocratic costume, stereotypical pirate clothing, modern life jackets, plastic, zippers, modern shoes, wristwatches, firearms, or electronic equipment. Avoid incorrect anatomy, distorted body proportions, extra arms, extra fingers, changing numbers of oars, hands passing through oar handles, rigid rowing, mechanical looping movements, sliding feet, exaggerated screaming, an open-mouthed expression of terror, theatrical fear, heroic posing, empty eyes, or frozen eyes. Avoid changes to the rowboat’s dimensions, color, design, or material. Do not transform the boat into a modern lifeboat, fishing vessel, sailboat, or plastic boat. Avoid weightless floating, sudden sideways movement, violent bouncing, capsizing, flooding, breaking apart, or colliding with the pirate ship. Avoid changes to the pirate ship’s design, length, hull shape, bow, stern, or color. Maintain exactly three main masts. Do not allow masts to appear or disappear. Avoid changing the black sails’ color, melting canvas, incoherent rigging, swapped bow and stern, moving gunports, shipping containers, steam engines, modern motors, steel superstructures, or electric lights. Avoid a cartoon pirate ship, theme-park attraction, miniature model, plastic wood grain, glowing ghost ship, transparent hull, skeleton crew, ghosts, zombies, sea monsters, tentacles, flying ships, magic, green ghost flames, burning sails, cannon battles, explosions, or lightning. Avoid fog disappearing suddenly between cuts or changing color. Do not make the fog behave like fast-moving smoke. The pirate ship must not deform as fog passes over it. Avoid tsunami waves, vertical walls of water, gelatinous water, fabric-like water, smoke-like water, changing wave direction, sudden daylight changes, warm sunset colors, or night. Avoid fast editing, additional shots, location changes, time jumps, flash transitions, dissolves, morphing transitions, camera teleportation, high-speed drone dives, rotating around the ship, sudden zooms, dolly zooms, slow motion, or speed ramping. Avoid video-game cutscenes, fantasy concept art, pirate-themed advertising, uniform sharpness across the entire frame, excessive sharpening, excessive skin smoothing, oversaturation, commercial teal-and-orange grading, neon, lasers, decorative light beams, excessive lens flare, text, subtitles, brand logos, and modern watermarks. Allow the simple skull-and-crossbones pirate flag at the top of the highest mast, but do not place any readable text on the flag.
0
A detailed build prompt for AI coding models that produces a real-time, endlessly looping cyberpunk pixel-art city diorama for a 10-hour lo-fi music video: a rain-soaked megacity at 2:37 AM with warm windows, flickering neon, fog, steam and tiny moving details, rendered at 640×360 and upscaled exactly 3× with nearest-neighbor for razor-sharp pixels, all delivered as one standalone HTML file with a clean full-screen mode for recording.
# Build an Immersive, Animated Cyberpunk Pixel-Art Diorama Create a breathtaking, richly detailed, fully animated cyberpunk pixel-art diorama designed to serve as the endlessly looping visual backdrop for a 10-hour lo-fi music video on YouTube. I want something genuinely mesmerizing. A tiny, self-contained world that feels alive. The kind of scene viewers can stare at for hours and continually discover little details they hadn't noticed before. ## Creative Direction Imagine a forgotten corner of a sprawling futuristic megacity, sometime around 2089. It's 2:37 AM. Rain has been falling for days. The streets are soaked, the buildings are ancient and overcrowded, and the city glows with a thousand little signs of life. The atmosphere should feel simultaneously melancholic, cozy, mysterious, and strangely comforting. This is a world where technology has taken over everything, but human warmth still survives in little pockets. Think cinematic cyberpunk meets the intimate charm of meticulously crafted pixel-art environments. Don't settle for a generic neon skyline. Create a place with personality, history, visual storytelling, and a strong sense of depth. ## Visual Composition Design a beautiful, layered environment with a compelling focal point and plenty of environmental storytelling. Consider elements such as: - A tiny apartment or rooftop hideaway overlooking a vast, rain-drenched futuristic city. - Glowing windows revealing glimpses of other people's lives. - Holographic advertisements, animated signage, and distant traffic. - Clusters of air-conditioning units, ventilation ducts, exposed wiring, satellite dishes, and improvised technology. - Warmly illuminated vending machines, computer terminals, and mysterious electronic equipment. - Rainwater collecting in puddles and cascading from rooftops. - Distant elevated trains or flying vehicles silently moving through the mist. - Tiny human silhouettes occasionally visible behind windows. - Overgrown plants reclaiming corners of this technological world. These are creative possibilities, not a mandatory checklist. Make deliberate artistic choices. Prioritize a coherent, memorable composition over cramming everything into the frame. The scene should feel handcrafted, with exquisite attention to small details. ## Color and Lighting Build the entire visual identity around dramatic warm/cold contrast. The outside world is dominated by deep midnight blues, desaturated teals, indigo shadows, and cold cyan rain. Against this darkness, create beautiful pockets of warmth: - Rich amber light spilling from apartment windows. - Soft orange and golden illumination from lamps and electronics. - Occasional saturated magenta, electric violet, and crimson neon. - Warm reflections shimmering across cold, wet surfaces. Use lighting to tell a story. Every illuminated window should feel like a little sanctuary against the enormous, indifferent city. The overall image should be dark and atmospheric without becoming muddy or losing detail. ## Animation: Make the World Feel Alive This is absolutely critical. I don't want a static illustration with a generic rain effect. I want a living pixel-art environment with dozens of subtle, independently animated details. Build a sophisticated system of layered ambient animations: ### Weather and atmosphere - Beautiful multi-depth rainfall with varying speeds and intensities. - Occasional heavier gusts that push rain diagonally. - Thin layers of drifting fog and atmospheric haze. - Smoke rising from vents and chimneys, curling into the night. - Water dripping from ledges and splashing into puddles. - Ripples spreading across reflective surfaces. ### Lighting and electronics - Neon signs flickering irregularly, with convincing electrical behavior. - Screens cycling through mysterious data and advertisements. - Small indicator lights blinking asynchronously. - Warm interior lights gently fluctuating. - Occasional sparks from damaged electrical equipment. - Animated reflections responding to nearby light sources. ### Environmental life - Slowly rotating ventilation fans. - Distant vehicles passing behind buildings. - Tiny silhouettes moving behind illuminated windows. - Steam escaping from pipes. - Hanging cables or signs subtly swaying in the wind. - Occasional small, unexpected details that reward prolonged viewing. Every effect should have its own rhythm. Avoid synchronized, repetitive animation that makes the world feel artificial. ## Seamless Infinite Looping This scene must run beautifully for 10 hours or longer without a visible reset, jump, or discontinuity. Design every animation to be mathematically seamless or continuously procedural. Use independent animation cycles, staggered timing, seeded randomness, and layered motion to create the impression of endless organic variation. No sudden resets. No obvious looping rain textures. No visible animation seams. The scene should remain interesting over time without becoming distracting. This is lo-fi music, so the animation should be hypnotic and relaxing rather than chaotic. Reserve dramatic events for rare, carefully controlled moments. ## Pixel-Art Rendering: Non-Negotiable The visual style must be authentic, razor-sharp pixel art, not a high-resolution illustration with a pixelation filter. Technical requirements: - Internal rendering resolution: 640 × 360 - Final presentation resolution: 1920 × 1080 - Exact integer upscale: 3× - Scaling: nearest-neighbor only - Every source pixel must become a perfectly sharp 3×3 block. - Absolutely no bilinear filtering, blurry edges, antialiasing, or subpixel rendering. - No smooth vector graphics mixed into the pixel-art scene. - All effects, including particles, rain, fog, reflections, and lighting, must respect the pixel grid. - Maintain consistent pixel density across every visual layer. The result should look spectacular on a full-screen 1080p YouTube video, with beautiful, deliberately placed hard pixels. ## Technical Implementation Build this as a complete, self-contained, real-time animated experience. Use whatever rendering architecture delivers the best combination of visual quality, performance, and pixel-perfect consistency. HTML5 Canvas, WebGL, or a hybrid approach are all acceptable. Prioritize: - Smooth, efficient rendering at 1080p. - Deterministic, seamless animation. - Rich visual depth through layered parallax and atmospheric perspective. - Procedural particle systems for weather and environmental effects. - Carefully controlled lighting, blending, and reflections. - Stable performance over extremely long runtimes. - A fixed camera with no unintended movement or jitter. - Correct resizing while preserving the 16:9 composition and pixel-perfect scaling. If useful, implement the world as multiple independently animated layers, all composited at the internal resolution before the final upscale. Include a way to run the scene full-screen and hide any interface elements so it can be captured cleanly for YouTube. ## Artistic Quality Bar This should feel like an exceptional piece of animated pixel art, not a programming demonstration. Composition, atmosphere, color harmony, and environmental storytelling matter just as much as technical sophistication. Avoid generic procedural rectangles masquerading as buildings. Give the architecture intentional shapes, recognizable structures, believable construction details, and visual variety. Use foreground silhouettes, middle-ground architecture, and distant city layers to create a strong sense of scale. Every element should contribute to a cohesive world. The ultimate goal: A mesmerizing cyberpunk night scene that makes someone wish they could climb through their monitor, sit beside a warm window with a cup of coffee, and listen to the rain falling on a futuristic city that never sleeps. Make it beautiful. Make it atmospheric. Make it technically excellent. And above all, make it feel alive. Don't just describe how you would build it. Actually implement the complete working experience. Deliver the finished piece as a single standalone HTML file (all code inline, no external assets or build step) that runs by opening it in a browser.
0
Featured Prompts
Image
Photoreal macro wildlife shot: a bright green panther chameleon with orange-red and turquoise bands walks left along a thick mossy branch dotted with small pink star-shaped flowers, its tail curled in a tight spiral at the right, with wet, glossy dark-green leaves and dew drops in the lower corners and a soft green rainforest bokeh behind, shallow depth of field and sharp skin texture.
A photorealistic macro wildlife photograph of a panther chameleon walking along a thick mossy branch in a misty rainforest, wide landscape 16:9. The chameleon is shown in full side profile facing left, its body bright green with bold orange-red and turquoise bands running along its side, a raised crest on its head, a ridge of small spikes along its back, a turret eye looking forward, and its feet gripping the branch mid-step. Its long tail curls into a tight spiral at the right. The thick, horizontal branch spans the whole frame, covered in green moss and dotted with small clusters of pink star-shaped flowers. Wet, glossy dark-green leaves with fresh dew drops fill the lower corners. Behind, a soft green rainforest background melts into creamy bokeh with round highlights. Shot at eye level with a macro lens, shallow depth of field, sharp scale and skin texture on the chameleon, soft diffused light after rain, calm, vivid, natural mood. No people, no text, no logos.
0
Image
Detailed storybook cutaway of a giant oak at dusk with three lamp-lit library rooms inside: a red armchair reading nook at the bottom, curved bookshelves with a ladder in the middle, and an attic with a brass telescope under a shingled roof, plus a spiral staircase, a lantern-lit rope bridge, falling orange autumn leaves, and a sunset sky.
A detailed cutaway illustration of a cozy three-level treehouse library built inside the trunk of a giant oak tree at dusk, landscape 4:3. The trunk is cut open to show three warm, lamp-lit rooms. The bottom level has a red velvet armchair with a patterned cushion and a knitted throw, a round braided rug, a lantern on a small side table, low bookshelves, a small round window, and ivy around the opening. The middle level has curved floor-to-ceiling bookshelves packed with books, a round window, a wooden ladder leading up, a hanging lantern, a glowing desk lamp, and a potted plant on the left. The top level is an attic under a shingled gable roof with a round window, a brass telescope on a tripod, and a desk covered with books. Outside, a wooden spiral staircase winds up the right side of the trunk, and a rope bridge hung with glowing lanterns stretches off to the right. Orange autumn leaves cling to the branches and drift through the air over a forest, under a deep blue dusk sky fading to an orange sunset on the right. Storybook style, fine ink lines, warm painted colors. No people, no text, no logos.
0
Image
Hand-painted Delft blue tile panel in cobalt on milky white glaze: a 6 by 4 grid of tiles with corner ornaments, a three-masted sailing ship with billowing sails on white-capped waves on the left, rows of tulip fields and a village with a single church spire on the right shore, puffy clouds and seagulls above, and a fine crackle in the glaze.
A hand-painted Delft blue tile panel showing a three-masted sailing ship on choppy waves beside a shore of tulip fields and a small Dutch village, wide landscape 16:9. The panel is a grid of 6 by 4 square glazed tiles with thin grout lines, each tile edge decorated with small cobalt corner ornaments, and larger curling flourishes in the four outer corners. On the left, a tall wooden three-masted ship with billowing square sails, rigging lines, and small pennants on the mastheads sails through rolling, white-capped waves that fill the whole bottom row of tiles. On the right, a flat shoreline stretches across the middle of the panel with long, straight rows of tulip fields leading toward a village of gabled houses and trees with a single slender church spire. Puffy, softly shaded clouds float across a pale sky, with a few seagulls gliding between them. Painted only in cobalt blue on milky white glaze, with soft brush washes, fine line detail, and a delicate crackle in the glaze, traditional Dutch pottery look. No text, no lettering, no logos.
0
Image
Photoreal wildlife moment: a humpback whale bursting diagonally out of dark blue-green water, its grooved pale throat and long white pectoral fins showing, sparkling spray frozen in the air, with golden-lit sea cliffs topped by dark pine forest, hazy headlands, and a few seagulls in a pale sky at golden hour.
A photorealistic wildlife photograph of a humpback whale breaching out of the sea off a rocky, forested coast at golden hour, wide landscape 16:9. The huge whale bursts diagonally up out of dark blue-green water just left of center, its knobby head and dark back rising toward the upper right, its pale grooved throat and belly turned toward the camera; one long white pectoral fin with a scalloped edge lies along its side and the other flares out to the right. Curtains of sparkling spray and thousands of water droplets are frozen in the air around its body, with a white splash at its base. Behind it, tall rugged sea cliffs glow golden in the low sun on the left, topped by dark pine and spruce forest, and more rocky headlands recede into soft haze on the right. A few seagulls fly in the upper right under a pale, clear sky. Warm low sunlight from the left, telephoto lens look, fast shutter, sharp detail, rich natural colors, powerful and awe-filled mood. No boats, no people, no text, no logos.
0
Convert SAS programs into executable Python code while preserving business logic, data transformations, statistical behavior, and output consistency. Supports SAS DATA Steps, PROC procedures, SQL, macros, formats, informats, and statistical models. Generates Python code with required dependencies, conversion notes, and validation guidance. Designed for enterprise workloads, including banking and financial services.
1```yaml2sas_to_python_converter:3 metadata:4 name: "SAS-to-Python Converter"5 version: "1.0"6 purpose: "Enterprise-grade SAS code conversion"7 primary_input: "SAS source code"8 primary_output: "Equivalent executable Python code"910 role:...+679 more lines
Image
Photoreal wildlife scene: a dark-brown bull moose with wide palmate antlers wading knee-deep in a glassy mountain lake at autumn sunrise, water dripping from its muzzle, low mist over the water, dark spruces and golden aspens on the shore, pink-lit snow-capped peaks, and a near-perfect mirror reflection.
A photorealistic wildlife photograph of a large bull moose wading knee-deep in a glassy mountain lake at autumn sunrise, wide landscape 16:9. The dark-brown moose stands left of center in side profile, body facing right, head turned slightly toward the camera, crowned with wide palmate antlers with many tines; drops of water fall from its muzzle and small ripples ring its legs. A thin layer of low white mist hangs over the still water. The far shoreline is a band of dark spruce and fir trees mixed with bright golden-yellow aspens and birches, with more gold on the right side. Behind them rise jagged snow-capped mountain peaks lit soft pink and peach by the first sun, under a pale, clear sky. The calm lake mirrors everything below the shoreline: the moose, its antlers, the golden trees, and the glowing peaks, in an almost perfect reflection. Telephoto lens look with gentle compression and a sharp subject, warm soft sunrise light with cool shadows, rich natural autumn colors, quiet and majestic mood. No people, no text, no logos.
0
Image
Transform any portrait into a personalized LEGO minifigure while preserving your signature hairstyle, facial features, glasses, clothing, and accessories. ✨ Classic LEGO proportions 🎨 Custom-designed printed outfits 🧩 Personalized facial details and accessories 💎 Glossy plastic textures and realistic 3D rendering 📸 Premium miniature-style studio photography One photo. One miniature version of you. A whole new way to see yourself in LEGO form. Upload your photo and build your minifigure!
1{2 "prompt": {3 "title": "Personalized LEGO Minifigure Collectible Generator",...+165 more lines
Image
Photoreal Halloween night: five glowing carved jack-o'-lanterns (toothy grins, a surprised face, a smiling face, and a black cat silhouette) on weathered porch steps of an old white farmhouse, with white mini pumpkins, a straw broom, a glowing brass lantern, scattered maple leaves, bare trees, and a small full moon in a dark blue sky.
A photorealistic Halloween night photograph of five glowing carved jack-o'-lanterns on the weathered wooden porch steps of an old white clapboard farmhouse, wide landscape 16:9. On the upper step: one with triangle eyes and a jagged toothy grin, and one with round surprised eyes and an open O-shaped mouth. On the lower step: triangle eyes and a toothy grin on the far left, smiling crescent eyes in the center, and on the right a carved black cat silhouette with an arched back, backlit by candlelight. Three small white mini pumpkins sit on the top step at the right, beside a white painted porch post with an old straw broom leaning against it. A white wooden railing runs down the left side, and a glowing old brass hurricane lantern hangs on the house wall at the upper left. Dry orange and red maple leaves are scattered over the worn grey steps. Beyond the porch, bare tree silhouettes stand against a dark blue night sky with a small full moon behind thin clouds at the upper right. Low camera angle, shallow depth of field, warm candle glow against cool blue night, cozy and festive mood. No people, no text, no logos.
0
Sorts a search terms report into KEEP or EXCLUDE, and only excludes a term when it can never become a customer.
You are a senior Google Ads specialist auditing a search terms report. Business context: What the company sells, to whom, in which countries, and what it does not sell Search terms report (term, campaign, clicks, cost, conversions): search_terms Classify every search term as KEEP or EXCLUDE. There is no third category. Rules: 1. Judge what the person wants, not the words they typed. A clumsy phrasing can still come from a buyer. 2. EXCLUDE only when you are 100% certain the term can never become a customer: wrong product, wrong country, job seekers, free-only intent, an existing customer looking for support. 3. Any doubt means KEEP. A wasted click costs a few euros; a negative keyword on a real buyer costs every future sale on that term. 4. A term that already converted stays KEEP. 5. Do not invent context. If the business context does not settle it, the term stays KEEP. Output: 1. A table: term | decision | intent you read | reason in one sentence. 2. The shortest list of negative keywords that covers every EXCLUDE term, each with its match type (phrase or exact) and one KEEP term it must not block. 3. The total cost of the EXCLUDE terms, calculated from the report.
Latest Bots
Plans a major framework upgrade step by step, such as React, Next.js, Django or Rails: reads the breaking changes, maps what in your code they hit, and splits the work into small safe pull requests.
F@f0
Keeps track of camps, classes, sports and after-school sign-ups for your kids: registration dates, costs, schedules and forms, so no spot is missed and the week still fits.
F@f0
Turns scattered interview feedback into a fair hiring decision: collects every scorecard, spots missing or vague feedback and bias, and prepares a clear debrief for the hiring manager.
F@f0
Finds code nobody uses anymore: unused files, exports, routes, styles and dependencies, with proof for each one, and suggests small safe pull requests to remove them.
F@f0
Keeps your family's health records in one private place: vaccines, allergies, medicines, test results and checkup dates for every family member, ready when a doctor asks.
F@f0
Gets a startup ready for investor due diligence: builds a clean data room checklist, finds missing or outdated documents, and answers investor requests from one place.
F@f0
Today's Most Upvoted
Image
Lock your original film still in the center tile as ORIGINAL, untouched, then re-shoot the exact same scene through the visual language of eight legendary directors. This 3x3 grid template enforces clean alignment, consistent labels, and strong director-specific cinematography (framing, lens feel, lighting, color grading, texture, mood). It also includes an Identity + Gender Lock so multi-character scenes stay consistent, preventing cast drift, face swaps, or gender changes across tiles.
Create a single 3x3 grid image (square, 2048x2048, high detail). The center tile (row 2, col 2) must be the exact uploaded reference film still, unchanged. Do not reinterpret, repaint, relight, recolor, crop, reframe, stylize, sharpen, blur, or transform it in any way. It must remain exactly as provided. Director detection rule If the director of the uploaded film still is one of the 8 directors listed below, then the tile for that same director must be an exact duplicate of the ORIGINAL center tile, with no changes at all (same image content, same framing, same colors, same lighting, same texture). Only apply the label. All other tiles follow the normal re-shoot rules. Grid rules 9 equal tiles in a clean 3x3 layout, thin uniform gutters between tiles. Each tile has a simple, readable label in the top-left corner, consistent font and size, high contrast, no warping. Center tile label: ORIGINAL Other tiles labels exactly: Alfred Hitchcock Akira Kurosawa Federico Fellini Andrei Tarkovsky Ingmar Bergman Jean-Luc Godard Agnès Varda Sergio Leone No other text, logos, subtitles, or watermarks. Keep the 3x3 alignment perfectly straight and clean. IDENTITY + GENDER LOCK (applies to ALL non-ORIGINAL tiles) - Use the ORIGINAL center tile as the single source of truth for every person’s identity. - Preserve the exact number of people and their roles/positions (no swapping who is who). - Do NOT change any person’s gender or gender presentation. No gender swap, no sex change, no cross-casting. - Keep each person’s key identity traits consistent: face structure, hairstyle length/type, facial hair (must NOT appear/disappear), makeup level (must NOT appear/disappear), body proportions, age range, skin tone, and distinctive features (moles/scars/glasses). - Do not turn one person into a different person. Do not merge faces. Do not split one person into two. Do not duplicate the same face across different people. - If any identity attribute is ambiguous, default to matching the ORIGINAL exactly. - Allowed changes are ONLY cinematic treatment per director: framing, lens feel, camera height, DOF, lighting, palette, contrast curve, texture, mood, and set emphasis. Identities must remain locked. NEGATIVE: gender swap, femininize/masculinize, add/remove beard, add/remove lipstick, change hair length drastically, face replacement, identity drift. CAST ANCHORING - Person A = left-most person in ORIGINAL, Person B = right-most person in ORIGINAL, Person C = center/back person in ORIGINAL, etc. - Each tile must keep Person A/B/C as the same individuals (same gender presentation and identity), only reshot cinematically. Content rules (for non-duplicate tiles) Maintain recognizable continuity across all tiles (who/where/what). Do not change identities into different people. Vary per director: framing, lens feel, camera height, depth of field, lighting, color palette, contrast curve, texture, production design emphasis, mood. Ultra-sharp cinematic stills (except where diffusion is specified), coherent lighting, correct anatomy, no duplicated faces, no mangled hands, no broken perspective, no glitch artifacts, and perfectly readable labels. Director-specific style and color grading (apply strongly per tile, unless the duplicate rule applies) Alfred Hitchcock Palette: muted neutrals, cool grays, sickly greens, deep blacks, occasional saturated red accent. Contrast: high contrast with crisp, suspenseful shadows. Texture: classic 35mm cleanliness with tense atmosphere. Lens/DOF: 35–50mm, controlled depth, precise geometry. Lighting/Blocking: noir-influenced practicals, hard key, voyeuristic framing, psychological tension. Akira Kurosawa Palette: earthy desaturated browns/greens; restrained primaries if color. Contrast: bold tonal separation, punchy blacks. Texture: gritty film grain, tactile elements (mud, rain, wind). Lens/DOF: 24–50mm with deep focus; dynamic staging and strong geometry. Lighting/Atmosphere: dramatic natural light, weather as design (fog, rain streaks, backlight). Federico Fellini Palette: warm ambers, carnival reds, creamy highlights, pastel accents. Contrast: medium contrast, dreamy glow and gentle bloom. Texture: soft diffusion, theatrical surreal polish. Lens/DOF: normal to wide, staged tableaux, rich background set dressing. Lighting: expressive, stage-like, whimsical yet melancholic mood. Andrei Tarkovsky Palette: subdued sepia/olive, cold cyan-gray, low saturation, weathered tones. Contrast: low-to-medium, soft highlight roll-off. Texture: organic grain, misty air, water stains, aged surfaces. Lens/DOF: 50–85mm, contemplative framing, naturalistic DOF. Lighting/Atmosphere: window light, overcast feel, poetic elements (fog, rain, smoke), quiet intensity. Ingmar Bergman Palette: near-monochrome restraint, cold grays, pale skin tones, minimal color distractions. Contrast: high contrast, sculpted faces, deep shadows. Texture: clean, intimate, psychologically focused. Lens/DOF: 50–85mm, tighter framing, shallow-to-medium DOF. Lighting: strong key with dramatic falloff, emotionally intense portraits. Jean-Luc Godard Palette: bold primaries (red/blue/yellow) punctuating neutrals, or intentionally flat natural colors. Contrast: medium contrast, occasional slightly overexposed highlights. Texture: raw 16mm/35mm energy, imperfect and alive. Lens/DOF: wider lenses, spontaneous off-center composition. Lighting: available light feel, street/neon/practicals, documentary new-wave immediacy. Agnès Varda Palette: warm natural daylight, gentle pastels, honest skin tones, subtle complementary colors. Contrast: medium, soft and inviting. Texture: tactile lived-in realism, subtle film grain. Lens/DOF: 28–50mm, environmental portrait framing with context. Lighting: naturalistic, human-first, intimate but open atmosphere. Sergio Leone Palette: sunbaked golds, dusty oranges, sepia browns, deep shadows, occasional turquoise sky tones. Contrast: high contrast, harsh sun, strong silhouettes. Texture: gritty dust, sweat, leather, weathered surfaces, pronounced grain. Lens/DOF: extreme wide (24–35mm) and extreme close-up language; shallow DOF for eyes/details. Lighting/Mood: hard sunlight, rim light, operatic tension, iconic dramatic shadow shapes. Output: a single final 3x3 grid image only.
![Architectural Study Sheet: [HISTORIC_SITE_NAME]](https://prompts-chat-space.fra1.digitaloceanspaces.com/prompt-media/prompt-media-1765704322514-417ujb.jpg)
Image
A vintage architectural infographic of [HISTORIC_SITE_NAME] that blends art and technical clarity: a detailed front elevation at the center, a clean line-art landscape of [LOCATION] behind it, and annotated dimension lines with sample values like “[HEIGHT_VALUE_1]” and “[HEIGHT_VALUE_2]”. Surrounded by 2–3 close-up detail boxes and a “Site plan – [LOCATION]” panel, the piece uses pen-and-ink hatching on warm aged paper to feel like a hand-drawn architectural study sheet.
A vintage architectural infographic of historic_site_name that blends art and technical clarity: a detailed front elevation at the center, a clean line-art landscape of location behind it, and annotated dimension lines with sample values like “height_value_1” and “height_value_2”. Surrounded by 2–3 close-up detail boxes and a “Site plan – location” panel, the piece uses pen-and-ink hatching on warm aged paper to feel like a hand-drawn architectural study sheet.
Image
Creates a clean, high-resolution badge photo with soft even lighting, a plain solid background, and a corporate outfit, ready for internal tools and profiles.
Create a modern corporate ID photo of the person from the uploaded image, suitable for company badges and internal systems. Keep the face identical to the uploaded image, with realistic proportions, no beautification or age adjustment. Framing: • Neutral, centered head and shoulders • Subject looking straight at the camera with a neutral but friendly expression Background: • Plain, uniform background in [BACKGROUND_COLOR], no texture, no gradient • No props, no text, no logos Style: • Even, soft lighting with minimal shadows • High clarity and sharpness around the face, natural skin tones, high-resolution Outfit: • Transform clothing into [OUTFIT_STYLE] that matches a corporate environment • No visible logos, patterns or distracting accessories Make the result look like an upgraded, well-lit, professional version of a corporate ID or access badge photo, ready to be dropped into internal tools, email accounts or passes.
Image
Generates a vertical collage of five distinct black-and-white fine art portraits of a woman, emulating 35mm film with visible grain and high contrast. Features intimate close-ups, spontaneous laughter, and moody split lighting. Captures raw emotion, unretouched skin texture, and a chic editorial fashion aesthetic with masterful chiaroscuro and photorealistic detail.
A vertical collage of 5 distinct black and white fine art portraits of a woman, shot on 35mm film with visible grain and high contrast. Top Left: Intimate close-up, she rests her chin on her hand, smiling softly, messy hair strands on face, wearing a dangling earring, soft window light.Top Right: Spontaneous joy, head thrown back laughing, hand running through messy hair, wearing a white t-shirt, dramatic high-contrast lighting.Middle Left: Extreme close-up profile shot, sharp focus on the eye and nose, visible freckles and skin texture, half face in deep shadow (split lighting).Bottom Left: Wearing a chunky knit sweater, hands holding her head, intense gaze at camera, prominent eyebrows, soft moody lighting.Bottom Right: Artistic composition, a face in profile silhouette close to another face looking at the camera, wearing a black turtleneck, low-key lighting with deep blacks. Style: Editorial fashion photography, raw emotion, unretouched skin texture, chiaroscuro, moody atmosphere, masterpiece, photorealistic.
Image
“Create an isometric miniature 3D diorama representing the iconic architecture of country_name through famous_structure. Use a 45° top-down view. Apply clean soft textures and realistic PBR materials. Lighting feels balanced and natural. The raised base includes nearby streets, landscape features, and cultural details linked to the structure. Add tiny stylized locals and visitors with heavy facial details. Background stays solid background_color. Top center text shows country_name in bold. Second line shows structure_name. Place a minimal architecture icon below. Text color adjusts for contrast.”
Image
Recreates your uploaded photo as a believable still from classic The Simpsons, converting every person and any animals while preserving the exact count, poses, and composition. Background and props are adapted to a Springfield-like look with clean cel shading and no text or watermarks.
Use the uploaded photo as the ONLY reference for composition and subjects. Recreate it as a clean, believable still frame from “The Simpsons” (classic seasons look), with consistent show-accurate character design and background painting. Core requirement - EVERY visible subject in the photo must be converted into a Simpsons-style character, including: - Multiple humans - Babies/children - Pets and animals (cats, dogs, birds, etc.) - Do not keep any subject photorealistic. No “half-real, half-cartoon” results. Identity and count lock - Keep the exact number of humans and animals. - Keep each subject’s position, relative size, pose, gesture, and gaze direction. - Keep key identity cues per subject: hairstyle, facial hair, glasses, distinctive accessories, clothing type, and overall vibe. - Do NOT merge people, remove animals, invent extra characters, or swap who is who. Simpsons character design rules (must match the show) - Skin: Simpsons yellow for humans, with show-typical flat fills. - Eyes: large white round eyes with small black dot pupils (no detailed irises). - Nose: simple rounded nose shape, minimal lines. - Mouth: simple linework, subtle overbite feel when fitting. - Hands: 4 fingers for humans (Simpsons standard). - Linework: clean black outlines, uniform thickness, no sketchy strokes. - Shading: minimal cel-style shading only, no realistic shadows or textures. Animals conversion rules (show-accurate) - Convert each animal into a Simpsons-like version: - Simplified body shapes, bold outlines, flat colors - Expressive but simple face: dot pupils, minimal muzzle detail - Keep species readable and preserve unique markings (spots, fur color blocks) in simplified form. Clothing and accessories - Keep the original outfits and accessories but simplify details into flat color blocks. - Preserve logos/patterns only if they were clearly present, but simplify heavily. - No added text on clothing. Background and environment - Convert the background into a Simpsons Springfield-like environment that matches the original setting: - If indoors: simple pastel walls, clean props, basic perspective, typical sitcom staging. - If outdoors: bright sky, simplified buildings/trees, Springfield color palette. - Keep major background objects (tables, phones, chairs, signs) but simplify to animation props. - Do not change the location type (do not move it to Moe’s, Kwik-E-Mart, or the Simpsons house unless the original already matches that kind of place). Camera and framing - Match the original camera angle, lens feel, crop, and spacing. - Keep it as a single TV frame, not a poster. Quality and negatives - No text, subtitles, captions, watermarks, logos, UI, or borders. - No 3D, no painterly look, no anime, no caricature exaggeration beyond Simpsons norms. - No uncanny face drift: characters must look like Simpsons characters while still clearly mapping to each subject in the photo. - High resolution, crisp edges, clean colors, looks like an actual episode screenshot.
Latest Prompts
Video
A boy teaching the bangla meaning of manifestations with example nicely in 8s
A boy teaching the bangla meaning of manifestations with example nicely in 8s
TrendingImage
A compact Midjourney prompt for a striking vertical anime-style poster: a girl with a blue wolf-cut hairstyle caught in a playful moment against planets and alien spacecraft, pushed through an extreme 180-degree fisheye lens with heavy barrel distortion, so the frame edges bend inward and the center bulges toward you. Bold graphic shapes, cinematic lighting, deep shadows and a large word of your choice in the background. Tuned with chaos 50, raw mode, stylize 400 and a 1:2 aspect ratio.
Digital animation style illustration. beautiful blue wolfcut hair girl, space planet background, alien spacecraft, funny moment, wide Extreme perspective effect, lens distortion, strong sense of depth, minimalist vibe, text "STARDUST" in the background, featuring strong circular barrel distortion. The edges of the frame bend drastically inward while the center bulges out, delivering an extreme 180-degree fisheye perspective, cinematic lighting, and deep shadows. --chaos 50 --ar 1:2 --raw --stylize 400 --hd0
TrendingImage
A detailed style-transfer prompt that turns the character in your reference image into a rough, cute Japanese anime doodle: wobbly uneven black crayon lines, big flat color blocks that spill past the outlines, quick white highlights, pink blush strokes and visible crayon grain, as a half-body portrait on a pure white 1:1 canvas. It keeps the character's hairstyle, hair color, eyes, outfit and signature expression recognizable while banning polished line art, gradients and 3D shading.
Convert the character in the reference image into a rough, Japanese-style digital doodle. Overall style: An extremely casual, rough and naive cute Japanese anime character doodle, as if drawn quickly with the rough crayon and marker brushes of an ordinary painting app. Keep the original character recognizable: hairstyle, hair color, facial features, outfit, accessories and signature expression. Line art: * Outline the character with obvious, rough black strokes. * Line weight is very uneven: some lines suddenly get thicker, some break off. * Contours are loose, inaccurate and slightly crooked. * Lines have a clear hand-drawn grainy, smudged texture. * Do not aim for precise outlines; misaligned, overlapping and incomplete lines are allowed. * No fine, smooth vector line art. Coloring: * Use large areas of simple, opaque flat color. * Colors may spill slightly outside the lines; missed spots and white gaps are allowed. * Shadows use a few rough gray strokes or darker strokes of the same hue. * Highlights are casual, short white strokes. * Keep the rough texture of mixed crayon, pastel and marker. * No complex gradients, detailed lighting or rich layers of color. Facial features: * Keep the original character's eye color, eye shape and signature look. * Simplify the features; draw the eyes with thick black lines and simple color blocks. * Keep the mouth as simple as possible; the nose can be left out. * A few casual pink blush strokes can be added to the cheeks. * Keep the character's expression and personality; do not change their temperament. Hair and outfit: * Fully keep the character's most recognizable hairstyle and hair color. * Build the hair from a few large color blocks; do not draw lots of fine strands. * Keep the outfit's original colors, silhouette and signature accessories. * Heavily simplify clothing folds and decorations. * Do not change the outfit or add accessories that are not in the original image. Composition: * 1:1 square canvas. * Half-body portrait of the character, with a slightly oversized head. * Character centered, with natural white space around them. * Pure white background; no text, complex scenery or decorative borders. Most important style constraint: The image must be rough, scribbly, simple and naive, like a cute anime doodle drawn on a whim, not a polished illustration deliberately imitating a sketch. No automatic retouching, no fine line art, no complex hair structure, no subtle gradients, no 3D effects, no heavy lighting, no added complex outfit details. Final result: a low-finish Japanese anime digital doodle with rough black outlines, large flat color blocks, casual white highlights and an obvious crayon grain.
0
Create a reusable skill for vehicle-specific DIY repair manuals grounded in verified OEM sources. Cover beginner-friendly maintenance, diagnostics, disassembly, rebuilding and engine overhaul. Generate accurate, reviewed black-and-white diagrams in every chapter, embedded beside relevant steps. Use professional 8.5×11-inch layout, 200–230 pages. First provide a detailed outline, page budget and figure-placement plan for one approval; then deliver one complete, illustrated, editable DOCX.
--- name: car-repair-manual-writer description: Create a reusable skill for vehicle-specific DIY repair manuals grounded in verified OEM sources. Cover beginner-friendly maintenance, diagnostics, disassembly, rebuilding and engine overhaul. Generate accurate, reviewed black-and-white diagrams in every chapter, embedded beside relevant steps. Use professional 8.5×11-inch layout, 200–230 pages. First provide a detailed outline, page budget and figure-placement plan for one approval; then deliver one complete, illustrated, editable DOCX. --- # My Skill Describe what this skill does and how the agent should use it. ## Instructions - Step 1: ... - Step 2: ...
Opinionated conventions for building clear, honest and accessible charts and dashboards.
# Data Visualization taste of a clarity-first data visualization developer - Start from the question the chart must answer, and write that question as the chart title or subtitle. Confidence: 0.90 - Choose the chart by the comparison: bars for categories, lines for trends over time, scatter plots for relationships. Confidence: 0.90 - Start bar chart value axes at zero; line charts may use a tighter range when the change is what matters. Confidence: 0.90 - Avoid pie charts with more than three slices, and never use 3D charts. Confidence: 0.85 - Sort categorical bars by value unless the categories have a natural order like months or ratings. Confidence: 0.85 - Label lines and series directly at the end of the line instead of making readers match colors with a legend. Confidence: 0.80 - Use a sequential palette for ordered data, a diverging palette around a meaningful midpoint, and a categorical palette for groups. Confidence: 0.85 - Keep categorical palettes to about seven colors and check them with a color-blindness simulator. Confidence: 0.85 - Never encode meaning with color alone; add labels, patterns, shapes or positions as well. Confidence: 0.90 - Remove chart junk: heavy gridlines, borders, shadows and decorative backgrounds. Confidence: 0.85 - Format numbers for humans with thousands separators, sensible rounding and units such as 1.2M or 35 percent. Confidence: 0.85 - Show uncertainty with confidence bands or error bars when the data comes from samples or forecasts. Confidence: 0.75 - Use a declarative library such as Vega-Lite, Observable Plot or ECharts for standard charts, and reach for D3 only for custom visuals. Confidence: 0.80 - Render with SVG for small and medium datasets, and switch to Canvas or WebGL above roughly ten thousand marks. Confidence: 0.75 - Make charts responsive by redesigning for small screens, for example fewer ticks or a horizontal bar layout, not just scaling down. Confidence: 0.80 - Provide a text summary and an accessible data table for every important chart. Confidence: 0.85 - Make tooltips keyboard accessible, and never hide key information only in hover states. Confidence: 0.80 - Aggregate or sample data on the server before sending it to the browser, rather than plotting millions of raw points. Confidence: 0.85 - Keep the same color for the same category across every chart in a dashboard. Confidence: 0.90 - Annotate notable events, like a release or an outage, directly on time series charts. Confidence: 0.75 - Show the data source and the last refresh time under each chart. Confidence: 0.85 - Test charts with real and edge-case data: empty series, single points, very long labels and negative values. Confidence: 0.80
0
Taste
Opinionated conventions for planning, running and reading load and performance tests for web services.
# Load Testing taste of a performance-minded reliability engineer - Start every load test from a written goal, such as p95 latency under 300 ms at 500 requests per second, not from a vague "see what breaks". Confidence: 0.95 - Write load tests as code with k6, Gatling or Locust and keep them in the same repository as the service. Confidence: 0.90 - Model realistic traffic from production logs: the mix of endpoints, payload sizes and think time between requests. Confidence: 0.90 - Use an open workload model with a fixed arrival rate when testing services that face the internet, since closed models hide queueing delays. Confidence: 0.85 - Run separate test types on purpose: smoke, load at expected peak, stress beyond peak, spike, and a long soak test for memory leaks. Confidence: 0.90 - Report latency as percentiles, at least p50, p95 and p99, and never rely on the average alone. Confidence: 0.95 - Define pass or fail thresholds in the test script so CI can fail the build automatically. Confidence: 0.85 - Run load tests against a production-like environment with the same instance sizes, data volume and configuration. Confidence: 0.90 - Seed test data that matches production cardinality, because a tiny database makes every query look fast. Confidence: 0.85 - Warm up caches and connection pools before measuring, and exclude the warm-up period from results. Confidence: 0.75 - Generate load from machines with enough CPU and network headroom, and watch the load generator's own metrics. Confidence: 0.85 - Correlate test results with server-side metrics, traces and logs to find the real bottleneck instead of guessing. Confidence: 0.90 - Track error rate and timeouts next to latency; a fast response that returns an error is not a success. Confidence: 0.90 - Change one variable per run and record the commit, configuration and environment with each result. Confidence: 0.85 - Run a short performance smoke test on every merge to main and the full suite before major releases. Confidence: 0.80 - Compare results with a stored baseline and flag regressions larger than an agreed percentage. Confidence: 0.80 - Mock or sandbox third-party APIs that charge per call or enforce rate limits, but test your own dependencies for real. Confidence: 0.80 - Find the breaking point and document how the system fails: graceful rejection with 429 or 503 is better than collapse. Confidence: 0.85 - Verify that autoscaling reacts in time by ramping load gradually and measuring how long new capacity takes to help. Confidence: 0.75 - Announce load tests to the team and on-call engineers, and never point them at shared production systems without approval. Confidence: 0.95 - Turn findings into capacity plans with clear headroom targets, such as running at no more than 60 percent of the tested limit. Confidence: 0.70
0
Taste
Opinionated conventions for a fast, maintainable and portable Lua-based Neovim configuration.
# Neovim Config taste of a minimalist terminal-first developer - Write the whole config in Lua, starting from a single init.lua that requires small modules under lua/config and lua/plugins. Confidence: 0.90 - Use lazy.nvim as the plugin manager and commit lazy-lock.json so every machine gets the same plugin versions. Confidence: 0.90 - Lazy-load plugins by event, command, filetype or key mapping, and keep startup time under 50 ms measured with :Lazy profile. Confidence: 0.80 - Prefer the built-in LSP client with nvim-lspconfig over heavier all-in-one language plugins. Confidence: 0.85 - Install language servers, formatters and linters with mason.nvim, but pin the tool list in config instead of installing by hand. Confidence: 0.80 - Format on save with conform.nvim and lint with nvim-lint, using the same tools and settings the project runs in CI. Confidence: 0.85 - Use nvim-treesitter for highlighting, indentation and text objects, and list the parsers you need explicitly. Confidence: 0.85 - Pick one fuzzy finder, such as telescope.nvim or fzf-lua, and route files, grep, buffers and LSP symbols through it. Confidence: 0.85 - Set the leader key to space before loading any plugin so every mapping uses it. Confidence: 0.90 - Give every custom mapping a desc field so which-key and :map show what it does. Confidence: 0.85 - Group mappings by prefix, like leader f for find, leader g for git and leader l for LSP, and avoid overriding core Vim motions. Confidence: 0.80 - Keep options in one options.lua file using vim.opt, with a short comment for anything that is not obvious. Confidence: 0.80 - Use relative line numbers, a sign column that is always shown, and persistent undo files. Confidence: 0.75 - Use autocommand groups with clear = true so reloading the config never duplicates handlers. Confidence: 0.90 - Respect .editorconfig files and avoid hard-coding indentation per language unless a project has no settings. Confidence: 0.80 - Show git changes in the sign column with gitsigns.nvim and stage hunks from the editor. Confidence: 0.80 - Use the built-in completion engine or blink.cmp, with LSP and snippet sources only, to keep the popup fast and relevant. Confidence: 0.70 - Choose one colorscheme with good Tree-sitter and LSP semantic token support, and do not chase new themes every week. Confidence: 0.65 - Add a plugin only when it replaces a repeated manual step, and remove plugins you have not used in a month. Confidence: 0.80 - Keep machine-specific settings in a git-ignored local.lua file so the main config stays portable. Confidence: 0.75 - Run :checkhealth after upgrades and fix warnings before adding new plugins. Confidence: 0.80 - Store the config in a dotfiles repository and upgrade plugins deliberately, reviewing the lazy.nvim changelog first. Confidence: 0.85
0
Builds a seating chart for weddings, dinners and team events from your tables and guest list - keeps couples and families together, honours sit-with and keep-apart requests and head-table seats, puts mobility needs at accessible tables, seats nobody among strangers and fills tables by group. Flags misspelled names, duplicates, conflicting requests and missing seats; prints place cards and meal counts. Includes an offline stdlib Python planner.
---
name: event-seating-chart-planner
description: Builds a seating chart for weddings, dinners and team events from your tables and guest list - keeps couples and families together, honours sit-with and keep-apart requests and head-table seats, puts mobility needs at accessible tables, seats nobody among strangers and fills tables by group. Flags misspelled names, duplicates, conflicting requests and missing seats; prints place cards and meal counts. Includes an offline stdlib Python planner.
---
# Event Seating Chart Planner
You help hosts turn a guest list into a seating chart without the spreadsheet agony. Seating is the job everyone leaves until the last week: the divorced uncle and aunt must not share a table, grandma needs a step-free spot by the door, the plus-one knows nobody, two RSVPs are still missing, the caterer wants vegan and child meals per table, and every change breaks something else. You collect the tables and the guest list, check the list for problems first, build a chart that meets the hard requests, explain the trade-offs and produce place cards and a caterer sheet.
You work only from the information the host gives you. You do not judge family politics: when two requests conflict, say so and ask the host which one wins. Keep the guest list private - do not repeat notes about relationships beyond what the chart needs.
## Files in this skill
- `scripts/seating_plan.py` - reads an event JSON (tables with seats, accessible, kids, fixed head-table guests; rules) and a guest CSV (name, party, group, rsvp, child, needs, diet, sit_with, keep_apart), merges parties and sit-with requests, places them table by table and improves the plan by moving and swapping groups; reports SC01-SC10 and prints the chart, a caterer summary and place cards; `--csv` place-card export, `--json`, `--include-pending` (Python 3.8+ standard library only)
- `references/seating-rules-and-etiquette.md` - how to collect the list, what counts as a hard or soft request, head table and family conventions, accessibility, children, dietary needs and room layout tips
- `references/checks-and-codes.md` - every finding code, its severity and what to do, plus the input format and how the planner scores a chart
- `templates/seating-brief.md` - the summary to send the host (and the venue / caterer)
- `examples/event.json` - a wedding dinner with a head table, an accessible table, four tables of 8 and a kids table
- `examples/guests.csv` - 32 rows with families, friends, work colleagues, a declined and a pending RSVP, a duplicate row, a misspelled sit-with name, a keep-apart pair, a wheelchair user and dietary needs
- `examples/seating-chart.md` - the real planner output on the example
## Workflow
### 1. Collect the tables and the list
Ask for the venue's table plan (number of tables, seats per table, which are step-free or near the exit, a kids table, the head table and who sits there). Ask for the guest list with RSVP, party (people who arrive together: couple, family), group (how they know the hosts: bride family, work, school friends), children, mobility or other needs, meal choice, and any "must sit with" or "keep apart" requests. Put them in `examples/event.json` and `examples/guests.csv` form.
### 2. Run the planner
```
python3 scripts/seating_plan.py examples/event.json examples/guests.csv
python3 scripts/seating_plan.py event.json guests.csv --include-pending
python3 scripts/seating_plan.py event.json guests.csv --csv > place-cards.csv
python3 scripts/seating_plan.py event.json guests.csv --json
python3 scripts/seating_plan.py --self-test
```
Exit 0 = all hard requests met, 1 = a hard request failed or the list has a high finding, 2 = bad input. Without a shell, seat fixed guests first, then the accessibility needs, then the largest groups, and check every keep-apart pair at the end.
### 3. Read the result
- High: SC01 not enough seats (or a group that fits nowhere), SC02 conflicting or broken keep-apart requests, SC03 names in requests or fixed seats that are not on the attending list (spelling suggestions shown).
- Medium: SC04 a guest at a table with nobody they know, SC05 a mobility need at a non-accessible table, SC08 duplicate rows, SC09 parties or requests too big for one table, SC10 a child without an adult from their party.
- Low/info: half-empty or empty tables (SC06), pending RSVPs seated provisionally (SC07).
### 4. Adjust with the host
Fix the list problems first (spelling, duplicates, RSVPs) and re-run. Then walk the host through each table: who is there and why, the lonely guests and the trade-offs. Make manual moves the host asks for and re-run to confirm the keep-apart pairs still hold. Fill `templates/seating-brief.md`.
### 5. Deliver
Return the chart per table, the open questions, the place-card list A-Z, the meal counts per table and in total, and the special needs list for the venue (wheelchair space, high chairs, allergies).
## Example result
29 guests attend (1 declined, 1 pending left out) for 44 seats. The couple, maid of honour, best man and Zeynep (who asked to sit with Selin) fill the head table. Grandma Fatma (wheelchair) sits at accessible Table 1 with the Kaya family; Linda and Richard Moore are kept apart (Tables 2 and 3); the work colleagues share Table 4 with the bride's friends. Sam's request to sit with "Olivr Grant" is a typo of Oliver Grant, Merve Sahin is listed twice, and neighbour Kemal knows nobody at his table. The kids table is empty because children stay with their parents.
## Rules
- Hard requests (keep apart, fixed seats, accessibility) beat soft ones (groups, balance); say clearly which request was dropped and why.
- Never split a couple or a parent and a young child unless the host asks.
- Do not guess at conflicts: ask the host, and keep sensitive notes out of anything printed.
- Re-run after every manual change; the chart is only valid for the list it was made from.
- Pending RSVPs are left out unless the host says to seat them; chase them before printing place cards.
FILE:references/seating-rules-and-etiquette.md
# Seating rules and etiquette
## Collecting the list
- One row per person, including children and plus-ones (use "Guest of <name>" until you have a name).
- Party = who arrives together and must sit together (couple, parent with young children). Group = how they know the hosts; it decides who shares a table.
- Ask the hosts directly for keep-apart pairs (exes, family feuds) and keep this column out of anything printed or shared with the venue.
- RSVP status: seat only confirmed guests; set a deadline for pending ones about 3 weeks before the event, when most venues need final numbers.
## Hard vs soft requests
- Hard: keep apart, fixed seats (head table, speakers, VIPs), accessibility, a young child next to a parent, capacity.
- Soft: sit with friends, tables by group, balanced tables, mixing groups at networking events.
When a soft request breaks a hard one, the hard one wins; tell the host.
## Common conventions
- Weddings: the head table (couple, wedding party, sometimes parents) faces the room; parents and grandparents at the tables closest to it; families of both sides near the front; friends and colleagues further back. Sweetheart table = couple only.
- Family dinners and birthdays: the guest of honour in the middle of the long side, with the people they see least often nearby.
- Corporate dinners: a host from the company at every table; mix departments if networking is the goal (`mix_groups: true`), seat speakers near the stage and the exit.
- Round tables of 8-10 work best for conversation; 12+ means people only talk to their neighbours.
- Avoid a table where one guest is the only one from their group - pair singles with someone outgoing or a similar-age group.
## Accessibility and needs
- Wheelchair users: a table on a step-free route near the door and the toilets, with a chair removed at the place (mark it on the room plan).
- Hearing impairment: away from speakers and the band, facing the room.
- Older guests: away from loudspeakers and the dance floor, near the exit and toilets.
- High chairs and booster seats: tell the venue per table.
- Allergies: list name, table and allergen for the caterer; a printed card at the place for severe allergies.
## Children
- Toddlers stay with their parents. A kids table works for ages about 5-12 when it is next to the parents' tables and has an adult or sitter nearby.
- Count child meals separately (and high chairs) in the caterer summary.
## Room layout tips
- Number tables in a way guests can find (signs on every table, an alphabetical escort-card list at the entrance).
- Keep the path from the door to the accessible table clear.
- Leave 1-2 empty seats across the room for late changes; venues usually allow 1-2 extra chairs per round table, but check the fire-safety capacity.
## Final week checklist
- Final RSVPs and meal choices -> re-run the planner -> host approval.
- Send the venue: table plan, guest count per table, high chairs, wheelchair spaces.
- Send the caterer: meals per table and in total, allergies with names and tables.
- Print place cards and the escort-card list from `--csv`.
FILE:references/checks-and-codes.md
# Checks and finding codes
| Code | Severity | Check | What to do |
|---|---|---|---|
| SC01 | high | more attending guests than seats, or a party/group that fits at no table with enough free seats | add a table or seats, confirm RSVPs, split the group over neighbouring tables |
| SC02 | high | a sit-with request joins two guests who must be kept apart (request dropped); keep-apart inside one party; a keep-apart pair seated together | ask the host which request wins |
| SC03 | high | a name in sit_with / keep_apart or a fixed seat is not on the attending list (did-you-mean suggestion) | fix the spelling or add the guest |
| SC04 | medium | guest at a table with fewer than `min_known` people from their party, group or sit-with list | swap, or seat them next to a sociable guest |
| SC05 | medium | wheelchair / step-free / walker / mobility / crutches need at a table not marked accessible | swap with someone at an accessible table |
| SC06 | low: table under half full; info: empty table | balance | merge tables or remove one |
| SC07 | info | RSVP pending, seated because of `--include-pending` | chase the RSVP |
| SC08 | medium | the same name twice (seated once), row without a name | check if two different people; add an initial |
| SC09 | medium | a party larger than the largest table (split), a sit-with group that would exceed the largest table (request dropped), a party split over tables | neighbouring tables; free seats at one table |
| SC10 | medium | child at a non-kids table without an adult from their party | move next to their parents |
## Verdict
- **N hard request(s) could not be met** - any high finding.
- **all hard requests met, N soft issue(s)** - medium findings only.
- **all requests met**.
## How the planner works
1. Attending guests only (rsvp yes; pending with `--include-pending`; no/declined skipped).
2. Parties are merged (when `keep_parties_together`), then sit-with requests, unless that joins a keep-apart pair or exceeds the largest table.
3. Groups are placed in order: fixed head-table guests (only they and their sit-with partners use a table with `fixed`), mobility needs, then by group size.
4. Each group goes to the table where the chart's penalty rises least; then the planner moves single groups, whole groups and swaps pairs while the penalty falls.
5. Penalty: keep-apart pair at one table 100, mobility need at a non-accessible table 40, a guest who knows fewer than `min_known` people 12, each extra group at a table 2 (unless `mix_groups`), each extra table a group is spread over 3, an adult at the kids table 3.
The plan is deterministic: the same input gives the same chart.
## Event JSON
`event, date, rules{keep_parties_together (true), mix_groups (false), min_known (1)}, tables[{name, seats, accessible, kids, fixed[names], notes}]`.
## Guest CSV
`name, party, group, rsvp (yes/no/pending), child (yes), needs (wheelchair; high chair; nut allergy), diet (vegetarian, vegan, gluten-free, child menu ...), sit_with (names separated by ;), keep_apart (names separated by ;)`. Only `name` is required; party defaults to the name, group to "-", rsvp to yes.
FILE:templates/seating-brief.md
# Seating brief: <event> (<date>)
**Guests:** <29 attending (1 declined, 1 pending)> **Seats:** <44 at 6 tables> **Status:** <draft 2 - waiting for 1 RSVP>
## Open questions for the host
- [ ] <Sam asked to sit with "Olivr Grant" - Oliver Grant? (seated together after the fix)>
- [ ] <Merve Sahin is on the list twice - one person or two?>
- [ ] <Kemal knows nobody at Table 3 - who should he sit next to?>
- [ ] <Chris Evans: RSVP pending - seat at Table 3 if he comes>
## Tables
| Table | Who | Notes |
|---|---|---|
| <Head table> | <Elif, Daniel, Selin, Tom, Zeynep> | <facing the room> |
| <Table 1 (accessible)> | <Kaya family, Grandma Fatma> | <wheelchair place on the aisle, high chair for Ela> |
## For the venue
- Tables and seat counts: <...>
- Wheelchair places: <Table 1 x1> High chairs: <Table 1 x1>
- Remove: <kids table (empty)>
## For the caterer
| Table | Standard | Vegetarian | Vegan | Gluten-free | Child | Other |
|---|---|---|---|---|---|---|
| <Head table> | <3> | <2> | <0> | <0> | <0> | <-> |
| **Total** | <18> | <3> | <2> | <1> | <3> | <pescatarian 1, soft food 1> |
Allergies: <Max Hill (Table 2) - nut allergy>
## Place cards
<attach place-cards.csv from `seating_plan.py --csv`>
FILE:examples/event.json
{
"event": "Elif and Daniel's wedding dinner",
"date": "2027-06-12",
"rules": {"keep_parties_together": true, "mix_groups": false, "min_known": 1},
"tables": [
{"name": "Head table", "seats": 6, "fixed": ["Elif Kaya", "Daniel Moore"], "notes": "facing the room"},
{"name": "Table 1", "seats": 8, "accessible": true, "notes": "next to the terrace door, step-free"},
{"name": "Table 2", "seats": 8},
{"name": "Table 3", "seats": 8},
{"name": "Table 4", "seats": 8},
{"name": "Kids table", "seats": 6, "kids": true, "notes": "near Table 2, crayons and placemats"}
]
}
FILE:examples/guests.csv
name,party,group,rsvp,child,needs,diet,sit_with,keep_apart
Elif Kaya,Couple,couple,yes,,,vegetarian,,
Daniel Moore,Couple,couple,yes,,,standard,,
Selin Kaya,Maid of honour,bride friends,yes,,,standard,Elif Kaya,
Tom Moore,Best man,groom family,yes,,,standard,Daniel Moore,
Ayse Kaya,Kaya parents,bride family,yes,,,standard,,
Mehmet Kaya,Kaya parents,bride family,yes,,,standard,,
Fatma Yilmaz,Grandma Fatma,bride family,yes,,wheelchair,soft food,Ayse Kaya,
Can Kaya,Can family,bride family,yes,,,standard,,
Deniz Kaya,Can family,bride family,yes,,,vegan,,
Ela Kaya,Can family,bride family,yes,yes,high chair,child menu,,
Linda Moore,Linda,groom family,yes,,,gluten-free,,Richard Moore
Richard Moore,Richard and Jo,groom family,yes,,,standard,,Linda Moore
Jo Parker,Richard and Jo,groom family,yes,,,standard,,
Sarah Moore,Sarah family,groom family,yes,,,standard,,
James Hill,Sarah family,groom family,yes,,,standard,,
Lily Hill,Sarah family,groom family,yes,yes,,child menu,,
Max Hill,Sarah family,groom family,yes,yes,nut allergy,child menu,,
Zeynep Arslan,Zeynep,bride friends,yes,,,vegetarian,Selin Kaya,
Burak Demir,Burak and Ece,bride friends,yes,,,standard,,
Ece Demir,Burak and Ece,bride friends,yes,,,standard,,
Merve Sahin,Merve,bride friends,yes,,,vegan,,
Oliver Grant,Oliver and Priya,groom friends,yes,,,standard,,
Priya Grant,Oliver and Priya,groom friends,yes,,,vegetarian,,
Sam Turner,Sam,groom friends,yes,,,standard,Olivr Grant,
Chris Evans,Chris,groom friends,pending,,,standard,,
Nina Patel,Nina,work,yes,,,standard,,
Leo Fischer,Leo and Mia,work,yes,,,standard,,
Mia Fischer,Leo and Mia,work,yes,,,pescatarian,,
Hannah Lee,Hannah,work,yes,,,standard,,
Peter Novak,Peter,work,no,,,standard,,
Kemal Ozturk,Kemal,neighbours,yes,,,standard,,
Merve Sahin,Merve,bride friends,yes,,,vegan,,
FILE:examples/seating-chart.md
# Seating chart: Elif and Daniel's wedding dinner (2027-06-12)
29 attending guest(s) (1 declined; 1 pending left out), 44 seat(s) at 6 table(s). Source: examples/guests.csv.
**Verdict: 1 hard request(s) could not be met - see findings**
Findings: 1 high, 2 medium, 0 low, 1 info.
## Tables
| Table | Seats | Guests | Groups | Meals |
|---|---|---|---|---|
| Head table [fixed] | 5/6 | Tom Moore, Elif Kaya, Daniel Moore, Selin Kaya, Zeynep Arslan | bride friends 2, couple 2, groom family 1 | standard 3, vegetarian 2 |
| Table 1 [accessible] | 6/8 | Can Kaya, Deniz Kaya, Ela Kaya (child), Fatma Yilmaz *, Ayse Kaya, Mehmet Kaya | bride family 6 | child menu (child) 1, soft food 1, standard 3, vegan 1 |
| Table 2 | 5/8 | Linda Moore, Sarah Moore, James Hill, Lily Hill (child), Max Hill (child) | groom family 5 | child menu (child) 2, gluten-free 1, standard 2 |
| Table 3 | 6/8 | Kemal Ozturk, Oliver Grant, Priya Grant, Richard Moore, Jo Parker, Sam Turner | groom family 2, groom friends 3, neighbours 1 | standard 5, vegetarian 1 |
| Table 4 | 7/8 | Burak Demir, Ece Demir, Hannah Lee, Leo Fischer, Mia Fischer, Merve Sahin, Nina Patel | bride friends 3, work 4 | pescatarian 1, standard 5, vegan 1 |
| Kids table [kids] | 0/6 | - | - | - |
`*` = mobility need (seat on the aisle side, nearest the door).
## Findings
| Sev | Code | Who | Finding | Fix |
|---|---|---|---|---|
| high | SC03 | Sam Turner | sit_with 'Olivr Grant' is not on the (attending) guest list - did you mean Oliver Grant? | fix the spelling |
| medium | SC04 | Kemal Ozturk | at Table 3 without anyone from their party or group (neighbours) | seat them next to the most sociable guest there, or swap |
| medium | SC08 | Merve Sahin | listed twice (lines 22 and 33) - seated once | check whether these are two different people; add a surname or initial |
| info | SC06 | Kids table | empty table | remove it from the room plan |
## Caterer summary
| Meal | Count |
|---|---|
| child menu (child) | 3 |
| gluten-free | 1 |
| pescatarian | 1 |
| soft food | 1 |
| standard | 18 |
| vegan | 2 |
| vegetarian | 3 |
Special needs: Ela Kaya (Table 1) - high chair; Fatma Yilmaz (Table 1) - wheelchair; Max Hill (Table 2) - nut allergy.
## Place cards (A-Z)
| Guest | Table |
|---|---|
| Ayse Kaya | Table 1 |
| Burak Demir | Table 4 |
| Can Kaya | Table 1 |
| Daniel Moore | Head table |
| Deniz Kaya | Table 1 |
| Ece Demir | Table 4 |
| Ela Kaya | Table 1 |
| Elif Kaya | Head table |
| Fatma Yilmaz | Table 1 |
| Hannah Lee | Table 4 |
| James Hill | Table 2 |
| Jo Parker | Table 3 |
| Kemal Ozturk | Table 3 |
| Leo Fischer | Table 4 |
| Lily Hill | Table 2 |
| Linda Moore | Table 2 |
| Max Hill | Table 2 |
| Mehmet Kaya | Table 1 |
| Merve Sahin | Table 4 |
| Mia Fischer | Table 4 |
| Nina Patel | Table 4 |
| Oliver Grant | Table 3 |
| Priya Grant | Table 3 |
| Richard Moore | Table 3 |
| Sam Turner | Table 3 |
| Sarah Moore | Table 2 |
| Selin Kaya | Head table |
| Tom Moore | Head table |
| Zeynep Arslan | Head table |
The chart is a starting point: move people by hand where you know better, then re-run to check the requests still hold.
FILE:scripts/seating_plan.py
#!/usr/bin/env python3
"""Event seating chart planner (stdlib only, Python 3.8+).
Reads an event file (tables with seat counts, accessible / kids / fixed head-table seats, rules)
and a guest list CSV (name, party, group, RSVP, child, needs, diet, sit_with, keep_apart) and
builds a seating chart: parties stay together, "sit with" requests share a table, "keep apart"
pairs never share one, guests with mobility needs go to accessible tables, nobody is seated
without someone they know, and tables are filled by group where possible. Checks the list first
(unknown or misspelled names, duplicates, impossible or conflicting requests, not enough seats)
and prints the chart, place cards and a per-table meal count for the caterer.
Usage:
seating_plan.py EVENT.json GUESTS.csv [--include-pending] [--csv] [--json]
seating_plan.py --self-test
Exit: 0 = all hard requests met, 1 = a hard request could not be met (or a high finding), 2 = bad input.
"""
import argparse, csv, difflib, io, json, sys
SEV = {"high": 0, "medium": 1, "low": 2, "info": 3}
EVENT_KEYS = {"event", "date", "tables", "rules"}
TABLE_KEYS = {"name", "seats", "accessible", "kids", "fixed", "notes"}
RULE_KEYS = {"keep_parties_together", "mix_groups", "min_known"}
MOBILITY = ("wheelchair", "step-free", "walker", "mobility", "crutches")
W_APART, W_ACCESS, W_LONELY, W_GROUP, W_SPREAD = 100, 40, 12, 2, 3
class InputError(Exception):
pass
def norm(s):
return " ".join(str(s or "").split()).lower()
def split_list(s):
return [x.strip() for x in str(s or "").replace(",", ";").split(";") if x.strip()]
# ---------------------------------------------------------------- load
def load_event(cfg):
if not isinstance(cfg, dict) or not isinstance(cfg.get("tables"), list) or not cfg["tables"]:
raise InputError("event file must be a JSON object with a non-empty \"tables\" list")
bad = set(cfg) - EVENT_KEYS
if bad:
raise InputError("unknown key(s) in event file: %s" % ", ".join(sorted(bad)))
rules = cfg.get("rules") or {}
badr = set(rules) - RULE_KEYS
if badr:
raise InputError("unknown rule(s): %s" % ", ".join(sorted(badr)))
tables, names = [], set()
for i, t in enumerate(cfg["tables"], 1):
badt = set(t) - TABLE_KEYS
if badt:
raise InputError("table #%d: unknown key(s) %s" % (i, ", ".join(sorted(badt))))
name = str(t.get("name") or "Table %d" % i)
if name in names:
raise InputError("table name %r used twice" % name)
names.add(name)
seats = t.get("seats")
if not isinstance(seats, int) or seats < 1:
raise InputError("table %s: seats must be a positive whole number, got %r" % (name, seats))
tables.append({"name": name, "seats": seats, "accessible": bool(t.get("accessible")), "kids": bool(t.get("kids")),
"fixed": [str(x) for x in t.get("fixed") or []], "notes": t.get("notes", "")})
return {"event": cfg.get("event", "Event"), "date": cfg.get("date", ""), "tables": tables,
"together": rules.get("keep_parties_together", True), "mix": bool(rules.get("mix_groups", False)),
"min_known": int(rules.get("min_known", 1))}
def load_guests(text, include_pending=False):
rows = list(csv.DictReader(io.StringIO(text)))
if not rows:
raise InputError("guest list is empty")
cols = {c.strip().lower() for c in rows[0].keys() if c}
if "name" not in cols:
raise InputError("guest list needs a 'name' column")
guests, skipped, F, seen = [], {"no": 0, "pending": 0}, [], {}
for ln, r in enumerate(rows, 2):
r = {(k or "").strip().lower(): (v or "").strip() for k, v in r.items()}
name = " ".join(r.get("name", "").split())
if not name:
F.append(("medium", "SC08", "line %d" % ln, "row without a name skipped", "fill in the name or delete the row"))
continue
rsvp = norm(r.get("rsvp") or "yes")
if rsvp in ("no", "declined", "n"):
skipped["no"] += 1
continue
if rsvp in ("pending", "maybe", "?", "invited", ""):
if not include_pending:
skipped["pending"] += 1
continue
if norm(name) in seen:
F.append(("medium", "SC08", name, "listed twice (lines %d and %d) - seated once" % (seen[norm(name)], ln), "check whether these are two different people; add a surname or initial"))
continue
seen[norm(name)] = ln
needs = [norm(x) for x in split_list(r.get("needs"))]
guests.append({"name": name, "party": r.get("party") or name, "group": r.get("group") or "-",
"child": norm(r.get("child")) in ("yes", "y", "true", "1", "child"),
"needs": needs, "mobility": any(any(m in n for m in MOBILITY) for n in needs),
"diet": norm(r.get("diet")) or "standard", "sit_with": split_list(r.get("sit_with")),
"keep_apart": split_list(r.get("keep_apart")), "line": ln, "pending": rsvp != "yes" and rsvp not in ("y", "accepted")})
return guests, skipped, F
# ---------------------------------------------------------------- plan
class DSU:
def __init__(self, n):
self.p = list(range(n))
def find(self, a):
while self.p[a] != a:
self.p[a] = self.p[self.p[a]]
a = self.p[a]
return a
def union(self, a, b):
self.p[self.find(a)] = self.find(b)
def plan(ev, guests, F=None):
F = list(F or [])
add = lambda sev, code, who, msg, fix: F.append((sev, code, who, msg, fix))
idx = {norm(g["name"]): i for i, g in enumerate(guests)}
allnames = [g["name"] for g in guests]
def resolve(who, ref, kind):
j = idx.get(norm(ref))
if j is None:
close = difflib.get_close_matches(ref, allnames, 1, 0.7)
add("high", "SC03", who, "%s %r is not on the (attending) guest list%s" % (kind, ref, " - did you mean %s?" % close[0] if close else ""),
"fix the spelling" if close else "add the guest or remove the request")
return j
n = len(guests)
seats = sum(t["seats"] for t in ev["tables"])
maxt = max(t["seats"] for t in ev["tables"])
if n > seats:
add("high", "SC01", "-", "%d guests but only %d seats (%d short)" % (n, seats, n - seats), "add a table or seats, or confirm the RSVPs")
dsu = DSU(n)
party_of = {}
for i, g in enumerate(guests):
party_of.setdefault(norm(g["party"]), []).append(i)
if ev["together"]:
for p, mem in party_of.items():
if len(mem) > maxt:
add("medium", "SC09", guests[mem[0]]["party"], "party of %d is larger than the largest table (%d) - it is split" % (len(mem), maxt), "seat the party on neighbouring tables")
for a, b in zip(mem, mem[1:]):
if (mem.index(b)) % maxt:
dsu.union(a, b)
else:
for a, b in zip(mem, mem[1:]):
dsu.union(a, b)
apart = set()
for i, g in enumerate(guests):
for ref in g["keep_apart"]:
j = resolve(g["name"], ref, "keep_apart")
if j is not None and j != i:
apart.add(tuple(sorted((i, j))))
# sit_with links, refusing those that would exceed the largest table or join a keep-apart pair
for i, g in enumerate(guests):
for ref in g["sit_with"]:
j = resolve(g["name"], ref, "sit_with")
if j is None or j == i:
continue
a, b = dsu.find(i), dsu.find(j)
if a == b:
continue
size = sum(1 for k in range(n) if dsu.find(k) in (a, b))
clash = [p for p in apart if {dsu.find(p[0]), dsu.find(p[1])} == {a, b}]
if clash:
x, y = clash[0]
add("high", "SC02", g["name"], "asks to sit with %s, but %s and %s must be kept apart - the request is dropped" % (guests[j]["name"], guests[x]["name"], guests[y]["name"]),
"ask the host which request wins")
continue
if size > maxt:
add("medium", "SC09", g["name"], "sitting with %s would make a group of %d (largest table %d) - request dropped" % (guests[j]["name"], size, maxt), "seat them on neighbouring tables")
continue
dsu.union(i, j)
for x, y in sorted(apart):
if dsu.find(x) == dsu.find(y):
add("high", "SC02", guests[x]["name"], "must be kept apart from %s but they are in the same party - cannot be met" % guests[y]["name"], "change the party or the request")
links = set()
for i, g in enumerate(guests):
for ref in g["sit_with"]:
j = idx.get(norm(ref))
if j is not None:
links.add((i, j)); links.add((j, i))
def knows(a, b):
ga, gb = guests[a], guests[b]
return (norm(ga["party"]) == norm(gb["party"]) or (ga["group"] == gb["group"] and ga["group"] != "-") or (a, b) in links)
clusters = {}
for i in range(n):
clusters.setdefault(dsu.find(i), []).append(i)
cl = list(clusters.values())
T = ev["tables"]
fixed_at = {}
for ti, t in enumerate(T):
for nm in t["fixed"]:
j = idx.get(norm(nm))
if j is None:
close = difflib.get_close_matches(nm, allnames, 1, 0.7)
add("high", "SC03", t["name"], "fixed seat for %r who is not on the attending list%s" % (nm, " - did you mean %s?" % close[0] if close else ""), "fix the name in the event file")
else:
fixed_at[j] = ti
assign = {}
load = [0] * len(T)
reserved = {ti for ti, t in enumerate(T) if t["fixed"]}
def pen_table(ti, members):
p = 0
mem = set(members)
for x, y in apart:
if x in mem and y in mem:
p += W_APART
groups = {}
for m in members:
g = guests[m]
if g["mobility"] and not T[ti]["accessible"]:
p += W_ACCESS
groups[g["group"]] = groups.get(g["group"], 0) + 1
if not ev["mix"]:
p += W_GROUP * max(0, len(groups) - 1)
for m in members:
g = guests[m]
known = sum(1 for o in members if o != m and knows(m, o))
if known < ev["min_known"]:
p += W_LONELY
if T[ti]["kids"]:
p += sum(3 for m in members if not guests[m]["child"])
return p
def members_of(ti):
return [m for c, t in assign.items() if t == ti for m in cl[c]]
def total():
p = sum(pen_table(ti, members_of(ti)) for ti in range(len(T)))
spread = {}
for c, ti in assign.items():
for m in cl[c]:
if guests[m]["group"] != "-":
spread.setdefault(guests[m]["group"], set()).add(ti)
return p + W_SPREAD * sum(len(v) - 1 for v in spread.values())
gsize = {}
for g in guests:
gsize[g["group"]] = gsize.get(g["group"], 0) + 1
order = sorted(range(len(cl)), key=lambda c: (-any(i in fixed_at for i in cl[c]), -any(guests[i]["mobility"] for i in cl[c]),
-gsize[guests[cl[c][0]]["group"]], guests[cl[c][0]]["group"], -len(cl[c]), cl[c][0]))
unseated = []
for c in order:
size = len(cl[c])
fx = [fixed_at[i] for i in cl[c] if i in fixed_at]
cands = [fx[0]] if fx else range(len(T))
best = None
for ti in cands:
if load[ti] + size > T[ti]["seats"] or (T[ti]["fixed"] and not fx and ti in reserved):
continue
assign[c] = ti
delta = total()
del assign[c]
key = (delta, -(load[ti] > 0), ti)
if best is None or key < best[0]:
best = (key, ti)
if best is None:
unseated.append(c)
continue
assign[c] = best[1]
load[best[1]] += size
# local search: move or swap clusters while it lowers the penalty (deterministic)
fixed_cl = {c for c in assign if any(i in fixed_at for i in cl[c])}
improved, rounds = True, 0
while improved and rounds < 50:
improved, rounds = False, rounds + 1
cur = total()
for c in sorted(assign):
if c in fixed_cl:
continue
for ti in range(len(T)):
if ti == assign[c] or load[ti] + len(cl[c]) > T[ti]["seats"] or ti in reserved:
continue
old = assign[c]
assign[c] = ti
new = total()
if new < cur:
load[old] -= len(cl[c]); load[ti] += len(cl[c]); cur = new; improved = True
else:
assign[c] = old
# move every cluster of one group (from all tables) to one table
for gname in sorted({guests[cl[c][0]]["group"] for c in assign if c not in fixed_cl}):
block = [c for c in assign if c not in fixed_cl and guests[cl[c][0]]["group"] == gname]
for b in range(len(T)):
if b in reserved:
continue
old = {c: assign[c] for c in block}
moving = sum(len(cl[c]) for c in block if old[c] != b)
if not moving or load[b] + moving > T[b]["seats"]:
continue
for c in block:
assign[c] = b
new = total()
if new < cur:
for c in block:
if old[c] != b:
load[old[c]] -= len(cl[c]); load[b] += len(cl[c])
cur = new; improved = True
break
for c in block:
assign[c] = old[c]
# move a whole group block (all clusters of one group at one table) to another table
for a in range(len(T)):
groups_here = sorted({guests[cl[c][0]]["group"] for c, x in assign.items() if x == a and c not in fixed_cl})
for gname in groups_here:
block = [c for c, x in assign.items() if x == a and c not in fixed_cl and guests[cl[c][0]]["group"] == gname]
bsize = sum(len(cl[c]) for c in block)
for b in range(len(T)):
if b == a or b in reserved or load[b] + bsize > T[b]["seats"]:
continue
for c in block:
assign[c] = b
new = total()
if new < cur:
load[a] -= bsize; load[b] += bsize; cur = new; improved = True
break
for c in block:
assign[c] = a
for c in sorted(assign):
for d in sorted(assign):
if d <= c or c in fixed_cl or d in fixed_cl or assign[c] == assign[d] or assign[c] in reserved or assign[d] in reserved:
continue
a, b = assign[c], assign[d]
if load[a] - len(cl[c]) + len(cl[d]) > T[a]["seats"] or load[b] - len(cl[d]) + len(cl[c]) > T[b]["seats"]:
continue
assign[c], assign[d] = b, a
new = total()
if new < cur:
load[a] += len(cl[d]) - len(cl[c]); load[b] += len(cl[c]) - len(cl[d]); cur = new; improved = True
else:
assign[c], assign[d] = a, b
seat = {}
for c, ti in assign.items():
for i in cl[c]:
seat[i] = ti
for c in unseated:
add("high", "SC01", ", ".join(guests[i]["name"] for i in cl[c]), "no table with %d free seats together - not seated" % len(cl[c]), "add seats or split the group across neighbouring tables")
# findings on the result
for x, y in sorted(apart):
if x in seat and y in seat and seat[x] == seat[y]:
add("high", "SC02", guests[x]["name"], "seated at %s together with %s although they must be kept apart" % (T[seat[x]]["name"], guests[y]["name"]), "move one of them by hand")
for i, g in enumerate(guests):
if i not in seat:
continue
ti = seat[i]
if g["mobility"] and not T[ti]["accessible"]:
add("medium", "SC05", g["name"], "needs %s but %s is not marked accessible" % ("/".join(g["needs"]), T[ti]["name"]), "swap with a guest at an accessible table")
mem = [m for m, t in seat.items() if t == ti and m != i]
known = [m for m in mem if knows(i, m)]
if len(known) < ev["min_known"]:
add("medium", "SC04", g["name"], "at %s without anyone from their party or group (%s)" % (T[ti]["name"], g["group"]), "seat them next to the most sociable guest there, or swap")
if g["child"] and not T[ti]["kids"] and not any(norm(guests[m]["party"]) == norm(g["party"]) and not guests[m]["child"] for m in mem):
add("medium", "SC10", g["name"], "child seated without an adult from their party", "move next to their parents or to the kids table")
if g["pending"]:
add("info", "SC07", g["name"], "RSVP still pending - seated provisionally", "chase the RSVP before printing place cards")
for ti, t in enumerate(T):
used = sum(1 for i in seat if seat[i] == ti)
if 0 < used < t["seats"] / 2:
add("low", "SC06", t["name"], "only %d of %d seats used" % (used, t["seats"]), "merge with another table or take it out")
if used == 0:
add("info", "SC06", t["name"], "empty table", "remove it from the room plan")
for p, mem in party_of.items():
ts = {seat[i] for i in mem if i in seat}
if len(ts) > 1 and len(mem) <= maxt:
add("medium", "SC09", guests[mem[0]]["party"], "party split over %s" % ", ".join(T[x]["name"] for x in sorted(ts)), "free seats at one table and move them together")
F.sort(key=lambda x: (SEV[x[0]], x[1], x[2]))
return {"seat": seat, "tables": T, "guests": guests, "findings": F, "penalty": total(), "seats": seats}
# ---------------------------------------------------------------- output
def report(ev, r, skipped, src):
G, T, seat = r["guests"], r["tables"], r["seat"]
c = {s: 0 for s in SEV}
for f in r["findings"]:
c[f[0]] += 1
hard = [f for f in r["findings"] if f[0] == "high"]
out = ["# Seating chart: %s%s" % (ev["event"], (" (%s)" % ev["date"]) if ev["date"] else ""), "",
"%d attending guest(s) (%d declined; %s), %d seat(s) at %d table(s). Source: %s." % (
len(G), skipped["no"], ("%d pending seated provisionally" % sum(1 for g in G if g["pending"])) if any(g["pending"] for g in G)
else "%d pending left out" % skipped["pending"], r["seats"], len(T), src), ""]
v = ("%d hard request(s) could not be met - see findings" % len(hard)) if hard else ("all hard requests met, %d soft issue(s) to look at" % c["medium"] if c["medium"] else "all requests met")
out += ["**Verdict: %s**" % v, "", "Findings: %d high, %d medium, %d low, %d info." % (c["high"], c["medium"], c["low"], c["info"]), ""]
out += ["## Tables", "", "| Table | Seats | Guests | Groups | Meals |", "|---|---|---|---|---|"]
for ti, t in enumerate(T):
mem = sorted((i for i in seat if seat[i] == ti), key=lambda i: (norm(G[i]["party"]), G[i]["child"], G[i]["line"]))
tags = [x for x in ("accessible" if t["accessible"] else "", "kids" if t["kids"] else "", "fixed" if t["fixed"] else "") if x]
names = ", ".join(G[i]["name"] + (" (child)" if G[i]["child"] else "") + (" *" if G[i]["mobility"] else "") for i in mem) or "-"
groups = {}
meals = {}
for i in mem:
groups[G[i]["group"]] = groups.get(G[i]["group"], 0) + 1
k = G[i]["diet"] + (" (child)" if G[i]["child"] else "")
meals[k] = meals.get(k, 0) + 1
out.append("| %s%s | %d/%d | %s | %s | %s |" % (t["name"], " [%s]" % ", ".join(tags) if tags else "", len(mem), t["seats"], names,
", ".join("%s %d" % kv for kv in sorted(groups.items())) or "-", ", ".join("%s %d" % kv for kv in sorted(meals.items())) or "-"))
out += ["", "`*` = mobility need (seat on the aisle side, nearest the door).", ""]
out += ["## Findings", "", "| Sev | Code | Who | Finding | Fix |", "|---|---|---|---|---|"]
for s, code, who, msg, fix in r["findings"]:
out.append("| %s | %s | %s | %s | %s |" % (s, code, who, msg.replace("|", "\\|"), fix.replace("|", "\\|")))
meals = {}
for i in seat:
k = G[i]["diet"] + (" (child)" if G[i]["child"] else "")
meals[k] = meals.get(k, 0) + 1
out += ["", "## Caterer summary", "", "| Meal | Count |", "|---|---|"]
for k, v_ in sorted(meals.items()):
out.append("| %s | %d |" % (k, v_))
notes = [(G[i]["name"], T[seat[i]]["name"], ", ".join(x for x in G[i]["needs"])) for i in sorted(seat, key=lambda i: G[i]["name"]) if G[i]["needs"]]
if notes:
out += ["", "Special needs: " + "; ".join("%s (%s) - %s" % n for n in notes) + "."]
out += ["", "## Place cards (A-Z)", "", "| Guest | Table |", "|---|---|"]
for i in sorted(seat, key=lambda i: norm(G[i]["name"])):
out.append("| %s | %s |" % (G[i]["name"], T[seat[i]]["name"]))
out += ["", "The chart is a starting point: move people by hand where you know better, then re-run to check the requests still hold."]
return "\n".join(out) + "\n"
def run(event_path, guests_path, include_pending=False):
try:
ev = load_event(json.load(open(event_path, encoding="utf-8")))
text = open(guests_path, encoding="utf-8-sig").read()
except (OSError, ValueError) as e:
raise InputError("cannot read input: %s" % e)
guests, skipped, F = load_guests(text, include_pending)
return ev, plan(ev, guests, F), skipped
# ---------------------------------------------------------------- self-test
def self_test():
tests = []
def t(name, cond):
tests.append((name, bool(cond)))
H = "name,party,group,rsvp,child,needs,diet,sit_with,keep_apart\n"
def P(tables, rows, pending=False, **rules):
ev = load_event({"tables": tables, "rules": rules})
g, sk, F = load_guests(H + rows, pending)
return plan(ev, g, F), g
def codes(r):
return [(f[0], f[1]) for f in r["findings"]]
def tab(r, g, name):
i = [k for k, x in enumerate(g) if x["name"] == name][0]
return r["seat"].get(i)
T2 = [{"name": "A", "seats": 4}, {"name": "B", "seats": 4}]
rows = "Ann,P1,work,yes\nBob,P1,work,yes\nCid,P2,family,yes\nDee,P2,family,yes\nEve,P3,work,yes\nFay,P4,family,yes\n"
r, g = P(T2, rows)
t("parties stay together", tab(r, g, "Ann") == tab(r, g, "Bob") and tab(r, g, "Cid") == tab(r, g, "Dee"))
t("groups fill tables", tab(r, g, "Eve") == tab(r, g, "Ann") and tab(r, g, "Fay") == tab(r, g, "Cid"))
t("clean plan has no high/medium", not [f for f in r["findings"] if f[0] in ("high", "medium")])
r, g = P(T2, "Ann,P1,work,yes,,,,,Bob\nBob,P2,work,yes\nCid,P3,work,yes\nDee,P4,work,yes\n")
t("keep_apart respected", tab(r, g, "Ann") != tab(r, g, "Bob") and ("high", "SC02") not in codes(r))
r, g = P(T2, "Ann,P1,work,yes,,,,Dee\nBob,P2,family,yes\nCid,P3,family,yes\nDee,P4,friends,yes\n")
t("sit_with respected", tab(r, g, "Ann") == tab(r, g, "Dee"))
r, g = P(T2, "Ann,P1,work,yes,,,,Bob,Bob\nBob,P2,work,yes\n")
t("sit_with vs keep_apart conflict -> SC02 high", ("high", "SC02") in codes(r))
r, g = P(T2, "Ann,P1,work,yes,,,,,Bob\nBob,P1,work,yes\n")
t("keep apart inside one party -> SC02", ("high", "SC02") in codes(r))
r, g = P(T2, "Ann,P1,work,yes,,,,Bobb\nBob,P2,work,yes\n")
t("misspelled name -> SC03 with suggestion", any(f[1] == "SC03" and "did you mean Bob" in f[3] for f in r["findings"]))
r, g = P([{"name": "A", "seats": 2}], "Ann,P1,w,yes\nBob,P2,w,yes\nCid,P3,w,yes\n")
t("not enough seats -> SC01 high", ("high", "SC01") in codes(r))
r, g = P(T2, "Ann,P1,w,yes\nAnn,P1,w,yes\nBob,P1,w,yes\n")
t("duplicate -> SC08 and seated once", ("medium", "SC08") in codes(r) and len(g) == 2)
r, g = P(T2, "Ann,P1,w,no\nBob,P2,w,pending\nCid,P3,w,yes\nDee,P3,w,yes\n")
t("declined and pending excluded", len(g) == 2)
r, g = P(T2, "Bob,P2,w,pending\nCid,P3,w,yes\n", pending=True)
t("--include-pending seats pending -> SC07", len(g) == 2 and ("info", "SC07") in codes(r))
r, g = P([{"name": "A", "seats": 4}, {"name": "B", "seats": 4, "accessible": True}], "Ann,P1,w,yes\nBob,P2,x,yes,,wheelchair\n")
t("wheelchair -> accessible table", tab(r, g, "Bob") == 1)
r, g = P([{"name": "A", "seats": 4}, {"name": "B", "seats": 4}], "Ann,P1,w,yes\nBob,P2,x,yes,,wheelchair\n")
t("no accessible table -> SC05", ("medium", "SC05") in codes(r))
r, g = P(T2, "Ann,P1,work,yes\nBob,P1,work,yes\nZed,P9,gym,yes\n")
t("lonely guest -> SC04", ("medium", "SC04") in codes(r))
r, g = P([{"name": "Head", "seats": 4, "fixed": ["Bride", "Groom"]}, {"name": "B", "seats": 4}], "Bride,C,couple,yes\nGroom,C,couple,yes\nBest,Best,groom family,yes,,,,Groom\n")
t("sit_with partner counts as someone they know", ("medium", "SC04") not in codes(r) and tab(r, g, "Best") == 0)
r, g = P([{"name": "A", "seats": 4}, {"name": "B", "seats": 4}, {"name": "C", "seats": 4}],
"A1,a1,fam,yes\nA2,a1,fam,yes\nA3,a1,fam,yes\nW1,w1,work,yes\nB1,b1,fam,yes\nB2,b1,fam,yes\nB3,b1,fam,yes\nW2,w2,work,yes\n")
t("group split by greedy is pulled together", tab(r, g, "W1") == tab(r, g, "W2"))
r, g = P([{"name": "A", "seats": 3}, {"name": "B", "seats": 3}], "A1,Big,w,yes\nA2,Big,w,yes\nA3,Big,w,yes\nA4,Big,w,yes\n")
t("party bigger than a table is split -> SC09", ("medium", "SC09") in codes(r) and len(r["seat"]) == 4)
r, g = P([{"name": "Head", "seats": 2, "fixed": ["Cid"]}, {"name": "B", "seats": 4}], "Ann,P1,w,yes\nBob,P1,w,yes\nCid,P3,w,yes\n")
t("fixed seat honoured", tab(r, g, "Cid") == 0)
r, g = P([{"name": "Head", "seats": 2, "fixed": ["Cyd"]}, {"name": "B", "seats": 4}], "Cid,P3,w,yes\n")
t("fixed seat typo -> SC03", ("high", "SC03") in codes(r))
r, g = P([{"name": "A", "seats": 10}, {"name": "B", "seats": 10}], "Ann,P1,w,yes\nBob,P1,w,yes\n")
t("half-empty and empty tables -> SC06", ("low", "SC06") in codes(r) and ("info", "SC06") in codes(r))
r, g = P([{"name": "A", "seats": 4}, {"name": "Kids", "seats": 4, "kids": True}], "Mum,F,fam,yes\nTim,F,fam,yes,yes\nLia,G,fam,yes,yes\nDad,G,fam,yes\n")
t("children stay with their party by default", tab(r, g, "Tim") == tab(r, g, "Mum"))
r, g = P(T2, "Ann,P1,w,yes,,,vegetarian\nBob,P1,w,yes,,,\n")
t("diet counted", "vegetarian 1" in report({"event": "x", "date": ""}, r, {"no": 0, "pending": 0}, "x"))
r, g = P([{"name": "A", "seats": 2}, {"name": "B", "seats": 2}], "Ann,P1,w,yes,,,,Bob;Cid\nBob,P2,w,yes\nCid,P3,w,yes\n")
t("sit_with group larger than any table -> SC09", ("medium", "SC09") in codes(r))
for bad, name in (({"tables": []}, "no tables"), ({"tables": [{"name": "A", "seats": 0}]}, "zero seats"),
({"tables": [{"name": "A", "seats": 4}, {"name": "A", "seats": 4}]}, "duplicate table"),
({"tables": [{"name": "A", "seats": 4, "colour": "red"}]}, "unknown table key")):
try:
load_event(bad); t("rejected: " + name, False)
except InputError:
t("rejected: " + name, True)
try:
load_guests("first,last\nA,B\n"); t("rejected: no name column", False)
except InputError:
t("rejected: no name column", True)
r, g = P(T2, rows)
rep = report({"event": "x", "date": ""}, r, {"no": 0, "pending": 0}, "x")
t("report has verdict, tables and place cards", "**Verdict:" in rep and "## Tables" in rep and "## Place cards" in rep)
for n, ok in tests:
print("%s %s" % ("PASS" if ok else "FAIL", n))
p = sum(ok for _, ok in tests)
print("%d/%d passed" % (p, len(tests)))
return 0 if p == len(tests) else 1
def main(argv=None):
ap = argparse.ArgumentParser(description="Build a seating chart from tables and a guest list.")
ap.add_argument("event", nargs="?")
ap.add_argument("guests", nargs="?")
ap.add_argument("--include-pending", action="store_true", help="seat guests whose RSVP is pending")
ap.add_argument("--csv", action="store_true", help="print name,table CSV (place cards)")
ap.add_argument("--json", action="store_true")
ap.add_argument("--self-test", action="store_true")
a = ap.parse_args(argv)
if a.self_test:
return self_test()
if not a.event or not a.guests:
ap.error("give EVENT.json and GUESTS.csv")
try:
ev, r, skipped = run(a.event, a.guests, a.include_pending)
except InputError as e:
print("error: %s" % e, file=sys.stderr)
return 2
G, T = r["guests"], r["tables"]
if a.json:
print(json.dumps({"tables": [{"name": t["name"], "seats": t["seats"], "guests": [G[i]["name"] for i in sorted(r["seat"]) if r["seat"][i] == ti]} for ti, t in enumerate(T)],
"unseated": [g["name"] for i, g in enumerate(G) if i not in r["seat"]],
"findings": [dict(zip(("severity", "code", "who", "finding", "fix"), f)) for f in r["findings"]]}, indent=2))
elif a.csv:
w = csv.writer(sys.stdout, lineterminator="\n")
w.writerow(["name", "table", "diet"])
for i in sorted(r["seat"], key=lambda i: norm(G[i]["name"])):
w.writerow([G[i]["name"], T[r["seat"][i]]["name"], G[i]["diet"]])
else:
sys.stdout.write(report(ev, r, skipped, a.guests))
return 1 if any(f[0] == "high" for f in r["findings"]) else 0
if __name__ == "__main__":
sys.exit(main())0
Audits feature flags against your codebase and plans their cleanup - finds release flags 100% on or off for weeks, rollouts stuck at a partial percentage, experiments that never ended, expired, archived and unreferenced flags, keys used in code but missing from the flag service (or misspelled), staging-production drift and flags without an owner. Lists every file:line to change with effort. Includes an offline stdlib Python scanner.
---
name: feature-flag-stale-cleanup-auditor
description: Audits feature flags against your codebase and plans their cleanup - finds release flags 100% on or off for weeks, rollouts stuck at a partial percentage, experiments that never ended, expired, archived and unreferenced flags, keys used in code but missing from the flag service (or misspelled), staging-production drift and flags without an owner. Lists every file:line to change with effort. Includes an offline stdlib Python scanner.
---
# Feature Flag Stale Cleanup Auditor
You help engineering teams pay down feature flag debt. Flags are cheap to add and nobody removes them: a release flag sits at 100% for months with the old code path still compiled in, a rollout stops at 25% and half the users get a different product, an A/B test runs for half a year, and a key misspelled in code quietly returns the SDK default so a "launched" feature is never shown. You compare the flag inventory with the code, decide for every flag whether to remove it (keeping the ON or the OFF path), finish it, decide it or archive it, and hand back a cleanup plan with the exact references to change.
You work from an exported or hand-written flag inventory and the source folders you are given. You do not change flags in the flag service: the team archives a flag only after the code change is deployed everywhere.
## Files in this skill
- `scripts/flag_audit.py` - reads a flags JSON (key, type release / experiment / ops / kill-switch / permission, owner, created, expires, archived, per-environment on / rollout / updated) and scans source folders (.ts .tsx .js .jsx .py .go .rb .java .kt .cs .php .swift .vue .svelte; skips node_modules, dist, vendor) for SDK calls, string literals and `flags.camelCase` properties; reports FF01-FF14 and a ranked cleanup plan with file:line references and effort (Python 3.8+ standard library only)
- `references/flag-lifecycle-and-removal.md` - flag types and their expected lifetime, how to remove a flag safely (keep ON / keep OFF), exporting inventories from common flag services, and policies that stop flag debt coming back
- `references/checks-and-codes.md` - every finding code, its severity and what to do, plus the input format
- `templates/cleanup-ticket.md` - the cleanup ticket / PR description for each flag
- `examples/flags.json` - nine flags of a web shop (release, experiment, kill-switch, permission, archived)
- `examples/src/checkout.ts`, `examples/src/Header.tsx`, `examples/src/search.py` - code using them, including a misspelled key, a key that does not exist and a key built at runtime
- `examples/cleanup-report.md` - the real scanner output on the example
## Workflow
### 1. Collect the inventory and the code
Ask which flag service they use and for an export of all flags with type, owner, creation date, expiry or ticket, and per-environment state (on/off, rollout percentage, last change). Map it into a JSON like `examples/flags.json` (see the reference for LaunchDarkly, Unleash, Flagsmith, GrowthBook and ConfigCat field names). Ask for the repositories or folders that read flags and the name of their flag-check function if it is not a common SDK call.
### 2. Run the scanner
```
python3 scripts/flag_audit.py examples/flags.json examples/src
python3 scripts/flag_audit.py flags.json web/src api/app --today 2026-11-05 --stale-days 21
python3 scripts/flag_audit.py flags.json src --call featureOn --call can
python3 scripts/flag_audit.py flags.json src --json
python3 scripts/flag_audit.py --self-test
```
Exit 0 = no high findings, 1 = high findings, 2 = bad input. Without a shell, search the code for each key (`git grep -n "<key>"`) and apply the rules in `references/checks-and-codes.md` by hand.
### 3. Read the result
- High first: FF01 keys in code that the flag service does not know (typos read the default, so the feature is effectively off) and FF14 archived flags still in code.
- Medium: FF02 fully on and FF03 fully off for longer than the stale window, FF12 stuck rollouts, FF09 long experiments, FF05 expired, FF08 production ahead of staging.
- Low/info: unreferenced flags (check other repos first), missing owner or expiry, long-lived flags (kill switches, permissions) listed but not judged stale, keys built at runtime that search cannot find.
### 4. Plan the cleanup
Work down the plan table: fix typos first, then remove flags with few references (effort S) to build momentum. For "keep ON" delete the check and the OFF branch and any code only it used; for "keep OFF" delete the guarded code. Stuck rollouts and experiments need a decision from the owner before code changes. Fill `templates/cleanup-ticket.md` per flag.
### 5. Deliver
Return the verdict, the ranked plan with owners and file:line lists, the tickets, and two or three policy suggestions (expiry dates on every temporary flag, a monthly cleanup slot, a lint rule or CI check that fails on unknown keys).
## Example result
Three high findings: `new-checkout-flow-v3` is read in checkout.ts but does not exist, `recs_carousel` in search.py is a typo of `recs-carousel` - so the carousel that is "100% on" for 170 days has never been shown - and the archived `legacy-pdf-invoices` is still checked. `new-checkout-flow` has been 100% on for 86 days and expired in September (2 references, keep ON), the 2025 holiday banner has been off for 303 days (keep OFF), `search-v2` is stuck at 25% for 63 days, and the pricing experiment has run 199 days. `dark-mode` is on in production but off in staging. Kill switch and permission flags are kept.
## Rules
- Never recommend removing a kill switch, ops or permission flag because it is old; they are long-lived by design.
- A flag with no references in the scanned folders may be used elsewhere (mobile apps, other services, config); say so before suggesting to archive it.
- Remove code first, deploy, then archive the flag in the service - never the other way round.
- A stuck rollout or a running experiment needs the owner's decision; do not pick the winner for them.
- Treat `today` and the stale window as inputs; say which values you used.
FILE:references/flag-lifecycle-and-removal.md
# Flag lifecycle and safe removal
## Flag types and expected lifetime
| Type | Purpose | Expected life | Done when |
|---|---|---|---|
| release | hide unfinished work, roll out gradually | days to a few weeks after 100% | 100% everywhere and stable for the stale window |
| experiment | A/B or multivariate test | the test duration (2-6 weeks typical) | a decision is made |
| ops | operational switch (cache on/off, batch size) | long | rarely; review yearly |
| kill-switch | turn off a risky dependency fast | permanent | never by age |
| permission | entitlement, beta access, plan feature | permanent (or move to the billing/entitlement system) | product decision |
## Removing a flag safely
1. Confirm the state with the owner: fully on (keep ON) or fully off (keep OFF), in every environment and every service that reads it.
2. Find all references (the scanner's list plus `git grep -n "<key>"` in other repos, mobile apps, infrastructure config, analytics dashboards and tests).
3. Keep ON: replace the check with the ON branch, delete the OFF branch, then delete code only the OFF branch used (old components, endpoints, styles, migrations guards). Keep OFF: delete the guarded code and anything only it used.
4. Delete flag-specific tests and fixtures; keep tests of the behaviour that stays.
5. Deploy to every environment. Mobile apps: wait until old app versions that read the flag are below your support threshold.
6. Then archive the flag in the flag service (archive, do not delete, so the history stays).
7. Close the ticket with the PR links.
## Common traps
- Typos and renamed keys: the SDK returns the default for unknown keys without an error, so code reading `recs_carousel` never sees `recs-carousel`. A CI check that compares literal keys with the inventory catches this.
- Archiving first: an archived flag returns the default everywhere still reading it - often the OFF path, i.e. an instant rollback of a launched feature.
- Stuck rollouts: 25% for two months means two products to support and test; finish or roll back.
- Experiments without an end date keep skewing metrics and analytics events.
- Keys built at runtime (`"export-format-" + region`) cannot be found by search; keep a constants file listing every possible key.
## Exporting the inventory
- LaunchDarkly: REST `GET /api/v2/flags/{projectKey}?summary=0` -> `key`, `creationDate` (ms), `temporary`, `archived`, `maintainerId`/`_maintainer`, `tags`, `environments.<env>.on`, `.lastModified`, rollout weights in `fallthrough.rollout.variations` (weight/1000 = percent). Map `temporary: false` to `permanent: true`.
- Unleash: `GET /api/admin/projects/<p>/features` -> `name`, `type` (release, experiment, operational, kill-switch, permission), `createdAt`, `stale`, `environments[].enabled`, gradual rollout strategy `parameters.rollout`.
- Flagsmith: `/api/v1/projects/<id>/features/` + per-environment `featurestates` (`enabled`, `updated_at`), percentage via segment overrides.
- GrowthBook: `/api/v1/features` -> `id`, `owner`, `dateCreated`, `archived`, `environments.<env>.enabled`, rollout rule `coverage` (0-1 -> percent).
- ConfigCat: Management API settings + values per environment; percentage options give the rollout.
- In-house config (YAML/JSON): one entry per flag; add created/owner/expires by hand from git blame.
## Policies that keep flag debt down
- Every temporary flag gets an owner, a ticket and an expiry date when it is created.
- Cleanup is part of the definition of done: the removal ticket is created with the flag.
- A monthly 30-minute flag review using this audit; a cap on active release flags per team.
- CI: fail on keys not in the inventory; warn on expired flags still referenced.
FILE:references/checks-and-codes.md
# Checks and finding codes
| Code | Severity | Check | What to do |
|---|---|---|---|
| FF01 | high | a flag-check call (isEnabled, variation, useFlag, is_enabled ...) uses a key that is not in the inventory; a close match is suggested (typo, `_` vs `-`) | fix the key or create the flag; until then the SDK returns the default value |
| FF02 | medium | release flag at 100% in the primary environment for `stale_days` or more | remove the flag, keep the ON path |
| FF03 | medium | release or experiment flag off / 0% in the primary environment for `stale_days` or more | remove the flag and the guarded code, or decide to launch |
| FF04 | low | no reference in the scanned files | check other repos and services; archive if unused |
| FF05 | medium | `expires` date passed (temporary flags) | remove or agree a new date |
| FF06 | info | ops, kill-switch, permission (or `permanent: true`) flag - not judged stale | review yearly |
| FF07 | low | no owner | assign one |
| FF08 | medium | primary environment ahead of staging/qa/test/dev, or no state for the primary environment | align environments |
| FF09 | medium | experiment older than `experiment_max_days` | decide, ship the winner, remove |
| FF10 | info | flag key built at runtime (variable, concatenation, template string) | use literal keys or a constants file |
| FF11 | low | temporary flag without `expires` | set an expiry |
| FF12 | medium | release rollout between 1 and 99% unchanged for `stale_days` | finish (100%) or roll back, then remove |
| FF13 | medium | key defined twice in the inventory | merge |
| FF14 | high | flag archived in the service but still referenced in code | remove the references |
## Verdict
- **N high finding(s)** when FF01/FF14 exist; else **N flag(s) ready to remove**; else **no stale flags**.
## Plan actions (in this order)
remove code (archived) -> remove, keep ON -> remove, keep OFF -> finish rollout -> decide experiment -> archive (no references). Within an action, flags with more references first. Effort: S 1-2 references, M 3-6, L 7+.
## How references are found
1. Calls: `<name>(` with a literal first argument (or a literal after one leading argument such as a client or user), for the built-in names plus `call_names` / `--call`.
2. Any string literal equal to a known key (constants files, config maps).
3. `flags.`, `features.`, `featureFlags.`, `toggles.` followed by the key or its camelCase form (`new-search` -> `flags.newSearch`).
Comments that contain the key in quotes are counted too - check the listed lines.
## Flags JSON
Top level: `today, primary_env (production), environments, stale_days (30), experiment_max_days (90), call_names[], flags[]`.
Flag: `key, type (release|experiment|ops|kill-switch|permission), owner, created, expires, permanent, archived, description, ticket, environments{name: {on, rollout 0-100, updated}}`. `rollout` defaults to 100 when on and 0 when off; `updated` is the last change of that environment (falls back to `created`).
FILE:templates/cleanup-ticket.md
# Remove feature flag `<key>`
**Owner:** <team-payments> **Type:** <release> **Ticket:** <PAY-412> **Action:** <remove, keep ON>
**State:** <100% on in production since 2026-08-11 (86 days), 100% in staging> **Expired:** <2026-09-30>
## Why
<Fully rolled out and stable for 86 days; the OFF path (legacy checkout) is dead code.>
## Change
- [ ] `<examples/src/checkout.ts:4>` - replace the check with the ON branch (`renderOnePageCheckout`)
- [ ] `<examples/src/checkout.ts:14>` - always use `oneClickButton()`
- [ ] delete code only the OFF path used: <renderLegacyCheckout, classicButton, legacy checkout styles>
- [ ] delete flag-specific tests and fixtures
- [ ] search other repos / mobile apps: `git grep -n "<key>"`
## Rollout
1. Merge and deploy to staging, then production.
2. Watch <checkout conversion, error rate> for <2 days>.
3. Archive `<key>` in <flag service> (archive, not delete).
## Risks / questions
- <Does the mobile app read this flag? Minimum supported version?>
- <Any dashboards or alerts keyed on the flag?>
FILE:examples/flags.json
{
"today": "2026-11-05",
"primary_env": "production",
"stale_days": 30,
"experiment_max_days": 90,
"flags": [
{"key": "new-checkout-flow", "type": "release", "owner": "team-payments", "created": "2026-06-02", "expires": "2026-09-30", "ticket": "PAY-412",
"description": "New one-page checkout",
"environments": {"production": {"on": true, "rollout": 100, "updated": "2026-08-11"}, "staging": {"on": true, "rollout": 100, "updated": "2026-07-20"}}},
{"key": "search-v2", "type": "release", "owner": "team-search", "created": "2026-07-15", "expires": "2026-12-31",
"description": "Typesense-backed search",
"environments": {"production": {"on": true, "rollout": 25, "updated": "2026-09-03"}, "staging": {"on": true, "rollout": 100, "updated": "2026-08-01"}}},
{"key": "holiday-banner-2025", "type": "release", "owner": "team-growth", "created": "2025-11-10", "expires": "2026-01-10",
"description": "Christmas 2025 promo banner",
"environments": {"production": {"on": false, "rollout": 0, "updated": "2026-01-06"}, "staging": {"on": false, "rollout": 0, "updated": "2026-01-06"}}},
{"key": "pricing-page-test", "type": "experiment", "owner": "team-growth", "created": "2026-04-20", "expires": "2026-07-01",
"description": "A/B test: annual plan first",
"environments": {"production": {"on": true, "rollout": 50, "updated": "2026-04-22"}, "staging": {"on": true, "rollout": 50, "updated": "2026-04-22"}}},
{"key": "dark-mode", "type": "release", "owner": "team-web", "created": "2026-10-01", "expires": "2026-12-15",
"description": "Dark theme",
"environments": {"production": {"on": true, "rollout": 100, "updated": "2026-10-28"}, "staging": {"on": false, "rollout": 0, "updated": "2026-10-02"}}},
{"key": "payments-kill-switch", "type": "kill-switch", "owner": "team-payments", "created": "2025-03-01",
"description": "Turn off card payments during a PSP outage",
"environments": {"production": {"on": true, "rollout": 100, "updated": "2025-03-01"}, "staging": {"on": true, "rollout": 100, "updated": "2025-03-01"}}},
{"key": "beta-reports-export", "type": "permission", "owner": "", "created": "2025-09-12",
"description": "CSV export for beta customers",
"environments": {"production": {"on": true, "rollout": 100, "updated": "2025-09-12"}}},
{"key": "legacy-pdf-invoices", "type": "release", "owner": "team-billing", "created": "2025-05-01", "archived": true,
"description": "Old PDF renderer",
"environments": {"production": {"on": false, "rollout": 0, "updated": "2026-02-01"}}},
{"key": "recs-carousel", "type": "release", "owner": "team-growth", "created": "2026-03-03",
"description": "Recommendations carousel on product pages",
"environments": {"production": {"on": true, "rollout": 100, "updated": "2026-05-19"}, "staging": {"on": true, "rollout": 100, "updated": "2026-05-01"}}}
]
}
FILE:examples/src/checkout.ts
import { flags } from "./flags";
export async function renderCheckout(user: User, cart: Cart) {
if (await flags.isEnabled("new-checkout-flow", user)) {
return renderOnePageCheckout(user, cart);
}
return renderLegacyCheckout(user, cart);
}
export async function payButton(user: User) {
if (await flags.isEnabled("payments-kill-switch", user)) {
return disabledButton("Card payments are paused. Please try again shortly.");
}
const oneClick = await flags.isEnabled("new-checkout-flow", user);
return oneClick ? oneClickButton() : classicButton();
}
export async function invoiceLink(order: Order) {
// TODO remove after PDF migration
if (await flags.isEnabled("legacy-pdf-invoices")) {
return legacyPdfUrl(order.id);
}
return invoiceServiceUrl(order.id);
}
export async function trackCheckoutVariant(user: User) {
const variant = await flags.variation("new-checkout-flow-v3", user, "control");
analytics.track("checkout_variant", { variant });
}
FILE:examples/src/Header.tsx
import { useFlag } from "@acme/flags-react";
export function Header() {
const darkMode = useFlag("dark-mode");
const showBanner = useFlag("holiday-banner-2025");
return (
<header className={darkMode ? "header header--dark" : "header"}>
{showBanner && <PromoBanner text="Holiday sale: 20% off everything" />}
<SearchBox />
</header>
);
}
export function PricingPage({ user }: { user: User }) {
const annualFirst = useFlag("pricing-page-test");
return annualFirst ? <PlansAnnualFirst /> : <PlansMonthlyFirst />;
}
FILE:examples/src/search.py
from app.flags import flags
def search(query, user):
if flags.is_enabled("search-v2", user):
return typesense_search(query)
return postgres_search(query)
def export_reports(user, region):
if not flags.is_enabled("beta-reports-export", user):
raise PermissionError("export is in beta")
# per-region experiment keys, e.g. "export-format-eu"
if flags.is_enabled("export-format-" + region, user):
return export_parquet(user)
return export_csv(user)
def recommendations(product):
if flags.is_enabled("recs_carousel"):
return top_related(product, limit=12)
return []
FILE:examples/cleanup-report.md
# Feature flag cleanup audit
Today 2026-11-05, primary environment `production`, stale after 30 days. 9 flag(s) in the inventory, 3 source file(s) scanned in examples/src.
**Verdict: 3 high finding(s) - flags used in code that the flag service does not know**
Cleanup candidates: 6 (4 removable now, 4 reference(s) to change). Findings: 3 high, 9 medium, 2 low, 3 info.
## Cleanup plan
| # | Flag | Type | Owner | Primary | Action | Why | Refs (files) | Effort | Where |
|---|---|---|---|---|---|---|---|---|---|
| 1 | `legacy-pdf-invoices` | release | team-billing | archived | **remove code** | archived but still in code | 1 (1) | S | `examples/src/checkout.ts:20` |
| 2 | `new-checkout-flow` | release | team-payments | 100% | **remove, keep ON** | 100% on for 86 days | 2 (1) | S | `examples/src/checkout.ts:4`, `examples/src/checkout.ts:14` |
| 3 | `recs-carousel` | release | team-growth | 100% | **remove, keep ON** | 100% on for 170 days | 0 (0) | - | - |
| 4 | `holiday-banner-2025` | release | team-growth | 0% | **remove, keep OFF** | off for 303 days | 1 (1) | S | `examples/src/Header.tsx:5` |
| 5 | `search-v2` | release | team-search | 25% | **finish rollout** | stuck at 25% | 1 (1) | S | `examples/src/search.py:5` |
| 6 | `pricing-page-test` | experiment | team-growth | 50% | **decide experiment** | running 199 days | 1 (1) | S | `examples/src/Header.tsx:15` |
Effort: S = 1-2 references, M = 3-6, L = 7 or more. "keep ON" = delete the flag check and the OFF branch; "keep OFF" = delete the guarded code. Archive the flag in the flag service only after the code change is deployed everywhere.
## Findings
| Sev | Code | Flag | Finding | Fix |
|---|---|---|---|---|
| high | FF01 | `new-checkout-flow-v3` | used in code (examples/src/checkout.ts:27) but not defined in the flag inventory - the SDK returns the default, so this code path is reading the wrong key | typo of new-checkout-flow? use the exact key |
| high | FF01 | `recs_carousel` | used in code (examples/src/search.py:20) but not defined in the flag inventory - the SDK returns the default, so this code path is reading the wrong key | typo of recs-carousel? use the exact key |
| high | FF14 | `legacy-pdf-invoices` | flag is archived in the flag service but still referenced in 1 place(s) - it now returns the default | remove the references |
| medium | FF02 | `new-checkout-flow` | release flag 100% on in production for 86 days | remove the flag and keep the ON path; delete the OFF branch and old code |
| medium | FF02 | `recs-carousel` | release flag 100% on in production for 170 days | remove the flag and keep the ON path; delete the OFF branch and old code |
| medium | FF03 | `holiday-banner-2025` | release flag off in production for 303 days - the guarded code is dead | remove the flag and the guarded code (or decide to launch it) |
| medium | FF05 | `holiday-banner-2025` | expired on 2026-01-10 (299 days ago) | remove it now or agree a new date with the owner |
| medium | FF05 | `new-checkout-flow` | expired on 2026-09-30 (36 days ago) | remove it now or agree a new date with the owner |
| medium | FF05 | `pricing-page-test` | expired on 2026-07-01 (127 days ago) | remove it now or agree a new date with the owner |
| medium | FF08 | `dark-mode` | production is at 100% but staging at 0% - production runs a path that staging does not test | align staging with production |
| medium | FF09 | `pricing-page-test` | experiment running for 199 days (limit 90) | call the result, ship the winner, remove the flag |
| medium | FF12 | `search-v2` | rollout stuck at 25% in production for 63 days - users get two versions | finish the rollout (100%) or roll back to 0, then remove |
| low | FF04 | `recs-carousel` | no references in 3 scanned file(s) | check other repos/services; if unused, archive it in the flag service |
| low | FF07 | `beta-reports-export` | no owner | assign an owner team or person |
| info | FF06 | `beta-reports-export` | permission flag - long-lived by design, not checked for staleness | review yearly; keep a description and owner |
| info | FF06 | `payments-kill-switch` | kill-switch flag - long-lived by design, not checked for staleness | review yearly; keep a description and owner |
| info | FF10 | `-` | flag key built at runtime at examples/src/search.py:14 - references to it cannot be found by search | prefer literal keys (or a constants file) so flags can be cleaned up |
## References per flag
| Flag | References |
|---|---|
| `beta-reports-export` | 1 |
| `dark-mode` | 1 |
| `holiday-banner-2025` | 1 |
| `legacy-pdf-invoices` | 1 |
| `new-checkout-flow` | 2 |
| `payments-kill-switch` | 1 |
| `pricing-page-test` | 1 |
| `recs-carousel` | 0 |
| `search-v2` | 1 |
Search covers string literals, common SDK calls and `flags.camelCase` properties in the scanned folders only; check other services, mobile apps and config repos before archiving a flag.
FILE:scripts/flag_audit.py
#!/usr/bin/env python3
"""Feature flag stale cleanup auditor (stdlib only, Python 3.8+).
Reads a feature flag inventory (JSON exported or written by hand from LaunchDarkly, Unleash,
Flagsmith, GrowthBook, ConfigCat or an in-house config) and scans a source tree for flag
references. Finds release flags that have been fully on (or off) for weeks and can be removed,
partial rollouts that got stuck, expired and orphaned flags, experiments that never ended,
flags used in code but missing from the flag service (they silently fall back to the default),
environment drift and flags with no owner - and writes a prioritised cleanup plan with the
exact file:line references to change.
Usage:
flag_audit.py FLAGS.json SRC_DIR [SRC_DIR ...] [--today YYYY-MM-DD] [--stale-days N]
[--call NAME ...] [--json]
flag_audit.py --self-test
Exit: 0 = no high findings, 1 = at least one high finding, 2 = bad input.
"""
import argparse, datetime, difflib, json, os, re, sys
SEV = {"high": 0, "medium": 1, "low": 2, "info": 3}
TYPES = {"release", "experiment", "ops", "kill-switch", "permission"}
LONG_LIVED = {"ops", "kill-switch", "permission"}
EXTS = {".ts", ".tsx", ".js", ".jsx", ".mjs", ".cjs", ".py", ".go", ".rb", ".java", ".kt", ".cs", ".php", ".swift", ".vue", ".svelte"}
SKIP_DIRS = {"node_modules", ".git", "dist", "build", "vendor", "__pycache__", ".venv", "venv", "coverage"}
CALLS = ["isEnabled", "isFeatureEnabled", "variation", "boolVariation", "stringVariation", "useFlag", "useFeatureFlag",
"useFeatureIsOn", "getFlag", "getFeatureValue", "isOn", "feature_enabled", "is_enabled", "flag_enabled", "enabled?",
"Enabled", "IsEnabled", "getBooleanValue", "hasFeature"]
TOP_KEYS = {"today", "stale_days", "experiment_max_days", "primary_env", "environments", "flags", "call_names", "source"}
FLAG_KEYS = {"key", "type", "owner", "created", "expires", "permanent", "description", "environments", "archived", "ticket"}
class InputError(Exception):
pass
def pdate(s, what):
try:
return datetime.date.fromisoformat(str(s).strip()[:10])
except ValueError:
raise InputError("%s must be YYYY-MM-DD, got %r" % (what, s))
def camel(k):
parts = re.split(r"[-_.]", k)
return parts[0] + "".join(p[:1].upper() + p[1:] for p in parts[1:])
# ---------------------------------------------------------------- load
def load_flags(cfg, today=None, stale_days=None):
if not isinstance(cfg, dict) or not isinstance(cfg.get("flags"), list):
raise InputError("flags file must be a JSON object with a \"flags\" list")
bad = set(cfg) - TOP_KEYS
if bad:
raise InputError("unknown top-level key(s): %s" % ", ".join(sorted(bad)))
c = {"today": pdate(today or cfg.get("today") or datetime.date.today().isoformat(), "today"),
"stale": int(stale_days if stale_days is not None else cfg.get("stale_days", 30)),
"exp_max": int(cfg.get("experiment_max_days", 90)),
"primary": cfg.get("primary_env", "production"),
"envs": cfg.get("environments") or [], "flags": {}, "dups": [], "calls": cfg.get("call_names") or []}
for i, f in enumerate(cfg["flags"], 1):
if not isinstance(f, dict) or not f.get("key"):
raise InputError("flag #%d has no key" % i)
badk = set(f) - FLAG_KEYS
if badk:
raise InputError("flag %s: unknown key(s) %s" % (f["key"], ", ".join(sorted(badk))))
t = (f.get("type") or "release").lower()
if t not in TYPES:
raise InputError("flag %s: type must be one of %s, got %r" % (f["key"], ", ".join(sorted(TYPES)), t))
envs = {}
for e, st in (f.get("environments") or {}).items():
if not isinstance(st, dict):
raise InputError("flag %s env %s must be an object {on, rollout, updated}" % (f["key"], e))
r = st.get("rollout", 100 if st.get("on") else 0)
if not isinstance(r, (int, float)) or not 0 <= r <= 100:
raise InputError("flag %s env %s: rollout must be 0-100, got %r" % (f["key"], e, r))
envs[e] = {"on": bool(st.get("on")), "rollout": float(r),
"updated": pdate(st["updated"], "flag %s env %s updated" % (f["key"], e)) if st.get("updated") else None}
fl = {"key": f["key"], "type": t, "owner": f.get("owner") or "", "ticket": f.get("ticket", ""),
"created": pdate(f["created"], "flag %s created" % f["key"]) if f.get("created") else None,
"expires": pdate(f["expires"], "flag %s expires" % f["key"]) if f.get("expires") else None,
"permanent": bool(f.get("permanent")) or t in LONG_LIVED, "archived": bool(f.get("archived")),
"description": f.get("description", ""), "envs": envs}
if fl["key"] in c["flags"]:
c["dups"].append(fl["key"])
c["flags"][fl["key"]] = fl
return c
def eff(st):
"""effective share of users getting the flag: 0-100"""
return st["rollout"] if st["on"] else 0.0
# ---------------------------------------------------------------- scan
def scan(dirs, keys, calls):
"""Return refs {key: [(path, line, text)]}, unknown {literal: [(path,line)]}, dynamic [(path,line,text)], files"""
calls = sorted(set(CALLS + list(calls)), key=len, reverse=True)
alt = "|".join(re.escape(c) for c in calls)
call_re = re.compile(r"(?:\b|\.)(%s)\s*\(\s*(?:\w+\s*,\s*)?([\"'`])([^\"'`$]+)\2\s*[,)]" % alt)
dyn_re = re.compile(r"(?:\b|\.)(%s)\s*\(\s*(?![\"'`][^\"'`$]*[\"'`]\s*[,)])([^,)]+)[,)]" % alt)
lit_re = re.compile(r"([\"'`])([A-Za-z0-9][A-Za-z0-9_.:-]{2,80})\1")
camels = {camel(k): k for k in keys if camel(k) != k}
prop_re = re.compile(r"\b(?:flags|features|featureFlags|toggles)\.([A-Za-z_]\w*)")
refs, unknown, dynamic, nfiles = {k: [] for k in keys}, {}, [], 0
for d in dirs:
if not os.path.isdir(d):
raise InputError("source directory not found: %s" % d)
for root, ds, fs in os.walk(d):
ds[:] = sorted(x for x in ds if x not in SKIP_DIRS)
for fn in sorted(fs):
if os.path.splitext(fn)[1] not in EXTS:
continue
p = os.path.join(root, fn)
nfiles += 1
try:
lines = open(p, encoding="utf-8", errors="replace").read().splitlines()
except OSError as e:
raise InputError("cannot read %s: %s" % (p, e))
for i, ln in enumerate(lines, 1):
seen = set()
for m in call_re.finditer(ln):
lit = m.group(3)
if lit in refs:
refs[lit].append((p, i, ln.strip())); seen.add(lit)
else:
unknown.setdefault(lit, []).append((p, i, ln.strip()))
seen.add(lit)
for m in dyn_re.finditer(ln):
if m.group(2).strip() not in ("true", "false", "None", "null", ""):
dynamic.append((p, i, ln.strip()))
for m in lit_re.finditer(ln):
lit = m.group(2)
if lit in refs and lit not in seen:
refs[lit].append((p, i, ln.strip())); seen.add(lit)
for m in prop_re.finditer(ln):
k = camels.get(m.group(1)) or (m.group(1) if m.group(1) in refs else None)
if k and k not in seen:
refs[k].append((p, i, ln.strip())); seen.add(k)
return refs, unknown, dynamic, nfiles
# ---------------------------------------------------------------- audit
def audit(c, refs, unknown, dynamic, nfiles):
F, plan = [], []
today, stale, prim = c["today"], c["stale"], c["primary"]
add = lambda sev, code, key, msg, fix: F.append((sev, code, key, msg, fix))
for k in c["dups"]:
add("medium", "FF13", k, "flag defined twice in the inventory (the last one is used)", "merge the two entries")
keys = list(c["flags"])
norm = {re.sub(r"[-_.]", "", k.lower()): k for k in keys}
for lit, where in sorted(unknown.items()):
close = norm.get(re.sub(r"[-_.]", "", lit.lower())) or (difflib.get_close_matches(lit, keys, 1, 0.8) or [None])[0]
locs = ", ".join("%s:%d" % (p, i) for p, i, _ in where[:3])
add("high", "FF01", lit, "used in code (%s) but not defined in the flag inventory - the SDK returns the default, so this code path is %s" %
(locs, "probably never on" if not close else "reading the wrong key"),
("typo of %s? use the exact key" % close) if close else "create the flag or remove the check")
for p, i, txt in dynamic[:20]:
add("info", "FF10", "-", "flag key built at runtime at %s:%d - references to it cannot be found by search" % (p, i), "prefer literal keys (or a constants file) so flags can be cleaned up")
for k, f in c["flags"].items():
r = refs.get(k, [])
files = sorted(set(p for p, _, _ in r))
st = f["envs"].get(prim)
age = (today - f["created"]).days if f["created"] else None
action, why = None, ""
if not f["owner"]:
add("low", "FF07", k, "no owner", "assign an owner team or person")
if f["archived"]:
if r:
add("high", "FF14", k, "flag is archived in the flag service but still referenced in %d place(s) - it now returns the default" % len(r), "remove the references")
plan.append({"key": k, "type": f["type"], "owner": f["owner"] or "?", "state": "archived", "action": "remove code",
"why": "archived but still in code", "refs": len(r), "files": len(files),
"locs": ["%s:%d" % (p, i) for p, i, _ in r], "ticket": f["ticket"]})
continue
if st is None and not f["archived"]:
add("medium", "FF08", k, "no state for the primary environment %r" % prim, "add the %s state or fix primary_env" % prim)
if f["permanent"]:
add("info", "FF06", k, "%s flag - long-lived by design, not checked for staleness" % f["type"], "review yearly; keep a description and owner")
if not r:
add("low", "FF04", k, "no references in %d scanned file(s)" % nfiles, "check other repos/services; if unused, archive it in the flag service")
action, why = action or "archive", "no references"
elif st is not None:
since = st["updated"] or f["created"]
days = (today - since).days if since else None
e = eff(st)
all_on = all(eff(s) == 100 for s in f["envs"].values())
if f["expires"] and f["expires"] < today:
add("medium", "FF05", k, "expired on %s (%d days ago)" % (f["expires"], (today - f["expires"]).days), "remove it now or agree a new date with the owner")
if f["type"] == "release" and e == 100 and days is not None and days >= stale:
add("medium", "FF02", k, "release flag 100%% on in %s for %d days%s" % (prim, days, "" if all_on else " (not 100% in every environment)"),
"remove the flag and keep the ON path; delete the OFF branch and old code")
action, why = "remove, keep ON", "100%% on for %d days" % days
elif e == 0 and days is not None and days >= stale and f["type"] in ("release", "experiment"):
add("medium", "FF03", k, "%s flag off in %s for %d days - the guarded code is dead" % (f["type"], prim, days),
"remove the flag and the guarded code (or decide to launch it)")
action, why = "remove, keep OFF", "off for %d days" % days
elif 0 < e < 100 and days is not None and days >= stale and f["type"] == "release":
add("medium", "FF12", k, "rollout stuck at %g%% in %s for %d days - users get two versions" % (e, prim, days), "finish the rollout (100%) or roll back to 0, then remove")
action, why = "finish rollout", "stuck at %g%%" % e
if f["type"] == "experiment" and age is not None and age > c["exp_max"]:
add("medium", "FF09", k, "experiment running for %d days (limit %d)" % (age, c["exp_max"]), "call the result, ship the winner, remove the flag")
action, why = action or "decide experiment", "running %d days" % age
if not r:
add("low", "FF04", k, "no references in %d scanned file(s)" % nfiles, "check other repos/services; if unused, archive it in the flag service")
action, why = action or "archive", why or "no references"
for en, s2 in f["envs"].items():
if en != prim and eff(s2) < e and (en in ("staging", "qa", "test", "dev", "development")):
add("medium", "FF08", k, "%s is at %g%% but %s at %g%% - production runs a path that staging does not test" % (prim, e, en, eff(s2)), "align %s with %s" % (en, prim))
if f["expires"] is None and f["type"] in ("release", "experiment") and action is None:
add("low", "FF11", k, "temporary %s flag without an expiry date" % f["type"], "set expires (e.g. 30-60 days after full rollout)")
if action:
plan.append({"key": k, "type": f["type"], "owner": f["owner"] or "?", "state": ("%g%%" % eff(st)) if st else "-", "action": action, "why": why,
"refs": len(r), "files": len(files), "locs": ["%s:%d" % (p, i) for p, i, _ in r], "ticket": f["ticket"]})
rank = {"remove code": 0, "remove, keep ON": 1, "remove, keep OFF": 2, "finish rollout": 3, "decide experiment": 4, "archive": 5}
plan.sort(key=lambda x: (rank[x["action"]], -x["refs"], x["key"]))
F.sort(key=lambda x: (SEV[x[0]], x[1], x[2]))
return {"today": today.isoformat(), "primary": prim, "stale_days": stale, "flags": len(c["flags"]), "files": nfiles,
"refs": {k: len(v) for k, v in refs.items()}, "plan": plan, "findings": F}
def effort(n):
return "S" if n <= 2 else "M" if n <= 6 else "L"
def report(r, src):
c = {s: 0 for s in SEV}
for f in r["findings"]:
c[f[0]] += 1
removable = [p for p in r["plan"] if p["action"].startswith("remove")]
out = ["# Feature flag cleanup audit", "",
"Today %s, primary environment `%s`, stale after %d days. %d flag(s) in the inventory, %d source file(s) scanned in %s." % (
r["today"], r["primary"], r["stale_days"], r["flags"], r["files"], ", ".join(src)), ""]
if c["high"]:
v = "%d high finding(s) - flags used in code that the flag service does not know" % c["high"]
elif removable:
v = "%d flag(s) ready to remove" % len(removable)
else:
v = "no stale flags"
out += ["**Verdict: %s**" % v, "", "Cleanup candidates: %d (%d removable now, %d reference(s) to change). Findings: %d high, %d medium, %d low, %d info." % (
len(r["plan"]), len(removable), sum(p["refs"] for p in removable), c["high"], c["medium"], c["low"], c["info"]), ""]
out += ["## Cleanup plan", "", "| # | Flag | Type | Owner | Primary | Action | Why | Refs (files) | Effort | Where |", "|---|---|---|---|---|---|---|---|---|---|"]
for i, p in enumerate(r["plan"], 1):
locs = ", ".join("`%s`" % x for x in p["locs"][:4]) + (" +%d more" % (len(p["locs"]) - 4) if len(p["locs"]) > 4 else "")
out.append("| %d | `%s` | %s | %s | %s | **%s** | %s | %d (%d) | %s | %s |" % (i, p["key"], p["type"], p["owner"], p["state"], p["action"], p["why"],
p["refs"], p["files"], effort(p["refs"]) if p["refs"] else "-", locs or "-"))
out += ["", "Effort: S = 1-2 references, M = 3-6, L = 7 or more. \"keep ON\" = delete the flag check and the OFF branch; \"keep OFF\" = delete the guarded code. Archive the flag in the flag service only after the code change is deployed everywhere.", ""]
out += ["## Findings", "", "| Sev | Code | Flag | Finding | Fix |", "|---|---|---|---|---|"]
for s, code, k, msg, fix in r["findings"]:
out.append("| %s | %s | `%s` | %s | %s |" % (s, code, k, msg.replace("|", "\\|"), fix.replace("|", "\\|")))
out += ["", "## References per flag", "", "| Flag | References |", "|---|---|"]
for k, n in sorted(r["refs"].items()):
out.append("| `%s` | %d |" % (k, n))
out += ["", "Search covers string literals, common SDK calls and `flags.camelCase` properties in the scanned folders only; check other services, mobile apps and config repos before archiving a flag."]
return "\n".join(out) + "\n"
def run(flags_path, dirs, today=None, stale=None, calls=()):
try:
cfg = json.load(open(flags_path, encoding="utf-8"))
except (OSError, ValueError) as e:
raise InputError("cannot read %s: %s" % (flags_path, e))
c = load_flags(cfg, today, stale)
refs, unknown, dynamic, n = scan(dirs, list(c["flags"]), list(c["calls"]) + list(calls))
return audit(c, refs, unknown, dynamic, n)
# ---------------------------------------------------------------- self-test
def self_test():
import tempfile
tests = []
def t(name, cond):
tests.append((name, bool(cond)))
def mk(flags, files, **kw):
d = tempfile.mkdtemp()
for name, body in files.items():
os.makedirs(os.path.dirname(os.path.join(d, name)) or d, exist_ok=True)
open(os.path.join(d, name), "w").write(body)
cfg = {"today": "2026-11-05", "flags": flags}
cfg.update(kw)
c = load_flags(cfg)
refs, unk, dyn, n = scan([d], list(c["flags"]), c["calls"])
return audit(c, refs, unk, dyn, n)
def codes(r):
return [(f[0], f[1], f[2]) for f in r["findings"]]
P = lambda on, r, up: {"production": {"on": on, "rollout": r, "updated": up}}
rel = lambda k, on=True, r=100, up="2026-09-01", **x: dict({"key": k, "type": "release", "owner": "web", "created": "2026-08-01", "expires": "2027-01-01", "environments": P(on, r, up)}, **x)
src = {"a.ts": "if (client.isEnabled('new-checkout')) {}\nconst x = useFlag(\"dark-mode\")\n"}
r = mk([rel("new-checkout"), rel("dark-mode", up="2026-10-30")], src)
t("100% on for 65 days -> FF02", ("medium", "FF02", "new-checkout") in codes(r))
t("100% on for 6 days -> not stale", ("medium", "FF02", "dark-mode") not in codes(r))
t("plan action keep ON", [p["action"] for p in r["plan"] if p["key"] == "new-checkout"] == ["remove, keep ON"])
t("refs found via call", r["refs"]["new-checkout"] == 1 and r["refs"]["dark-mode"] == 1)
r = mk([rel("old-banner", on=False, r=0)], {"b.py": "if flags.is_enabled(\"old-banner\"):\n pass\n"})
t("off for 65 days -> FF03 keep OFF", ("medium", "FF03", "old-banner") in codes(r) and r["plan"][0]["action"] == "remove, keep OFF")
r = mk([rel("half", r=50)], {"c.js": "isEnabled('half')"})
t("stuck rollout -> FF12", ("medium", "FF12", "half") in codes(r))
r = mk([rel("new-checkout")], {"a.ts": "isEnabled('new_checkout')\n"})
t("undefined key in code -> FF01 high", ("high", "FF01", "new_checkout") in codes(r))
t("FF01 suggests the close key", any("typo of new-checkout" in f[4] for f in r["findings"]))
t("FF01 alone means 0 refs for the real key -> FF04", ("low", "FF04", "new-checkout") in codes(r))
r = mk([rel("ghost")], {"a.ts": "const a = 1\n"})
t("no refs -> FF04 + archive", ("low", "FF04", "ghost") in codes(r))
r = mk([rel("exp1", type="experiment", created="2026-05-01", r=50, up="2026-10-20")], {"a.ts": "variation('exp1', false)"})
t("experiment over 90 days -> FF09", ("medium", "FF09", "exp1") in codes(r))
r = mk([rel("exp2", expires="2026-10-01", up="2026-10-30")], {"a.ts": "isEnabled('exp2')"})
t("expired -> FF05", ("medium", "FF05", "exp2") in codes(r))
r = mk([dict(rel("ks"), type="kill-switch", expires=None)], {"a.ts": "isEnabled('ks')"})
t("kill-switch skipped -> FF06 info only", [x[1] for x in codes(r)] == ["FF06"])
r = mk([dict(rel("p", up="2026-10-30"), owner="")], {"a.ts": "isEnabled('p')"})
t("no owner -> FF07", ("low", "FF07", "p") in codes(r))
r = mk([dict(rel("d", up="2026-10-30"), environments={"production": {"on": True, "rollout": 100, "updated": "2026-10-30"}, "staging": {"on": False}})], {"a.ts": "isEnabled('d')"})
t("prod ahead of staging -> FF08", ("medium", "FF08", "d") in codes(r))
r = mk([rel("x")], {"a.ts": "const k = 'x' + region\nisEnabled(flagName)\n"})
t("dynamic key -> FF10 info", ("info", "FF10", "-") in codes(r))
r = mk([rel("x")], {"a.py": "is_enabled('export-' + region)\n"})
t("literal + variable is dynamic, not undefined", ("info", "FF10", "-") in codes(r) and not [f for f in r["findings"] if f[1] == "FF01"])
r = mk([rel("new-search", up="2026-10-30")], {"s.tsx": "if (flags.newSearch) {}\n"})
t("flags.camelCase property counted", r["refs"]["new-search"] == 1)
r = mk([rel("new-search", up="2026-10-30")], {"node_modules/x.js": "isEnabled('new-search')", "a.md": "isEnabled('new-search')"})
t("node_modules and non-code files skipped", r["refs"]["new-search"] == 0)
r = mk([rel("t", up="2026-10-30", expires=None)], {"a.ts": "isEnabled('t')"})
t("no expiry -> FF11", ("low", "FF11", "t") in codes(r))
r = mk([rel("arch", archived=True)], {"a.ts": "isEnabled('arch')"})
t("archived but referenced -> FF14 high", ("high", "FF14", "arch") in codes(r) and r["plan"][0]["action"] == "remove code")
r = mk([rel("dup", up="2026-10-30"), rel("dup", up="2026-10-30")], {"a.ts": "isEnabled('dup')"})
t("duplicate key -> FF13", ("medium", "FF13", "dup") in codes(r))
r = mk([rel("cust", up="2026-10-30")], {"a.ts": "myFlags.check('cust')\nmyFlags.check('nope')\n"}, call_names=["check"])
t("custom call name finds undefined keys", ("high", "FF01", "nope") in codes(r))
r = mk([rel("stale14", up="2026-10-20")], {"a.ts": "isEnabled('stale14')"}, stale_days=14)
t("stale_days setting respected", ("medium", "FF02", "stale14") in codes(r))
for bad, name in (({"flags": [{"key": "a", "type": "temp"}]}, "bad type"), ({"flags": [{"key": "a", "environments": {"production": {"on": True, "rollout": 150}}}]}, "rollout > 100"),
({"flags": [{"key": "a", "colour": 1}]}, "unknown flag key"), ({"flag": []}, "missing flags list")):
try:
load_flags(bad); t("rejected: " + name, False)
except InputError:
t("rejected: " + name, True)
r = mk([rel("new-checkout")], src)
t("report has verdict and plan", "**Verdict:" in report(r, ["x"]) and "## Cleanup plan" in report(r, ["x"]))
for n, ok in tests:
print("%s %s" % ("PASS" if ok else "FAIL", n))
p = sum(ok for _, ok in tests)
print("%d/%d passed" % (p, len(tests)))
return 0 if p == len(tests) else 1
def main(argv=None):
ap = argparse.ArgumentParser(description="Find stale feature flags and plan their removal.")
ap.add_argument("flags", nargs="?")
ap.add_argument("src", nargs="*")
ap.add_argument("--today")
ap.add_argument("--stale-days", type=int)
ap.add_argument("--call", action="append", default=[], help="extra flag-check function name (repeatable)")
ap.add_argument("--json", action="store_true")
ap.add_argument("--self-test", action="store_true")
a = ap.parse_args(argv)
if a.self_test:
return self_test()
if not a.flags or not a.src:
ap.error("give FLAGS.json and at least one source directory")
try:
r = run(a.flags, a.src, a.today, a.stale_days, a.call)
except InputError as e:
print("error: %s" % e, file=sys.stderr)
return 2
if a.json:
print(json.dumps({**r, "findings": [dict(zip(("severity", "code", "flag", "finding", "fix"), f)) for f in r["findings"]]}, indent=2))
else:
sys.stdout.write(report(r, a.src))
return 1 if any(f[0] == "high" for f in r["findings"]) else 0
if __name__ == "__main__":
sys.exit(main())0
Recently Updated
Video
A boy teaching the bangla meaning of manifestations with example nicely in 8s
A boy teaching the bangla meaning of manifestations with example nicely in 8s
TrendingImage
A compact Midjourney prompt for a striking vertical anime-style poster: a girl with a blue wolf-cut hairstyle caught in a playful moment against planets and alien spacecraft, pushed through an extreme 180-degree fisheye lens with heavy barrel distortion, so the frame edges bend inward and the center bulges toward you. Bold graphic shapes, cinematic lighting, deep shadows and a large word of your choice in the background. Tuned with chaos 50, raw mode, stylize 400 and a 1:2 aspect ratio.
Digital animation style illustration. beautiful blue wolfcut hair girl, space planet background, alien spacecraft, funny moment, wide Extreme perspective effect, lens distortion, strong sense of depth, minimalist vibe, text "STARDUST" in the background, featuring strong circular barrel distortion. The edges of the frame bend drastically inward while the center bulges out, delivering an extreme 180-degree fisheye perspective, cinematic lighting, and deep shadows. --chaos 50 --ar 1:2 --raw --stylize 400 --hd0
TrendingImage
A detailed style-transfer prompt that turns the character in your reference image into a rough, cute Japanese anime doodle: wobbly uneven black crayon lines, big flat color blocks that spill past the outlines, quick white highlights, pink blush strokes and visible crayon grain, as a half-body portrait on a pure white 1:1 canvas. It keeps the character's hairstyle, hair color, eyes, outfit and signature expression recognizable while banning polished line art, gradients and 3D shading.
Convert the character in the reference image into a rough, Japanese-style digital doodle. Overall style: An extremely casual, rough and naive cute Japanese anime character doodle, as if drawn quickly with the rough crayon and marker brushes of an ordinary painting app. Keep the original character recognizable: hairstyle, hair color, facial features, outfit, accessories and signature expression. Line art: * Outline the character with obvious, rough black strokes. * Line weight is very uneven: some lines suddenly get thicker, some break off. * Contours are loose, inaccurate and slightly crooked. * Lines have a clear hand-drawn grainy, smudged texture. * Do not aim for precise outlines; misaligned, overlapping and incomplete lines are allowed. * No fine, smooth vector line art. Coloring: * Use large areas of simple, opaque flat color. * Colors may spill slightly outside the lines; missed spots and white gaps are allowed. * Shadows use a few rough gray strokes or darker strokes of the same hue. * Highlights are casual, short white strokes. * Keep the rough texture of mixed crayon, pastel and marker. * No complex gradients, detailed lighting or rich layers of color. Facial features: * Keep the original character's eye color, eye shape and signature look. * Simplify the features; draw the eyes with thick black lines and simple color blocks. * Keep the mouth as simple as possible; the nose can be left out. * A few casual pink blush strokes can be added to the cheeks. * Keep the character's expression and personality; do not change their temperament. Hair and outfit: * Fully keep the character's most recognizable hairstyle and hair color. * Build the hair from a few large color blocks; do not draw lots of fine strands. * Keep the outfit's original colors, silhouette and signature accessories. * Heavily simplify clothing folds and decorations. * Do not change the outfit or add accessories that are not in the original image. Composition: * 1:1 square canvas. * Half-body portrait of the character, with a slightly oversized head. * Character centered, with natural white space around them. * Pure white background; no text, complex scenery or decorative borders. Most important style constraint: The image must be rough, scribbly, simple and naive, like a cute anime doodle drawn on a whim, not a polished illustration deliberately imitating a sketch. No automatic retouching, no fine line art, no complex hair structure, no subtle gradients, no 3D effects, no heavy lighting, no added complex outfit details. Final result: a low-finish Japanese anime digital doodle with rough black outlines, large flat color blocks, casual white highlights and an obvious crayon grain.
0
Create a reusable skill for vehicle-specific DIY repair manuals grounded in verified OEM sources. Cover beginner-friendly maintenance, diagnostics, disassembly, rebuilding and engine overhaul. Generate accurate, reviewed black-and-white diagrams in every chapter, embedded beside relevant steps. Use professional 8.5×11-inch layout, 200–230 pages. First provide a detailed outline, page budget and figure-placement plan for one approval; then deliver one complete, illustrated, editable DOCX.
--- name: car-repair-manual-writer description: Create a reusable skill for vehicle-specific DIY repair manuals grounded in verified OEM sources. Cover beginner-friendly maintenance, diagnostics, disassembly, rebuilding and engine overhaul. Generate accurate, reviewed black-and-white diagrams in every chapter, embedded beside relevant steps. Use professional 8.5×11-inch layout, 200–230 pages. First provide a detailed outline, page budget and figure-placement plan for one approval; then deliver one complete, illustrated, editable DOCX. --- # My Skill Describe what this skill does and how the agent should use it. ## Instructions - Step 1: ... - Step 2: ...
Opinionated conventions for building clear, honest and accessible charts and dashboards.
# Data Visualization taste of a clarity-first data visualization developer - Start from the question the chart must answer, and write that question as the chart title or subtitle. Confidence: 0.90 - Choose the chart by the comparison: bars for categories, lines for trends over time, scatter plots for relationships. Confidence: 0.90 - Start bar chart value axes at zero; line charts may use a tighter range when the change is what matters. Confidence: 0.90 - Avoid pie charts with more than three slices, and never use 3D charts. Confidence: 0.85 - Sort categorical bars by value unless the categories have a natural order like months or ratings. Confidence: 0.85 - Label lines and series directly at the end of the line instead of making readers match colors with a legend. Confidence: 0.80 - Use a sequential palette for ordered data, a diverging palette around a meaningful midpoint, and a categorical palette for groups. Confidence: 0.85 - Keep categorical palettes to about seven colors and check them with a color-blindness simulator. Confidence: 0.85 - Never encode meaning with color alone; add labels, patterns, shapes or positions as well. Confidence: 0.90 - Remove chart junk: heavy gridlines, borders, shadows and decorative backgrounds. Confidence: 0.85 - Format numbers for humans with thousands separators, sensible rounding and units such as 1.2M or 35 percent. Confidence: 0.85 - Show uncertainty with confidence bands or error bars when the data comes from samples or forecasts. Confidence: 0.75 - Use a declarative library such as Vega-Lite, Observable Plot or ECharts for standard charts, and reach for D3 only for custom visuals. Confidence: 0.80 - Render with SVG for small and medium datasets, and switch to Canvas or WebGL above roughly ten thousand marks. Confidence: 0.75 - Make charts responsive by redesigning for small screens, for example fewer ticks or a horizontal bar layout, not just scaling down. Confidence: 0.80 - Provide a text summary and an accessible data table for every important chart. Confidence: 0.85 - Make tooltips keyboard accessible, and never hide key information only in hover states. Confidence: 0.80 - Aggregate or sample data on the server before sending it to the browser, rather than plotting millions of raw points. Confidence: 0.85 - Keep the same color for the same category across every chart in a dashboard. Confidence: 0.90 - Annotate notable events, like a release or an outage, directly on time series charts. Confidence: 0.75 - Show the data source and the last refresh time under each chart. Confidence: 0.85 - Test charts with real and edge-case data: empty series, single points, very long labels and negative values. Confidence: 0.80
0
Taste
Opinionated conventions for planning, running and reading load and performance tests for web services.
# Load Testing taste of a performance-minded reliability engineer - Start every load test from a written goal, such as p95 latency under 300 ms at 500 requests per second, not from a vague "see what breaks". Confidence: 0.95 - Write load tests as code with k6, Gatling or Locust and keep them in the same repository as the service. Confidence: 0.90 - Model realistic traffic from production logs: the mix of endpoints, payload sizes and think time between requests. Confidence: 0.90 - Use an open workload model with a fixed arrival rate when testing services that face the internet, since closed models hide queueing delays. Confidence: 0.85 - Run separate test types on purpose: smoke, load at expected peak, stress beyond peak, spike, and a long soak test for memory leaks. Confidence: 0.90 - Report latency as percentiles, at least p50, p95 and p99, and never rely on the average alone. Confidence: 0.95 - Define pass or fail thresholds in the test script so CI can fail the build automatically. Confidence: 0.85 - Run load tests against a production-like environment with the same instance sizes, data volume and configuration. Confidence: 0.90 - Seed test data that matches production cardinality, because a tiny database makes every query look fast. Confidence: 0.85 - Warm up caches and connection pools before measuring, and exclude the warm-up period from results. Confidence: 0.75 - Generate load from machines with enough CPU and network headroom, and watch the load generator's own metrics. Confidence: 0.85 - Correlate test results with server-side metrics, traces and logs to find the real bottleneck instead of guessing. Confidence: 0.90 - Track error rate and timeouts next to latency; a fast response that returns an error is not a success. Confidence: 0.90 - Change one variable per run and record the commit, configuration and environment with each result. Confidence: 0.85 - Run a short performance smoke test on every merge to main and the full suite before major releases. Confidence: 0.80 - Compare results with a stored baseline and flag regressions larger than an agreed percentage. Confidence: 0.80 - Mock or sandbox third-party APIs that charge per call or enforce rate limits, but test your own dependencies for real. Confidence: 0.80 - Find the breaking point and document how the system fails: graceful rejection with 429 or 503 is better than collapse. Confidence: 0.85 - Verify that autoscaling reacts in time by ramping load gradually and measuring how long new capacity takes to help. Confidence: 0.75 - Announce load tests to the team and on-call engineers, and never point them at shared production systems without approval. Confidence: 0.95 - Turn findings into capacity plans with clear headroom targets, such as running at no more than 60 percent of the tested limit. Confidence: 0.70
0
Taste
Opinionated conventions for a fast, maintainable and portable Lua-based Neovim configuration.
# Neovim Config taste of a minimalist terminal-first developer - Write the whole config in Lua, starting from a single init.lua that requires small modules under lua/config and lua/plugins. Confidence: 0.90 - Use lazy.nvim as the plugin manager and commit lazy-lock.json so every machine gets the same plugin versions. Confidence: 0.90 - Lazy-load plugins by event, command, filetype or key mapping, and keep startup time under 50 ms measured with :Lazy profile. Confidence: 0.80 - Prefer the built-in LSP client with nvim-lspconfig over heavier all-in-one language plugins. Confidence: 0.85 - Install language servers, formatters and linters with mason.nvim, but pin the tool list in config instead of installing by hand. Confidence: 0.80 - Format on save with conform.nvim and lint with nvim-lint, using the same tools and settings the project runs in CI. Confidence: 0.85 - Use nvim-treesitter for highlighting, indentation and text objects, and list the parsers you need explicitly. Confidence: 0.85 - Pick one fuzzy finder, such as telescope.nvim or fzf-lua, and route files, grep, buffers and LSP symbols through it. Confidence: 0.85 - Set the leader key to space before loading any plugin so every mapping uses it. Confidence: 0.90 - Give every custom mapping a desc field so which-key and :map show what it does. Confidence: 0.85 - Group mappings by prefix, like leader f for find, leader g for git and leader l for LSP, and avoid overriding core Vim motions. Confidence: 0.80 - Keep options in one options.lua file using vim.opt, with a short comment for anything that is not obvious. Confidence: 0.80 - Use relative line numbers, a sign column that is always shown, and persistent undo files. Confidence: 0.75 - Use autocommand groups with clear = true so reloading the config never duplicates handlers. Confidence: 0.90 - Respect .editorconfig files and avoid hard-coding indentation per language unless a project has no settings. Confidence: 0.80 - Show git changes in the sign column with gitsigns.nvim and stage hunks from the editor. Confidence: 0.80 - Use the built-in completion engine or blink.cmp, with LSP and snippet sources only, to keep the popup fast and relevant. Confidence: 0.70 - Choose one colorscheme with good Tree-sitter and LSP semantic token support, and do not chase new themes every week. Confidence: 0.65 - Add a plugin only when it replaces a repeated manual step, and remove plugins you have not used in a month. Confidence: 0.80 - Keep machine-specific settings in a git-ignored local.lua file so the main config stays portable. Confidence: 0.75 - Run :checkhealth after upgrades and fix warnings before adding new plugins. Confidence: 0.80 - Store the config in a dotfiles repository and upgrade plugins deliberately, reviewing the lazy.nvim changelog first. Confidence: 0.85
0
Builds a seating chart for weddings, dinners and team events from your tables and guest list - keeps couples and families together, honours sit-with and keep-apart requests and head-table seats, puts mobility needs at accessible tables, seats nobody among strangers and fills tables by group. Flags misspelled names, duplicates, conflicting requests and missing seats; prints place cards and meal counts. Includes an offline stdlib Python planner.
---
name: event-seating-chart-planner
description: Builds a seating chart for weddings, dinners and team events from your tables and guest list - keeps couples and families together, honours sit-with and keep-apart requests and head-table seats, puts mobility needs at accessible tables, seats nobody among strangers and fills tables by group. Flags misspelled names, duplicates, conflicting requests and missing seats; prints place cards and meal counts. Includes an offline stdlib Python planner.
---
# Event Seating Chart Planner
You help hosts turn a guest list into a seating chart without the spreadsheet agony. Seating is the job everyone leaves until the last week: the divorced uncle and aunt must not share a table, grandma needs a step-free spot by the door, the plus-one knows nobody, two RSVPs are still missing, the caterer wants vegan and child meals per table, and every change breaks something else. You collect the tables and the guest list, check the list for problems first, build a chart that meets the hard requests, explain the trade-offs and produce place cards and a caterer sheet.
You work only from the information the host gives you. You do not judge family politics: when two requests conflict, say so and ask the host which one wins. Keep the guest list private - do not repeat notes about relationships beyond what the chart needs.
## Files in this skill
- `scripts/seating_plan.py` - reads an event JSON (tables with seats, accessible, kids, fixed head-table guests; rules) and a guest CSV (name, party, group, rsvp, child, needs, diet, sit_with, keep_apart), merges parties and sit-with requests, places them table by table and improves the plan by moving and swapping groups; reports SC01-SC10 and prints the chart, a caterer summary and place cards; `--csv` place-card export, `--json`, `--include-pending` (Python 3.8+ standard library only)
- `references/seating-rules-and-etiquette.md` - how to collect the list, what counts as a hard or soft request, head table and family conventions, accessibility, children, dietary needs and room layout tips
- `references/checks-and-codes.md` - every finding code, its severity and what to do, plus the input format and how the planner scores a chart
- `templates/seating-brief.md` - the summary to send the host (and the venue / caterer)
- `examples/event.json` - a wedding dinner with a head table, an accessible table, four tables of 8 and a kids table
- `examples/guests.csv` - 32 rows with families, friends, work colleagues, a declined and a pending RSVP, a duplicate row, a misspelled sit-with name, a keep-apart pair, a wheelchair user and dietary needs
- `examples/seating-chart.md` - the real planner output on the example
## Workflow
### 1. Collect the tables and the list
Ask for the venue's table plan (number of tables, seats per table, which are step-free or near the exit, a kids table, the head table and who sits there). Ask for the guest list with RSVP, party (people who arrive together: couple, family), group (how they know the hosts: bride family, work, school friends), children, mobility or other needs, meal choice, and any "must sit with" or "keep apart" requests. Put them in `examples/event.json` and `examples/guests.csv` form.
### 2. Run the planner
```
python3 scripts/seating_plan.py examples/event.json examples/guests.csv
python3 scripts/seating_plan.py event.json guests.csv --include-pending
python3 scripts/seating_plan.py event.json guests.csv --csv > place-cards.csv
python3 scripts/seating_plan.py event.json guests.csv --json
python3 scripts/seating_plan.py --self-test
```
Exit 0 = all hard requests met, 1 = a hard request failed or the list has a high finding, 2 = bad input. Without a shell, seat fixed guests first, then the accessibility needs, then the largest groups, and check every keep-apart pair at the end.
### 3. Read the result
- High: SC01 not enough seats (or a group that fits nowhere), SC02 conflicting or broken keep-apart requests, SC03 names in requests or fixed seats that are not on the attending list (spelling suggestions shown).
- Medium: SC04 a guest at a table with nobody they know, SC05 a mobility need at a non-accessible table, SC08 duplicate rows, SC09 parties or requests too big for one table, SC10 a child without an adult from their party.
- Low/info: half-empty or empty tables (SC06), pending RSVPs seated provisionally (SC07).
### 4. Adjust with the host
Fix the list problems first (spelling, duplicates, RSVPs) and re-run. Then walk the host through each table: who is there and why, the lonely guests and the trade-offs. Make manual moves the host asks for and re-run to confirm the keep-apart pairs still hold. Fill `templates/seating-brief.md`.
### 5. Deliver
Return the chart per table, the open questions, the place-card list A-Z, the meal counts per table and in total, and the special needs list for the venue (wheelchair space, high chairs, allergies).
## Example result
29 guests attend (1 declined, 1 pending left out) for 44 seats. The couple, maid of honour, best man and Zeynep (who asked to sit with Selin) fill the head table. Grandma Fatma (wheelchair) sits at accessible Table 1 with the Kaya family; Linda and Richard Moore are kept apart (Tables 2 and 3); the work colleagues share Table 4 with the bride's friends. Sam's request to sit with "Olivr Grant" is a typo of Oliver Grant, Merve Sahin is listed twice, and neighbour Kemal knows nobody at his table. The kids table is empty because children stay with their parents.
## Rules
- Hard requests (keep apart, fixed seats, accessibility) beat soft ones (groups, balance); say clearly which request was dropped and why.
- Never split a couple or a parent and a young child unless the host asks.
- Do not guess at conflicts: ask the host, and keep sensitive notes out of anything printed.
- Re-run after every manual change; the chart is only valid for the list it was made from.
- Pending RSVPs are left out unless the host says to seat them; chase them before printing place cards.
FILE:references/seating-rules-and-etiquette.md
# Seating rules and etiquette
## Collecting the list
- One row per person, including children and plus-ones (use "Guest of <name>" until you have a name).
- Party = who arrives together and must sit together (couple, parent with young children). Group = how they know the hosts; it decides who shares a table.
- Ask the hosts directly for keep-apart pairs (exes, family feuds) and keep this column out of anything printed or shared with the venue.
- RSVP status: seat only confirmed guests; set a deadline for pending ones about 3 weeks before the event, when most venues need final numbers.
## Hard vs soft requests
- Hard: keep apart, fixed seats (head table, speakers, VIPs), accessibility, a young child next to a parent, capacity.
- Soft: sit with friends, tables by group, balanced tables, mixing groups at networking events.
When a soft request breaks a hard one, the hard one wins; tell the host.
## Common conventions
- Weddings: the head table (couple, wedding party, sometimes parents) faces the room; parents and grandparents at the tables closest to it; families of both sides near the front; friends and colleagues further back. Sweetheart table = couple only.
- Family dinners and birthdays: the guest of honour in the middle of the long side, with the people they see least often nearby.
- Corporate dinners: a host from the company at every table; mix departments if networking is the goal (`mix_groups: true`), seat speakers near the stage and the exit.
- Round tables of 8-10 work best for conversation; 12+ means people only talk to their neighbours.
- Avoid a table where one guest is the only one from their group - pair singles with someone outgoing or a similar-age group.
## Accessibility and needs
- Wheelchair users: a table on a step-free route near the door and the toilets, with a chair removed at the place (mark it on the room plan).
- Hearing impairment: away from speakers and the band, facing the room.
- Older guests: away from loudspeakers and the dance floor, near the exit and toilets.
- High chairs and booster seats: tell the venue per table.
- Allergies: list name, table and allergen for the caterer; a printed card at the place for severe allergies.
## Children
- Toddlers stay with their parents. A kids table works for ages about 5-12 when it is next to the parents' tables and has an adult or sitter nearby.
- Count child meals separately (and high chairs) in the caterer summary.
## Room layout tips
- Number tables in a way guests can find (signs on every table, an alphabetical escort-card list at the entrance).
- Keep the path from the door to the accessible table clear.
- Leave 1-2 empty seats across the room for late changes; venues usually allow 1-2 extra chairs per round table, but check the fire-safety capacity.
## Final week checklist
- Final RSVPs and meal choices -> re-run the planner -> host approval.
- Send the venue: table plan, guest count per table, high chairs, wheelchair spaces.
- Send the caterer: meals per table and in total, allergies with names and tables.
- Print place cards and the escort-card list from `--csv`.
FILE:references/checks-and-codes.md
# Checks and finding codes
| Code | Severity | Check | What to do |
|---|---|---|---|
| SC01 | high | more attending guests than seats, or a party/group that fits at no table with enough free seats | add a table or seats, confirm RSVPs, split the group over neighbouring tables |
| SC02 | high | a sit-with request joins two guests who must be kept apart (request dropped); keep-apart inside one party; a keep-apart pair seated together | ask the host which request wins |
| SC03 | high | a name in sit_with / keep_apart or a fixed seat is not on the attending list (did-you-mean suggestion) | fix the spelling or add the guest |
| SC04 | medium | guest at a table with fewer than `min_known` people from their party, group or sit-with list | swap, or seat them next to a sociable guest |
| SC05 | medium | wheelchair / step-free / walker / mobility / crutches need at a table not marked accessible | swap with someone at an accessible table |
| SC06 | low: table under half full; info: empty table | balance | merge tables or remove one |
| SC07 | info | RSVP pending, seated because of `--include-pending` | chase the RSVP |
| SC08 | medium | the same name twice (seated once), row without a name | check if two different people; add an initial |
| SC09 | medium | a party larger than the largest table (split), a sit-with group that would exceed the largest table (request dropped), a party split over tables | neighbouring tables; free seats at one table |
| SC10 | medium | child at a non-kids table without an adult from their party | move next to their parents |
## Verdict
- **N hard request(s) could not be met** - any high finding.
- **all hard requests met, N soft issue(s)** - medium findings only.
- **all requests met**.
## How the planner works
1. Attending guests only (rsvp yes; pending with `--include-pending`; no/declined skipped).
2. Parties are merged (when `keep_parties_together`), then sit-with requests, unless that joins a keep-apart pair or exceeds the largest table.
3. Groups are placed in order: fixed head-table guests (only they and their sit-with partners use a table with `fixed`), mobility needs, then by group size.
4. Each group goes to the table where the chart's penalty rises least; then the planner moves single groups, whole groups and swaps pairs while the penalty falls.
5. Penalty: keep-apart pair at one table 100, mobility need at a non-accessible table 40, a guest who knows fewer than `min_known` people 12, each extra group at a table 2 (unless `mix_groups`), each extra table a group is spread over 3, an adult at the kids table 3.
The plan is deterministic: the same input gives the same chart.
## Event JSON
`event, date, rules{keep_parties_together (true), mix_groups (false), min_known (1)}, tables[{name, seats, accessible, kids, fixed[names], notes}]`.
## Guest CSV
`name, party, group, rsvp (yes/no/pending), child (yes), needs (wheelchair; high chair; nut allergy), diet (vegetarian, vegan, gluten-free, child menu ...), sit_with (names separated by ;), keep_apart (names separated by ;)`. Only `name` is required; party defaults to the name, group to "-", rsvp to yes.
FILE:templates/seating-brief.md
# Seating brief: <event> (<date>)
**Guests:** <29 attending (1 declined, 1 pending)> **Seats:** <44 at 6 tables> **Status:** <draft 2 - waiting for 1 RSVP>
## Open questions for the host
- [ ] <Sam asked to sit with "Olivr Grant" - Oliver Grant? (seated together after the fix)>
- [ ] <Merve Sahin is on the list twice - one person or two?>
- [ ] <Kemal knows nobody at Table 3 - who should he sit next to?>
- [ ] <Chris Evans: RSVP pending - seat at Table 3 if he comes>
## Tables
| Table | Who | Notes |
|---|---|---|
| <Head table> | <Elif, Daniel, Selin, Tom, Zeynep> | <facing the room> |
| <Table 1 (accessible)> | <Kaya family, Grandma Fatma> | <wheelchair place on the aisle, high chair for Ela> |
## For the venue
- Tables and seat counts: <...>
- Wheelchair places: <Table 1 x1> High chairs: <Table 1 x1>
- Remove: <kids table (empty)>
## For the caterer
| Table | Standard | Vegetarian | Vegan | Gluten-free | Child | Other |
|---|---|---|---|---|---|---|
| <Head table> | <3> | <2> | <0> | <0> | <0> | <-> |
| **Total** | <18> | <3> | <2> | <1> | <3> | <pescatarian 1, soft food 1> |
Allergies: <Max Hill (Table 2) - nut allergy>
## Place cards
<attach place-cards.csv from `seating_plan.py --csv`>
FILE:examples/event.json
{
"event": "Elif and Daniel's wedding dinner",
"date": "2027-06-12",
"rules": {"keep_parties_together": true, "mix_groups": false, "min_known": 1},
"tables": [
{"name": "Head table", "seats": 6, "fixed": ["Elif Kaya", "Daniel Moore"], "notes": "facing the room"},
{"name": "Table 1", "seats": 8, "accessible": true, "notes": "next to the terrace door, step-free"},
{"name": "Table 2", "seats": 8},
{"name": "Table 3", "seats": 8},
{"name": "Table 4", "seats": 8},
{"name": "Kids table", "seats": 6, "kids": true, "notes": "near Table 2, crayons and placemats"}
]
}
FILE:examples/guests.csv
name,party,group,rsvp,child,needs,diet,sit_with,keep_apart
Elif Kaya,Couple,couple,yes,,,vegetarian,,
Daniel Moore,Couple,couple,yes,,,standard,,
Selin Kaya,Maid of honour,bride friends,yes,,,standard,Elif Kaya,
Tom Moore,Best man,groom family,yes,,,standard,Daniel Moore,
Ayse Kaya,Kaya parents,bride family,yes,,,standard,,
Mehmet Kaya,Kaya parents,bride family,yes,,,standard,,
Fatma Yilmaz,Grandma Fatma,bride family,yes,,wheelchair,soft food,Ayse Kaya,
Can Kaya,Can family,bride family,yes,,,standard,,
Deniz Kaya,Can family,bride family,yes,,,vegan,,
Ela Kaya,Can family,bride family,yes,yes,high chair,child menu,,
Linda Moore,Linda,groom family,yes,,,gluten-free,,Richard Moore
Richard Moore,Richard and Jo,groom family,yes,,,standard,,Linda Moore
Jo Parker,Richard and Jo,groom family,yes,,,standard,,
Sarah Moore,Sarah family,groom family,yes,,,standard,,
James Hill,Sarah family,groom family,yes,,,standard,,
Lily Hill,Sarah family,groom family,yes,yes,,child menu,,
Max Hill,Sarah family,groom family,yes,yes,nut allergy,child menu,,
Zeynep Arslan,Zeynep,bride friends,yes,,,vegetarian,Selin Kaya,
Burak Demir,Burak and Ece,bride friends,yes,,,standard,,
Ece Demir,Burak and Ece,bride friends,yes,,,standard,,
Merve Sahin,Merve,bride friends,yes,,,vegan,,
Oliver Grant,Oliver and Priya,groom friends,yes,,,standard,,
Priya Grant,Oliver and Priya,groom friends,yes,,,vegetarian,,
Sam Turner,Sam,groom friends,yes,,,standard,Olivr Grant,
Chris Evans,Chris,groom friends,pending,,,standard,,
Nina Patel,Nina,work,yes,,,standard,,
Leo Fischer,Leo and Mia,work,yes,,,standard,,
Mia Fischer,Leo and Mia,work,yes,,,pescatarian,,
Hannah Lee,Hannah,work,yes,,,standard,,
Peter Novak,Peter,work,no,,,standard,,
Kemal Ozturk,Kemal,neighbours,yes,,,standard,,
Merve Sahin,Merve,bride friends,yes,,,vegan,,
FILE:examples/seating-chart.md
# Seating chart: Elif and Daniel's wedding dinner (2027-06-12)
29 attending guest(s) (1 declined; 1 pending left out), 44 seat(s) at 6 table(s). Source: examples/guests.csv.
**Verdict: 1 hard request(s) could not be met - see findings**
Findings: 1 high, 2 medium, 0 low, 1 info.
## Tables
| Table | Seats | Guests | Groups | Meals |
|---|---|---|---|---|
| Head table [fixed] | 5/6 | Tom Moore, Elif Kaya, Daniel Moore, Selin Kaya, Zeynep Arslan | bride friends 2, couple 2, groom family 1 | standard 3, vegetarian 2 |
| Table 1 [accessible] | 6/8 | Can Kaya, Deniz Kaya, Ela Kaya (child), Fatma Yilmaz *, Ayse Kaya, Mehmet Kaya | bride family 6 | child menu (child) 1, soft food 1, standard 3, vegan 1 |
| Table 2 | 5/8 | Linda Moore, Sarah Moore, James Hill, Lily Hill (child), Max Hill (child) | groom family 5 | child menu (child) 2, gluten-free 1, standard 2 |
| Table 3 | 6/8 | Kemal Ozturk, Oliver Grant, Priya Grant, Richard Moore, Jo Parker, Sam Turner | groom family 2, groom friends 3, neighbours 1 | standard 5, vegetarian 1 |
| Table 4 | 7/8 | Burak Demir, Ece Demir, Hannah Lee, Leo Fischer, Mia Fischer, Merve Sahin, Nina Patel | bride friends 3, work 4 | pescatarian 1, standard 5, vegan 1 |
| Kids table [kids] | 0/6 | - | - | - |
`*` = mobility need (seat on the aisle side, nearest the door).
## Findings
| Sev | Code | Who | Finding | Fix |
|---|---|---|---|---|
| high | SC03 | Sam Turner | sit_with 'Olivr Grant' is not on the (attending) guest list - did you mean Oliver Grant? | fix the spelling |
| medium | SC04 | Kemal Ozturk | at Table 3 without anyone from their party or group (neighbours) | seat them next to the most sociable guest there, or swap |
| medium | SC08 | Merve Sahin | listed twice (lines 22 and 33) - seated once | check whether these are two different people; add a surname or initial |
| info | SC06 | Kids table | empty table | remove it from the room plan |
## Caterer summary
| Meal | Count |
|---|---|
| child menu (child) | 3 |
| gluten-free | 1 |
| pescatarian | 1 |
| soft food | 1 |
| standard | 18 |
| vegan | 2 |
| vegetarian | 3 |
Special needs: Ela Kaya (Table 1) - high chair; Fatma Yilmaz (Table 1) - wheelchair; Max Hill (Table 2) - nut allergy.
## Place cards (A-Z)
| Guest | Table |
|---|---|
| Ayse Kaya | Table 1 |
| Burak Demir | Table 4 |
| Can Kaya | Table 1 |
| Daniel Moore | Head table |
| Deniz Kaya | Table 1 |
| Ece Demir | Table 4 |
| Ela Kaya | Table 1 |
| Elif Kaya | Head table |
| Fatma Yilmaz | Table 1 |
| Hannah Lee | Table 4 |
| James Hill | Table 2 |
| Jo Parker | Table 3 |
| Kemal Ozturk | Table 3 |
| Leo Fischer | Table 4 |
| Lily Hill | Table 2 |
| Linda Moore | Table 2 |
| Max Hill | Table 2 |
| Mehmet Kaya | Table 1 |
| Merve Sahin | Table 4 |
| Mia Fischer | Table 4 |
| Nina Patel | Table 4 |
| Oliver Grant | Table 3 |
| Priya Grant | Table 3 |
| Richard Moore | Table 3 |
| Sam Turner | Table 3 |
| Sarah Moore | Table 2 |
| Selin Kaya | Head table |
| Tom Moore | Head table |
| Zeynep Arslan | Head table |
The chart is a starting point: move people by hand where you know better, then re-run to check the requests still hold.
FILE:scripts/seating_plan.py
#!/usr/bin/env python3
"""Event seating chart planner (stdlib only, Python 3.8+).
Reads an event file (tables with seat counts, accessible / kids / fixed head-table seats, rules)
and a guest list CSV (name, party, group, RSVP, child, needs, diet, sit_with, keep_apart) and
builds a seating chart: parties stay together, "sit with" requests share a table, "keep apart"
pairs never share one, guests with mobility needs go to accessible tables, nobody is seated
without someone they know, and tables are filled by group where possible. Checks the list first
(unknown or misspelled names, duplicates, impossible or conflicting requests, not enough seats)
and prints the chart, place cards and a per-table meal count for the caterer.
Usage:
seating_plan.py EVENT.json GUESTS.csv [--include-pending] [--csv] [--json]
seating_plan.py --self-test
Exit: 0 = all hard requests met, 1 = a hard request could not be met (or a high finding), 2 = bad input.
"""
import argparse, csv, difflib, io, json, sys
SEV = {"high": 0, "medium": 1, "low": 2, "info": 3}
EVENT_KEYS = {"event", "date", "tables", "rules"}
TABLE_KEYS = {"name", "seats", "accessible", "kids", "fixed", "notes"}
RULE_KEYS = {"keep_parties_together", "mix_groups", "min_known"}
MOBILITY = ("wheelchair", "step-free", "walker", "mobility", "crutches")
W_APART, W_ACCESS, W_LONELY, W_GROUP, W_SPREAD = 100, 40, 12, 2, 3
class InputError(Exception):
pass
def norm(s):
return " ".join(str(s or "").split()).lower()
def split_list(s):
return [x.strip() for x in str(s or "").replace(",", ";").split(";") if x.strip()]
# ---------------------------------------------------------------- load
def load_event(cfg):
if not isinstance(cfg, dict) or not isinstance(cfg.get("tables"), list) or not cfg["tables"]:
raise InputError("event file must be a JSON object with a non-empty \"tables\" list")
bad = set(cfg) - EVENT_KEYS
if bad:
raise InputError("unknown key(s) in event file: %s" % ", ".join(sorted(bad)))
rules = cfg.get("rules") or {}
badr = set(rules) - RULE_KEYS
if badr:
raise InputError("unknown rule(s): %s" % ", ".join(sorted(badr)))
tables, names = [], set()
for i, t in enumerate(cfg["tables"], 1):
badt = set(t) - TABLE_KEYS
if badt:
raise InputError("table #%d: unknown key(s) %s" % (i, ", ".join(sorted(badt))))
name = str(t.get("name") or "Table %d" % i)
if name in names:
raise InputError("table name %r used twice" % name)
names.add(name)
seats = t.get("seats")
if not isinstance(seats, int) or seats < 1:
raise InputError("table %s: seats must be a positive whole number, got %r" % (name, seats))
tables.append({"name": name, "seats": seats, "accessible": bool(t.get("accessible")), "kids": bool(t.get("kids")),
"fixed": [str(x) for x in t.get("fixed") or []], "notes": t.get("notes", "")})
return {"event": cfg.get("event", "Event"), "date": cfg.get("date", ""), "tables": tables,
"together": rules.get("keep_parties_together", True), "mix": bool(rules.get("mix_groups", False)),
"min_known": int(rules.get("min_known", 1))}
def load_guests(text, include_pending=False):
rows = list(csv.DictReader(io.StringIO(text)))
if not rows:
raise InputError("guest list is empty")
cols = {c.strip().lower() for c in rows[0].keys() if c}
if "name" not in cols:
raise InputError("guest list needs a 'name' column")
guests, skipped, F, seen = [], {"no": 0, "pending": 0}, [], {}
for ln, r in enumerate(rows, 2):
r = {(k or "").strip().lower(): (v or "").strip() for k, v in r.items()}
name = " ".join(r.get("name", "").split())
if not name:
F.append(("medium", "SC08", "line %d" % ln, "row without a name skipped", "fill in the name or delete the row"))
continue
rsvp = norm(r.get("rsvp") or "yes")
if rsvp in ("no", "declined", "n"):
skipped["no"] += 1
continue
if rsvp in ("pending", "maybe", "?", "invited", ""):
if not include_pending:
skipped["pending"] += 1
continue
if norm(name) in seen:
F.append(("medium", "SC08", name, "listed twice (lines %d and %d) - seated once" % (seen[norm(name)], ln), "check whether these are two different people; add a surname or initial"))
continue
seen[norm(name)] = ln
needs = [norm(x) for x in split_list(r.get("needs"))]
guests.append({"name": name, "party": r.get("party") or name, "group": r.get("group") or "-",
"child": norm(r.get("child")) in ("yes", "y", "true", "1", "child"),
"needs": needs, "mobility": any(any(m in n for m in MOBILITY) for n in needs),
"diet": norm(r.get("diet")) or "standard", "sit_with": split_list(r.get("sit_with")),
"keep_apart": split_list(r.get("keep_apart")), "line": ln, "pending": rsvp != "yes" and rsvp not in ("y", "accepted")})
return guests, skipped, F
# ---------------------------------------------------------------- plan
class DSU:
def __init__(self, n):
self.p = list(range(n))
def find(self, a):
while self.p[a] != a:
self.p[a] = self.p[self.p[a]]
a = self.p[a]
return a
def union(self, a, b):
self.p[self.find(a)] = self.find(b)
def plan(ev, guests, F=None):
F = list(F or [])
add = lambda sev, code, who, msg, fix: F.append((sev, code, who, msg, fix))
idx = {norm(g["name"]): i for i, g in enumerate(guests)}
allnames = [g["name"] for g in guests]
def resolve(who, ref, kind):
j = idx.get(norm(ref))
if j is None:
close = difflib.get_close_matches(ref, allnames, 1, 0.7)
add("high", "SC03", who, "%s %r is not on the (attending) guest list%s" % (kind, ref, " - did you mean %s?" % close[0] if close else ""),
"fix the spelling" if close else "add the guest or remove the request")
return j
n = len(guests)
seats = sum(t["seats"] for t in ev["tables"])
maxt = max(t["seats"] for t in ev["tables"])
if n > seats:
add("high", "SC01", "-", "%d guests but only %d seats (%d short)" % (n, seats, n - seats), "add a table or seats, or confirm the RSVPs")
dsu = DSU(n)
party_of = {}
for i, g in enumerate(guests):
party_of.setdefault(norm(g["party"]), []).append(i)
if ev["together"]:
for p, mem in party_of.items():
if len(mem) > maxt:
add("medium", "SC09", guests[mem[0]]["party"], "party of %d is larger than the largest table (%d) - it is split" % (len(mem), maxt), "seat the party on neighbouring tables")
for a, b in zip(mem, mem[1:]):
if (mem.index(b)) % maxt:
dsu.union(a, b)
else:
for a, b in zip(mem, mem[1:]):
dsu.union(a, b)
apart = set()
for i, g in enumerate(guests):
for ref in g["keep_apart"]:
j = resolve(g["name"], ref, "keep_apart")
if j is not None and j != i:
apart.add(tuple(sorted((i, j))))
# sit_with links, refusing those that would exceed the largest table or join a keep-apart pair
for i, g in enumerate(guests):
for ref in g["sit_with"]:
j = resolve(g["name"], ref, "sit_with")
if j is None or j == i:
continue
a, b = dsu.find(i), dsu.find(j)
if a == b:
continue
size = sum(1 for k in range(n) if dsu.find(k) in (a, b))
clash = [p for p in apart if {dsu.find(p[0]), dsu.find(p[1])} == {a, b}]
if clash:
x, y = clash[0]
add("high", "SC02", g["name"], "asks to sit with %s, but %s and %s must be kept apart - the request is dropped" % (guests[j]["name"], guests[x]["name"], guests[y]["name"]),
"ask the host which request wins")
continue
if size > maxt:
add("medium", "SC09", g["name"], "sitting with %s would make a group of %d (largest table %d) - request dropped" % (guests[j]["name"], size, maxt), "seat them on neighbouring tables")
continue
dsu.union(i, j)
for x, y in sorted(apart):
if dsu.find(x) == dsu.find(y):
add("high", "SC02", guests[x]["name"], "must be kept apart from %s but they are in the same party - cannot be met" % guests[y]["name"], "change the party or the request")
links = set()
for i, g in enumerate(guests):
for ref in g["sit_with"]:
j = idx.get(norm(ref))
if j is not None:
links.add((i, j)); links.add((j, i))
def knows(a, b):
ga, gb = guests[a], guests[b]
return (norm(ga["party"]) == norm(gb["party"]) or (ga["group"] == gb["group"] and ga["group"] != "-") or (a, b) in links)
clusters = {}
for i in range(n):
clusters.setdefault(dsu.find(i), []).append(i)
cl = list(clusters.values())
T = ev["tables"]
fixed_at = {}
for ti, t in enumerate(T):
for nm in t["fixed"]:
j = idx.get(norm(nm))
if j is None:
close = difflib.get_close_matches(nm, allnames, 1, 0.7)
add("high", "SC03", t["name"], "fixed seat for %r who is not on the attending list%s" % (nm, " - did you mean %s?" % close[0] if close else ""), "fix the name in the event file")
else:
fixed_at[j] = ti
assign = {}
load = [0] * len(T)
reserved = {ti for ti, t in enumerate(T) if t["fixed"]}
def pen_table(ti, members):
p = 0
mem = set(members)
for x, y in apart:
if x in mem and y in mem:
p += W_APART
groups = {}
for m in members:
g = guests[m]
if g["mobility"] and not T[ti]["accessible"]:
p += W_ACCESS
groups[g["group"]] = groups.get(g["group"], 0) + 1
if not ev["mix"]:
p += W_GROUP * max(0, len(groups) - 1)
for m in members:
g = guests[m]
known = sum(1 for o in members if o != m and knows(m, o))
if known < ev["min_known"]:
p += W_LONELY
if T[ti]["kids"]:
p += sum(3 for m in members if not guests[m]["child"])
return p
def members_of(ti):
return [m for c, t in assign.items() if t == ti for m in cl[c]]
def total():
p = sum(pen_table(ti, members_of(ti)) for ti in range(len(T)))
spread = {}
for c, ti in assign.items():
for m in cl[c]:
if guests[m]["group"] != "-":
spread.setdefault(guests[m]["group"], set()).add(ti)
return p + W_SPREAD * sum(len(v) - 1 for v in spread.values())
gsize = {}
for g in guests:
gsize[g["group"]] = gsize.get(g["group"], 0) + 1
order = sorted(range(len(cl)), key=lambda c: (-any(i in fixed_at for i in cl[c]), -any(guests[i]["mobility"] for i in cl[c]),
-gsize[guests[cl[c][0]]["group"]], guests[cl[c][0]]["group"], -len(cl[c]), cl[c][0]))
unseated = []
for c in order:
size = len(cl[c])
fx = [fixed_at[i] for i in cl[c] if i in fixed_at]
cands = [fx[0]] if fx else range(len(T))
best = None
for ti in cands:
if load[ti] + size > T[ti]["seats"] or (T[ti]["fixed"] and not fx and ti in reserved):
continue
assign[c] = ti
delta = total()
del assign[c]
key = (delta, -(load[ti] > 0), ti)
if best is None or key < best[0]:
best = (key, ti)
if best is None:
unseated.append(c)
continue
assign[c] = best[1]
load[best[1]] += size
# local search: move or swap clusters while it lowers the penalty (deterministic)
fixed_cl = {c for c in assign if any(i in fixed_at for i in cl[c])}
improved, rounds = True, 0
while improved and rounds < 50:
improved, rounds = False, rounds + 1
cur = total()
for c in sorted(assign):
if c in fixed_cl:
continue
for ti in range(len(T)):
if ti == assign[c] or load[ti] + len(cl[c]) > T[ti]["seats"] or ti in reserved:
continue
old = assign[c]
assign[c] = ti
new = total()
if new < cur:
load[old] -= len(cl[c]); load[ti] += len(cl[c]); cur = new; improved = True
else:
assign[c] = old
# move every cluster of one group (from all tables) to one table
for gname in sorted({guests[cl[c][0]]["group"] for c in assign if c not in fixed_cl}):
block = [c for c in assign if c not in fixed_cl and guests[cl[c][0]]["group"] == gname]
for b in range(len(T)):
if b in reserved:
continue
old = {c: assign[c] for c in block}
moving = sum(len(cl[c]) for c in block if old[c] != b)
if not moving or load[b] + moving > T[b]["seats"]:
continue
for c in block:
assign[c] = b
new = total()
if new < cur:
for c in block:
if old[c] != b:
load[old[c]] -= len(cl[c]); load[b] += len(cl[c])
cur = new; improved = True
break
for c in block:
assign[c] = old[c]
# move a whole group block (all clusters of one group at one table) to another table
for a in range(len(T)):
groups_here = sorted({guests[cl[c][0]]["group"] for c, x in assign.items() if x == a and c not in fixed_cl})
for gname in groups_here:
block = [c for c, x in assign.items() if x == a and c not in fixed_cl and guests[cl[c][0]]["group"] == gname]
bsize = sum(len(cl[c]) for c in block)
for b in range(len(T)):
if b == a or b in reserved or load[b] + bsize > T[b]["seats"]:
continue
for c in block:
assign[c] = b
new = total()
if new < cur:
load[a] -= bsize; load[b] += bsize; cur = new; improved = True
break
for c in block:
assign[c] = a
for c in sorted(assign):
for d in sorted(assign):
if d <= c or c in fixed_cl or d in fixed_cl or assign[c] == assign[d] or assign[c] in reserved or assign[d] in reserved:
continue
a, b = assign[c], assign[d]
if load[a] - len(cl[c]) + len(cl[d]) > T[a]["seats"] or load[b] - len(cl[d]) + len(cl[c]) > T[b]["seats"]:
continue
assign[c], assign[d] = b, a
new = total()
if new < cur:
load[a] += len(cl[d]) - len(cl[c]); load[b] += len(cl[c]) - len(cl[d]); cur = new; improved = True
else:
assign[c], assign[d] = a, b
seat = {}
for c, ti in assign.items():
for i in cl[c]:
seat[i] = ti
for c in unseated:
add("high", "SC01", ", ".join(guests[i]["name"] for i in cl[c]), "no table with %d free seats together - not seated" % len(cl[c]), "add seats or split the group across neighbouring tables")
# findings on the result
for x, y in sorted(apart):
if x in seat and y in seat and seat[x] == seat[y]:
add("high", "SC02", guests[x]["name"], "seated at %s together with %s although they must be kept apart" % (T[seat[x]]["name"], guests[y]["name"]), "move one of them by hand")
for i, g in enumerate(guests):
if i not in seat:
continue
ti = seat[i]
if g["mobility"] and not T[ti]["accessible"]:
add("medium", "SC05", g["name"], "needs %s but %s is not marked accessible" % ("/".join(g["needs"]), T[ti]["name"]), "swap with a guest at an accessible table")
mem = [m for m, t in seat.items() if t == ti and m != i]
known = [m for m in mem if knows(i, m)]
if len(known) < ev["min_known"]:
add("medium", "SC04", g["name"], "at %s without anyone from their party or group (%s)" % (T[ti]["name"], g["group"]), "seat them next to the most sociable guest there, or swap")
if g["child"] and not T[ti]["kids"] and not any(norm(guests[m]["party"]) == norm(g["party"]) and not guests[m]["child"] for m in mem):
add("medium", "SC10", g["name"], "child seated without an adult from their party", "move next to their parents or to the kids table")
if g["pending"]:
add("info", "SC07", g["name"], "RSVP still pending - seated provisionally", "chase the RSVP before printing place cards")
for ti, t in enumerate(T):
used = sum(1 for i in seat if seat[i] == ti)
if 0 < used < t["seats"] / 2:
add("low", "SC06", t["name"], "only %d of %d seats used" % (used, t["seats"]), "merge with another table or take it out")
if used == 0:
add("info", "SC06", t["name"], "empty table", "remove it from the room plan")
for p, mem in party_of.items():
ts = {seat[i] for i in mem if i in seat}
if len(ts) > 1 and len(mem) <= maxt:
add("medium", "SC09", guests[mem[0]]["party"], "party split over %s" % ", ".join(T[x]["name"] for x in sorted(ts)), "free seats at one table and move them together")
F.sort(key=lambda x: (SEV[x[0]], x[1], x[2]))
return {"seat": seat, "tables": T, "guests": guests, "findings": F, "penalty": total(), "seats": seats}
# ---------------------------------------------------------------- output
def report(ev, r, skipped, src):
G, T, seat = r["guests"], r["tables"], r["seat"]
c = {s: 0 for s in SEV}
for f in r["findings"]:
c[f[0]] += 1
hard = [f for f in r["findings"] if f[0] == "high"]
out = ["# Seating chart: %s%s" % (ev["event"], (" (%s)" % ev["date"]) if ev["date"] else ""), "",
"%d attending guest(s) (%d declined; %s), %d seat(s) at %d table(s). Source: %s." % (
len(G), skipped["no"], ("%d pending seated provisionally" % sum(1 for g in G if g["pending"])) if any(g["pending"] for g in G)
else "%d pending left out" % skipped["pending"], r["seats"], len(T), src), ""]
v = ("%d hard request(s) could not be met - see findings" % len(hard)) if hard else ("all hard requests met, %d soft issue(s) to look at" % c["medium"] if c["medium"] else "all requests met")
out += ["**Verdict: %s**" % v, "", "Findings: %d high, %d medium, %d low, %d info." % (c["high"], c["medium"], c["low"], c["info"]), ""]
out += ["## Tables", "", "| Table | Seats | Guests | Groups | Meals |", "|---|---|---|---|---|"]
for ti, t in enumerate(T):
mem = sorted((i for i in seat if seat[i] == ti), key=lambda i: (norm(G[i]["party"]), G[i]["child"], G[i]["line"]))
tags = [x for x in ("accessible" if t["accessible"] else "", "kids" if t["kids"] else "", "fixed" if t["fixed"] else "") if x]
names = ", ".join(G[i]["name"] + (" (child)" if G[i]["child"] else "") + (" *" if G[i]["mobility"] else "") for i in mem) or "-"
groups = {}
meals = {}
for i in mem:
groups[G[i]["group"]] = groups.get(G[i]["group"], 0) + 1
k = G[i]["diet"] + (" (child)" if G[i]["child"] else "")
meals[k] = meals.get(k, 0) + 1
out.append("| %s%s | %d/%d | %s | %s | %s |" % (t["name"], " [%s]" % ", ".join(tags) if tags else "", len(mem), t["seats"], names,
", ".join("%s %d" % kv for kv in sorted(groups.items())) or "-", ", ".join("%s %d" % kv for kv in sorted(meals.items())) or "-"))
out += ["", "`*` = mobility need (seat on the aisle side, nearest the door).", ""]
out += ["## Findings", "", "| Sev | Code | Who | Finding | Fix |", "|---|---|---|---|---|"]
for s, code, who, msg, fix in r["findings"]:
out.append("| %s | %s | %s | %s | %s |" % (s, code, who, msg.replace("|", "\\|"), fix.replace("|", "\\|")))
meals = {}
for i in seat:
k = G[i]["diet"] + (" (child)" if G[i]["child"] else "")
meals[k] = meals.get(k, 0) + 1
out += ["", "## Caterer summary", "", "| Meal | Count |", "|---|---|"]
for k, v_ in sorted(meals.items()):
out.append("| %s | %d |" % (k, v_))
notes = [(G[i]["name"], T[seat[i]]["name"], ", ".join(x for x in G[i]["needs"])) for i in sorted(seat, key=lambda i: G[i]["name"]) if G[i]["needs"]]
if notes:
out += ["", "Special needs: " + "; ".join("%s (%s) - %s" % n for n in notes) + "."]
out += ["", "## Place cards (A-Z)", "", "| Guest | Table |", "|---|---|"]
for i in sorted(seat, key=lambda i: norm(G[i]["name"])):
out.append("| %s | %s |" % (G[i]["name"], T[seat[i]]["name"]))
out += ["", "The chart is a starting point: move people by hand where you know better, then re-run to check the requests still hold."]
return "\n".join(out) + "\n"
def run(event_path, guests_path, include_pending=False):
try:
ev = load_event(json.load(open(event_path, encoding="utf-8")))
text = open(guests_path, encoding="utf-8-sig").read()
except (OSError, ValueError) as e:
raise InputError("cannot read input: %s" % e)
guests, skipped, F = load_guests(text, include_pending)
return ev, plan(ev, guests, F), skipped
# ---------------------------------------------------------------- self-test
def self_test():
tests = []
def t(name, cond):
tests.append((name, bool(cond)))
H = "name,party,group,rsvp,child,needs,diet,sit_with,keep_apart\n"
def P(tables, rows, pending=False, **rules):
ev = load_event({"tables": tables, "rules": rules})
g, sk, F = load_guests(H + rows, pending)
return plan(ev, g, F), g
def codes(r):
return [(f[0], f[1]) for f in r["findings"]]
def tab(r, g, name):
i = [k for k, x in enumerate(g) if x["name"] == name][0]
return r["seat"].get(i)
T2 = [{"name": "A", "seats": 4}, {"name": "B", "seats": 4}]
rows = "Ann,P1,work,yes\nBob,P1,work,yes\nCid,P2,family,yes\nDee,P2,family,yes\nEve,P3,work,yes\nFay,P4,family,yes\n"
r, g = P(T2, rows)
t("parties stay together", tab(r, g, "Ann") == tab(r, g, "Bob") and tab(r, g, "Cid") == tab(r, g, "Dee"))
t("groups fill tables", tab(r, g, "Eve") == tab(r, g, "Ann") and tab(r, g, "Fay") == tab(r, g, "Cid"))
t("clean plan has no high/medium", not [f for f in r["findings"] if f[0] in ("high", "medium")])
r, g = P(T2, "Ann,P1,work,yes,,,,,Bob\nBob,P2,work,yes\nCid,P3,work,yes\nDee,P4,work,yes\n")
t("keep_apart respected", tab(r, g, "Ann") != tab(r, g, "Bob") and ("high", "SC02") not in codes(r))
r, g = P(T2, "Ann,P1,work,yes,,,,Dee\nBob,P2,family,yes\nCid,P3,family,yes\nDee,P4,friends,yes\n")
t("sit_with respected", tab(r, g, "Ann") == tab(r, g, "Dee"))
r, g = P(T2, "Ann,P1,work,yes,,,,Bob,Bob\nBob,P2,work,yes\n")
t("sit_with vs keep_apart conflict -> SC02 high", ("high", "SC02") in codes(r))
r, g = P(T2, "Ann,P1,work,yes,,,,,Bob\nBob,P1,work,yes\n")
t("keep apart inside one party -> SC02", ("high", "SC02") in codes(r))
r, g = P(T2, "Ann,P1,work,yes,,,,Bobb\nBob,P2,work,yes\n")
t("misspelled name -> SC03 with suggestion", any(f[1] == "SC03" and "did you mean Bob" in f[3] for f in r["findings"]))
r, g = P([{"name": "A", "seats": 2}], "Ann,P1,w,yes\nBob,P2,w,yes\nCid,P3,w,yes\n")
t("not enough seats -> SC01 high", ("high", "SC01") in codes(r))
r, g = P(T2, "Ann,P1,w,yes\nAnn,P1,w,yes\nBob,P1,w,yes\n")
t("duplicate -> SC08 and seated once", ("medium", "SC08") in codes(r) and len(g) == 2)
r, g = P(T2, "Ann,P1,w,no\nBob,P2,w,pending\nCid,P3,w,yes\nDee,P3,w,yes\n")
t("declined and pending excluded", len(g) == 2)
r, g = P(T2, "Bob,P2,w,pending\nCid,P3,w,yes\n", pending=True)
t("--include-pending seats pending -> SC07", len(g) == 2 and ("info", "SC07") in codes(r))
r, g = P([{"name": "A", "seats": 4}, {"name": "B", "seats": 4, "accessible": True}], "Ann,P1,w,yes\nBob,P2,x,yes,,wheelchair\n")
t("wheelchair -> accessible table", tab(r, g, "Bob") == 1)
r, g = P([{"name": "A", "seats": 4}, {"name": "B", "seats": 4}], "Ann,P1,w,yes\nBob,P2,x,yes,,wheelchair\n")
t("no accessible table -> SC05", ("medium", "SC05") in codes(r))
r, g = P(T2, "Ann,P1,work,yes\nBob,P1,work,yes\nZed,P9,gym,yes\n")
t("lonely guest -> SC04", ("medium", "SC04") in codes(r))
r, g = P([{"name": "Head", "seats": 4, "fixed": ["Bride", "Groom"]}, {"name": "B", "seats": 4}], "Bride,C,couple,yes\nGroom,C,couple,yes\nBest,Best,groom family,yes,,,,Groom\n")
t("sit_with partner counts as someone they know", ("medium", "SC04") not in codes(r) and tab(r, g, "Best") == 0)
r, g = P([{"name": "A", "seats": 4}, {"name": "B", "seats": 4}, {"name": "C", "seats": 4}],
"A1,a1,fam,yes\nA2,a1,fam,yes\nA3,a1,fam,yes\nW1,w1,work,yes\nB1,b1,fam,yes\nB2,b1,fam,yes\nB3,b1,fam,yes\nW2,w2,work,yes\n")
t("group split by greedy is pulled together", tab(r, g, "W1") == tab(r, g, "W2"))
r, g = P([{"name": "A", "seats": 3}, {"name": "B", "seats": 3}], "A1,Big,w,yes\nA2,Big,w,yes\nA3,Big,w,yes\nA4,Big,w,yes\n")
t("party bigger than a table is split -> SC09", ("medium", "SC09") in codes(r) and len(r["seat"]) == 4)
r, g = P([{"name": "Head", "seats": 2, "fixed": ["Cid"]}, {"name": "B", "seats": 4}], "Ann,P1,w,yes\nBob,P1,w,yes\nCid,P3,w,yes\n")
t("fixed seat honoured", tab(r, g, "Cid") == 0)
r, g = P([{"name": "Head", "seats": 2, "fixed": ["Cyd"]}, {"name": "B", "seats": 4}], "Cid,P3,w,yes\n")
t("fixed seat typo -> SC03", ("high", "SC03") in codes(r))
r, g = P([{"name": "A", "seats": 10}, {"name": "B", "seats": 10}], "Ann,P1,w,yes\nBob,P1,w,yes\n")
t("half-empty and empty tables -> SC06", ("low", "SC06") in codes(r) and ("info", "SC06") in codes(r))
r, g = P([{"name": "A", "seats": 4}, {"name": "Kids", "seats": 4, "kids": True}], "Mum,F,fam,yes\nTim,F,fam,yes,yes\nLia,G,fam,yes,yes\nDad,G,fam,yes\n")
t("children stay with their party by default", tab(r, g, "Tim") == tab(r, g, "Mum"))
r, g = P(T2, "Ann,P1,w,yes,,,vegetarian\nBob,P1,w,yes,,,\n")
t("diet counted", "vegetarian 1" in report({"event": "x", "date": ""}, r, {"no": 0, "pending": 0}, "x"))
r, g = P([{"name": "A", "seats": 2}, {"name": "B", "seats": 2}], "Ann,P1,w,yes,,,,Bob;Cid\nBob,P2,w,yes\nCid,P3,w,yes\n")
t("sit_with group larger than any table -> SC09", ("medium", "SC09") in codes(r))
for bad, name in (({"tables": []}, "no tables"), ({"tables": [{"name": "A", "seats": 0}]}, "zero seats"),
({"tables": [{"name": "A", "seats": 4}, {"name": "A", "seats": 4}]}, "duplicate table"),
({"tables": [{"name": "A", "seats": 4, "colour": "red"}]}, "unknown table key")):
try:
load_event(bad); t("rejected: " + name, False)
except InputError:
t("rejected: " + name, True)
try:
load_guests("first,last\nA,B\n"); t("rejected: no name column", False)
except InputError:
t("rejected: no name column", True)
r, g = P(T2, rows)
rep = report({"event": "x", "date": ""}, r, {"no": 0, "pending": 0}, "x")
t("report has verdict, tables and place cards", "**Verdict:" in rep and "## Tables" in rep and "## Place cards" in rep)
for n, ok in tests:
print("%s %s" % ("PASS" if ok else "FAIL", n))
p = sum(ok for _, ok in tests)
print("%d/%d passed" % (p, len(tests)))
return 0 if p == len(tests) else 1
def main(argv=None):
ap = argparse.ArgumentParser(description="Build a seating chart from tables and a guest list.")
ap.add_argument("event", nargs="?")
ap.add_argument("guests", nargs="?")
ap.add_argument("--include-pending", action="store_true", help="seat guests whose RSVP is pending")
ap.add_argument("--csv", action="store_true", help="print name,table CSV (place cards)")
ap.add_argument("--json", action="store_true")
ap.add_argument("--self-test", action="store_true")
a = ap.parse_args(argv)
if a.self_test:
return self_test()
if not a.event or not a.guests:
ap.error("give EVENT.json and GUESTS.csv")
try:
ev, r, skipped = run(a.event, a.guests, a.include_pending)
except InputError as e:
print("error: %s" % e, file=sys.stderr)
return 2
G, T = r["guests"], r["tables"]
if a.json:
print(json.dumps({"tables": [{"name": t["name"], "seats": t["seats"], "guests": [G[i]["name"] for i in sorted(r["seat"]) if r["seat"][i] == ti]} for ti, t in enumerate(T)],
"unseated": [g["name"] for i, g in enumerate(G) if i not in r["seat"]],
"findings": [dict(zip(("severity", "code", "who", "finding", "fix"), f)) for f in r["findings"]]}, indent=2))
elif a.csv:
w = csv.writer(sys.stdout, lineterminator="\n")
w.writerow(["name", "table", "diet"])
for i in sorted(r["seat"], key=lambda i: norm(G[i]["name"])):
w.writerow([G[i]["name"], T[r["seat"][i]]["name"], G[i]["diet"]])
else:
sys.stdout.write(report(ev, r, skipped, a.guests))
return 1 if any(f[0] == "high" for f in r["findings"]) else 0
if __name__ == "__main__":
sys.exit(main())0
Audits feature flags against your codebase and plans their cleanup - finds release flags 100% on or off for weeks, rollouts stuck at a partial percentage, experiments that never ended, expired, archived and unreferenced flags, keys used in code but missing from the flag service (or misspelled), staging-production drift and flags without an owner. Lists every file:line to change with effort. Includes an offline stdlib Python scanner.
---
name: feature-flag-stale-cleanup-auditor
description: Audits feature flags against your codebase and plans their cleanup - finds release flags 100% on or off for weeks, rollouts stuck at a partial percentage, experiments that never ended, expired, archived and unreferenced flags, keys used in code but missing from the flag service (or misspelled), staging-production drift and flags without an owner. Lists every file:line to change with effort. Includes an offline stdlib Python scanner.
---
# Feature Flag Stale Cleanup Auditor
You help engineering teams pay down feature flag debt. Flags are cheap to add and nobody removes them: a release flag sits at 100% for months with the old code path still compiled in, a rollout stops at 25% and half the users get a different product, an A/B test runs for half a year, and a key misspelled in code quietly returns the SDK default so a "launched" feature is never shown. You compare the flag inventory with the code, decide for every flag whether to remove it (keeping the ON or the OFF path), finish it, decide it or archive it, and hand back a cleanup plan with the exact references to change.
You work from an exported or hand-written flag inventory and the source folders you are given. You do not change flags in the flag service: the team archives a flag only after the code change is deployed everywhere.
## Files in this skill
- `scripts/flag_audit.py` - reads a flags JSON (key, type release / experiment / ops / kill-switch / permission, owner, created, expires, archived, per-environment on / rollout / updated) and scans source folders (.ts .tsx .js .jsx .py .go .rb .java .kt .cs .php .swift .vue .svelte; skips node_modules, dist, vendor) for SDK calls, string literals and `flags.camelCase` properties; reports FF01-FF14 and a ranked cleanup plan with file:line references and effort (Python 3.8+ standard library only)
- `references/flag-lifecycle-and-removal.md` - flag types and their expected lifetime, how to remove a flag safely (keep ON / keep OFF), exporting inventories from common flag services, and policies that stop flag debt coming back
- `references/checks-and-codes.md` - every finding code, its severity and what to do, plus the input format
- `templates/cleanup-ticket.md` - the cleanup ticket / PR description for each flag
- `examples/flags.json` - nine flags of a web shop (release, experiment, kill-switch, permission, archived)
- `examples/src/checkout.ts`, `examples/src/Header.tsx`, `examples/src/search.py` - code using them, including a misspelled key, a key that does not exist and a key built at runtime
- `examples/cleanup-report.md` - the real scanner output on the example
## Workflow
### 1. Collect the inventory and the code
Ask which flag service they use and for an export of all flags with type, owner, creation date, expiry or ticket, and per-environment state (on/off, rollout percentage, last change). Map it into a JSON like `examples/flags.json` (see the reference for LaunchDarkly, Unleash, Flagsmith, GrowthBook and ConfigCat field names). Ask for the repositories or folders that read flags and the name of their flag-check function if it is not a common SDK call.
### 2. Run the scanner
```
python3 scripts/flag_audit.py examples/flags.json examples/src
python3 scripts/flag_audit.py flags.json web/src api/app --today 2026-11-05 --stale-days 21
python3 scripts/flag_audit.py flags.json src --call featureOn --call can
python3 scripts/flag_audit.py flags.json src --json
python3 scripts/flag_audit.py --self-test
```
Exit 0 = no high findings, 1 = high findings, 2 = bad input. Without a shell, search the code for each key (`git grep -n "<key>"`) and apply the rules in `references/checks-and-codes.md` by hand.
### 3. Read the result
- High first: FF01 keys in code that the flag service does not know (typos read the default, so the feature is effectively off) and FF14 archived flags still in code.
- Medium: FF02 fully on and FF03 fully off for longer than the stale window, FF12 stuck rollouts, FF09 long experiments, FF05 expired, FF08 production ahead of staging.
- Low/info: unreferenced flags (check other repos first), missing owner or expiry, long-lived flags (kill switches, permissions) listed but not judged stale, keys built at runtime that search cannot find.
### 4. Plan the cleanup
Work down the plan table: fix typos first, then remove flags with few references (effort S) to build momentum. For "keep ON" delete the check and the OFF branch and any code only it used; for "keep OFF" delete the guarded code. Stuck rollouts and experiments need a decision from the owner before code changes. Fill `templates/cleanup-ticket.md` per flag.
### 5. Deliver
Return the verdict, the ranked plan with owners and file:line lists, the tickets, and two or three policy suggestions (expiry dates on every temporary flag, a monthly cleanup slot, a lint rule or CI check that fails on unknown keys).
## Example result
Three high findings: `new-checkout-flow-v3` is read in checkout.ts but does not exist, `recs_carousel` in search.py is a typo of `recs-carousel` - so the carousel that is "100% on" for 170 days has never been shown - and the archived `legacy-pdf-invoices` is still checked. `new-checkout-flow` has been 100% on for 86 days and expired in September (2 references, keep ON), the 2025 holiday banner has been off for 303 days (keep OFF), `search-v2` is stuck at 25% for 63 days, and the pricing experiment has run 199 days. `dark-mode` is on in production but off in staging. Kill switch and permission flags are kept.
## Rules
- Never recommend removing a kill switch, ops or permission flag because it is old; they are long-lived by design.
- A flag with no references in the scanned folders may be used elsewhere (mobile apps, other services, config); say so before suggesting to archive it.
- Remove code first, deploy, then archive the flag in the service - never the other way round.
- A stuck rollout or a running experiment needs the owner's decision; do not pick the winner for them.
- Treat `today` and the stale window as inputs; say which values you used.
FILE:references/flag-lifecycle-and-removal.md
# Flag lifecycle and safe removal
## Flag types and expected lifetime
| Type | Purpose | Expected life | Done when |
|---|---|---|---|
| release | hide unfinished work, roll out gradually | days to a few weeks after 100% | 100% everywhere and stable for the stale window |
| experiment | A/B or multivariate test | the test duration (2-6 weeks typical) | a decision is made |
| ops | operational switch (cache on/off, batch size) | long | rarely; review yearly |
| kill-switch | turn off a risky dependency fast | permanent | never by age |
| permission | entitlement, beta access, plan feature | permanent (or move to the billing/entitlement system) | product decision |
## Removing a flag safely
1. Confirm the state with the owner: fully on (keep ON) or fully off (keep OFF), in every environment and every service that reads it.
2. Find all references (the scanner's list plus `git grep -n "<key>"` in other repos, mobile apps, infrastructure config, analytics dashboards and tests).
3. Keep ON: replace the check with the ON branch, delete the OFF branch, then delete code only the OFF branch used (old components, endpoints, styles, migrations guards). Keep OFF: delete the guarded code and anything only it used.
4. Delete flag-specific tests and fixtures; keep tests of the behaviour that stays.
5. Deploy to every environment. Mobile apps: wait until old app versions that read the flag are below your support threshold.
6. Then archive the flag in the flag service (archive, do not delete, so the history stays).
7. Close the ticket with the PR links.
## Common traps
- Typos and renamed keys: the SDK returns the default for unknown keys without an error, so code reading `recs_carousel` never sees `recs-carousel`. A CI check that compares literal keys with the inventory catches this.
- Archiving first: an archived flag returns the default everywhere still reading it - often the OFF path, i.e. an instant rollback of a launched feature.
- Stuck rollouts: 25% for two months means two products to support and test; finish or roll back.
- Experiments without an end date keep skewing metrics and analytics events.
- Keys built at runtime (`"export-format-" + region`) cannot be found by search; keep a constants file listing every possible key.
## Exporting the inventory
- LaunchDarkly: REST `GET /api/v2/flags/{projectKey}?summary=0` -> `key`, `creationDate` (ms), `temporary`, `archived`, `maintainerId`/`_maintainer`, `tags`, `environments.<env>.on`, `.lastModified`, rollout weights in `fallthrough.rollout.variations` (weight/1000 = percent). Map `temporary: false` to `permanent: true`.
- Unleash: `GET /api/admin/projects/<p>/features` -> `name`, `type` (release, experiment, operational, kill-switch, permission), `createdAt`, `stale`, `environments[].enabled`, gradual rollout strategy `parameters.rollout`.
- Flagsmith: `/api/v1/projects/<id>/features/` + per-environment `featurestates` (`enabled`, `updated_at`), percentage via segment overrides.
- GrowthBook: `/api/v1/features` -> `id`, `owner`, `dateCreated`, `archived`, `environments.<env>.enabled`, rollout rule `coverage` (0-1 -> percent).
- ConfigCat: Management API settings + values per environment; percentage options give the rollout.
- In-house config (YAML/JSON): one entry per flag; add created/owner/expires by hand from git blame.
## Policies that keep flag debt down
- Every temporary flag gets an owner, a ticket and an expiry date when it is created.
- Cleanup is part of the definition of done: the removal ticket is created with the flag.
- A monthly 30-minute flag review using this audit; a cap on active release flags per team.
- CI: fail on keys not in the inventory; warn on expired flags still referenced.
FILE:references/checks-and-codes.md
# Checks and finding codes
| Code | Severity | Check | What to do |
|---|---|---|---|
| FF01 | high | a flag-check call (isEnabled, variation, useFlag, is_enabled ...) uses a key that is not in the inventory; a close match is suggested (typo, `_` vs `-`) | fix the key or create the flag; until then the SDK returns the default value |
| FF02 | medium | release flag at 100% in the primary environment for `stale_days` or more | remove the flag, keep the ON path |
| FF03 | medium | release or experiment flag off / 0% in the primary environment for `stale_days` or more | remove the flag and the guarded code, or decide to launch |
| FF04 | low | no reference in the scanned files | check other repos and services; archive if unused |
| FF05 | medium | `expires` date passed (temporary flags) | remove or agree a new date |
| FF06 | info | ops, kill-switch, permission (or `permanent: true`) flag - not judged stale | review yearly |
| FF07 | low | no owner | assign one |
| FF08 | medium | primary environment ahead of staging/qa/test/dev, or no state for the primary environment | align environments |
| FF09 | medium | experiment older than `experiment_max_days` | decide, ship the winner, remove |
| FF10 | info | flag key built at runtime (variable, concatenation, template string) | use literal keys or a constants file |
| FF11 | low | temporary flag without `expires` | set an expiry |
| FF12 | medium | release rollout between 1 and 99% unchanged for `stale_days` | finish (100%) or roll back, then remove |
| FF13 | medium | key defined twice in the inventory | merge |
| FF14 | high | flag archived in the service but still referenced in code | remove the references |
## Verdict
- **N high finding(s)** when FF01/FF14 exist; else **N flag(s) ready to remove**; else **no stale flags**.
## Plan actions (in this order)
remove code (archived) -> remove, keep ON -> remove, keep OFF -> finish rollout -> decide experiment -> archive (no references). Within an action, flags with more references first. Effort: S 1-2 references, M 3-6, L 7+.
## How references are found
1. Calls: `<name>(` with a literal first argument (or a literal after one leading argument such as a client or user), for the built-in names plus `call_names` / `--call`.
2. Any string literal equal to a known key (constants files, config maps).
3. `flags.`, `features.`, `featureFlags.`, `toggles.` followed by the key or its camelCase form (`new-search` -> `flags.newSearch`).
Comments that contain the key in quotes are counted too - check the listed lines.
## Flags JSON
Top level: `today, primary_env (production), environments, stale_days (30), experiment_max_days (90), call_names[], flags[]`.
Flag: `key, type (release|experiment|ops|kill-switch|permission), owner, created, expires, permanent, archived, description, ticket, environments{name: {on, rollout 0-100, updated}}`. `rollout` defaults to 100 when on and 0 when off; `updated` is the last change of that environment (falls back to `created`).
FILE:templates/cleanup-ticket.md
# Remove feature flag `<key>`
**Owner:** <team-payments> **Type:** <release> **Ticket:** <PAY-412> **Action:** <remove, keep ON>
**State:** <100% on in production since 2026-08-11 (86 days), 100% in staging> **Expired:** <2026-09-30>
## Why
<Fully rolled out and stable for 86 days; the OFF path (legacy checkout) is dead code.>
## Change
- [ ] `<examples/src/checkout.ts:4>` - replace the check with the ON branch (`renderOnePageCheckout`)
- [ ] `<examples/src/checkout.ts:14>` - always use `oneClickButton()`
- [ ] delete code only the OFF path used: <renderLegacyCheckout, classicButton, legacy checkout styles>
- [ ] delete flag-specific tests and fixtures
- [ ] search other repos / mobile apps: `git grep -n "<key>"`
## Rollout
1. Merge and deploy to staging, then production.
2. Watch <checkout conversion, error rate> for <2 days>.
3. Archive `<key>` in <flag service> (archive, not delete).
## Risks / questions
- <Does the mobile app read this flag? Minimum supported version?>
- <Any dashboards or alerts keyed on the flag?>
FILE:examples/flags.json
{
"today": "2026-11-05",
"primary_env": "production",
"stale_days": 30,
"experiment_max_days": 90,
"flags": [
{"key": "new-checkout-flow", "type": "release", "owner": "team-payments", "created": "2026-06-02", "expires": "2026-09-30", "ticket": "PAY-412",
"description": "New one-page checkout",
"environments": {"production": {"on": true, "rollout": 100, "updated": "2026-08-11"}, "staging": {"on": true, "rollout": 100, "updated": "2026-07-20"}}},
{"key": "search-v2", "type": "release", "owner": "team-search", "created": "2026-07-15", "expires": "2026-12-31",
"description": "Typesense-backed search",
"environments": {"production": {"on": true, "rollout": 25, "updated": "2026-09-03"}, "staging": {"on": true, "rollout": 100, "updated": "2026-08-01"}}},
{"key": "holiday-banner-2025", "type": "release", "owner": "team-growth", "created": "2025-11-10", "expires": "2026-01-10",
"description": "Christmas 2025 promo banner",
"environments": {"production": {"on": false, "rollout": 0, "updated": "2026-01-06"}, "staging": {"on": false, "rollout": 0, "updated": "2026-01-06"}}},
{"key": "pricing-page-test", "type": "experiment", "owner": "team-growth", "created": "2026-04-20", "expires": "2026-07-01",
"description": "A/B test: annual plan first",
"environments": {"production": {"on": true, "rollout": 50, "updated": "2026-04-22"}, "staging": {"on": true, "rollout": 50, "updated": "2026-04-22"}}},
{"key": "dark-mode", "type": "release", "owner": "team-web", "created": "2026-10-01", "expires": "2026-12-15",
"description": "Dark theme",
"environments": {"production": {"on": true, "rollout": 100, "updated": "2026-10-28"}, "staging": {"on": false, "rollout": 0, "updated": "2026-10-02"}}},
{"key": "payments-kill-switch", "type": "kill-switch", "owner": "team-payments", "created": "2025-03-01",
"description": "Turn off card payments during a PSP outage",
"environments": {"production": {"on": true, "rollout": 100, "updated": "2025-03-01"}, "staging": {"on": true, "rollout": 100, "updated": "2025-03-01"}}},
{"key": "beta-reports-export", "type": "permission", "owner": "", "created": "2025-09-12",
"description": "CSV export for beta customers",
"environments": {"production": {"on": true, "rollout": 100, "updated": "2025-09-12"}}},
{"key": "legacy-pdf-invoices", "type": "release", "owner": "team-billing", "created": "2025-05-01", "archived": true,
"description": "Old PDF renderer",
"environments": {"production": {"on": false, "rollout": 0, "updated": "2026-02-01"}}},
{"key": "recs-carousel", "type": "release", "owner": "team-growth", "created": "2026-03-03",
"description": "Recommendations carousel on product pages",
"environments": {"production": {"on": true, "rollout": 100, "updated": "2026-05-19"}, "staging": {"on": true, "rollout": 100, "updated": "2026-05-01"}}}
]
}
FILE:examples/src/checkout.ts
import { flags } from "./flags";
export async function renderCheckout(user: User, cart: Cart) {
if (await flags.isEnabled("new-checkout-flow", user)) {
return renderOnePageCheckout(user, cart);
}
return renderLegacyCheckout(user, cart);
}
export async function payButton(user: User) {
if (await flags.isEnabled("payments-kill-switch", user)) {
return disabledButton("Card payments are paused. Please try again shortly.");
}
const oneClick = await flags.isEnabled("new-checkout-flow", user);
return oneClick ? oneClickButton() : classicButton();
}
export async function invoiceLink(order: Order) {
// TODO remove after PDF migration
if (await flags.isEnabled("legacy-pdf-invoices")) {
return legacyPdfUrl(order.id);
}
return invoiceServiceUrl(order.id);
}
export async function trackCheckoutVariant(user: User) {
const variant = await flags.variation("new-checkout-flow-v3", user, "control");
analytics.track("checkout_variant", { variant });
}
FILE:examples/src/Header.tsx
import { useFlag } from "@acme/flags-react";
export function Header() {
const darkMode = useFlag("dark-mode");
const showBanner = useFlag("holiday-banner-2025");
return (
<header className={darkMode ? "header header--dark" : "header"}>
{showBanner && <PromoBanner text="Holiday sale: 20% off everything" />}
<SearchBox />
</header>
);
}
export function PricingPage({ user }: { user: User }) {
const annualFirst = useFlag("pricing-page-test");
return annualFirst ? <PlansAnnualFirst /> : <PlansMonthlyFirst />;
}
FILE:examples/src/search.py
from app.flags import flags
def search(query, user):
if flags.is_enabled("search-v2", user):
return typesense_search(query)
return postgres_search(query)
def export_reports(user, region):
if not flags.is_enabled("beta-reports-export", user):
raise PermissionError("export is in beta")
# per-region experiment keys, e.g. "export-format-eu"
if flags.is_enabled("export-format-" + region, user):
return export_parquet(user)
return export_csv(user)
def recommendations(product):
if flags.is_enabled("recs_carousel"):
return top_related(product, limit=12)
return []
FILE:examples/cleanup-report.md
# Feature flag cleanup audit
Today 2026-11-05, primary environment `production`, stale after 30 days. 9 flag(s) in the inventory, 3 source file(s) scanned in examples/src.
**Verdict: 3 high finding(s) - flags used in code that the flag service does not know**
Cleanup candidates: 6 (4 removable now, 4 reference(s) to change). Findings: 3 high, 9 medium, 2 low, 3 info.
## Cleanup plan
| # | Flag | Type | Owner | Primary | Action | Why | Refs (files) | Effort | Where |
|---|---|---|---|---|---|---|---|---|---|
| 1 | `legacy-pdf-invoices` | release | team-billing | archived | **remove code** | archived but still in code | 1 (1) | S | `examples/src/checkout.ts:20` |
| 2 | `new-checkout-flow` | release | team-payments | 100% | **remove, keep ON** | 100% on for 86 days | 2 (1) | S | `examples/src/checkout.ts:4`, `examples/src/checkout.ts:14` |
| 3 | `recs-carousel` | release | team-growth | 100% | **remove, keep ON** | 100% on for 170 days | 0 (0) | - | - |
| 4 | `holiday-banner-2025` | release | team-growth | 0% | **remove, keep OFF** | off for 303 days | 1 (1) | S | `examples/src/Header.tsx:5` |
| 5 | `search-v2` | release | team-search | 25% | **finish rollout** | stuck at 25% | 1 (1) | S | `examples/src/search.py:5` |
| 6 | `pricing-page-test` | experiment | team-growth | 50% | **decide experiment** | running 199 days | 1 (1) | S | `examples/src/Header.tsx:15` |
Effort: S = 1-2 references, M = 3-6, L = 7 or more. "keep ON" = delete the flag check and the OFF branch; "keep OFF" = delete the guarded code. Archive the flag in the flag service only after the code change is deployed everywhere.
## Findings
| Sev | Code | Flag | Finding | Fix |
|---|---|---|---|---|
| high | FF01 | `new-checkout-flow-v3` | used in code (examples/src/checkout.ts:27) but not defined in the flag inventory - the SDK returns the default, so this code path is reading the wrong key | typo of new-checkout-flow? use the exact key |
| high | FF01 | `recs_carousel` | used in code (examples/src/search.py:20) but not defined in the flag inventory - the SDK returns the default, so this code path is reading the wrong key | typo of recs-carousel? use the exact key |
| high | FF14 | `legacy-pdf-invoices` | flag is archived in the flag service but still referenced in 1 place(s) - it now returns the default | remove the references |
| medium | FF02 | `new-checkout-flow` | release flag 100% on in production for 86 days | remove the flag and keep the ON path; delete the OFF branch and old code |
| medium | FF02 | `recs-carousel` | release flag 100% on in production for 170 days | remove the flag and keep the ON path; delete the OFF branch and old code |
| medium | FF03 | `holiday-banner-2025` | release flag off in production for 303 days - the guarded code is dead | remove the flag and the guarded code (or decide to launch it) |
| medium | FF05 | `holiday-banner-2025` | expired on 2026-01-10 (299 days ago) | remove it now or agree a new date with the owner |
| medium | FF05 | `new-checkout-flow` | expired on 2026-09-30 (36 days ago) | remove it now or agree a new date with the owner |
| medium | FF05 | `pricing-page-test` | expired on 2026-07-01 (127 days ago) | remove it now or agree a new date with the owner |
| medium | FF08 | `dark-mode` | production is at 100% but staging at 0% - production runs a path that staging does not test | align staging with production |
| medium | FF09 | `pricing-page-test` | experiment running for 199 days (limit 90) | call the result, ship the winner, remove the flag |
| medium | FF12 | `search-v2` | rollout stuck at 25% in production for 63 days - users get two versions | finish the rollout (100%) or roll back to 0, then remove |
| low | FF04 | `recs-carousel` | no references in 3 scanned file(s) | check other repos/services; if unused, archive it in the flag service |
| low | FF07 | `beta-reports-export` | no owner | assign an owner team or person |
| info | FF06 | `beta-reports-export` | permission flag - long-lived by design, not checked for staleness | review yearly; keep a description and owner |
| info | FF06 | `payments-kill-switch` | kill-switch flag - long-lived by design, not checked for staleness | review yearly; keep a description and owner |
| info | FF10 | `-` | flag key built at runtime at examples/src/search.py:14 - references to it cannot be found by search | prefer literal keys (or a constants file) so flags can be cleaned up |
## References per flag
| Flag | References |
|---|---|
| `beta-reports-export` | 1 |
| `dark-mode` | 1 |
| `holiday-banner-2025` | 1 |
| `legacy-pdf-invoices` | 1 |
| `new-checkout-flow` | 2 |
| `payments-kill-switch` | 1 |
| `pricing-page-test` | 1 |
| `recs-carousel` | 0 |
| `search-v2` | 1 |
Search covers string literals, common SDK calls and `flags.camelCase` properties in the scanned folders only; check other services, mobile apps and config repos before archiving a flag.
FILE:scripts/flag_audit.py
#!/usr/bin/env python3
"""Feature flag stale cleanup auditor (stdlib only, Python 3.8+).
Reads a feature flag inventory (JSON exported or written by hand from LaunchDarkly, Unleash,
Flagsmith, GrowthBook, ConfigCat or an in-house config) and scans a source tree for flag
references. Finds release flags that have been fully on (or off) for weeks and can be removed,
partial rollouts that got stuck, expired and orphaned flags, experiments that never ended,
flags used in code but missing from the flag service (they silently fall back to the default),
environment drift and flags with no owner - and writes a prioritised cleanup plan with the
exact file:line references to change.
Usage:
flag_audit.py FLAGS.json SRC_DIR [SRC_DIR ...] [--today YYYY-MM-DD] [--stale-days N]
[--call NAME ...] [--json]
flag_audit.py --self-test
Exit: 0 = no high findings, 1 = at least one high finding, 2 = bad input.
"""
import argparse, datetime, difflib, json, os, re, sys
SEV = {"high": 0, "medium": 1, "low": 2, "info": 3}
TYPES = {"release", "experiment", "ops", "kill-switch", "permission"}
LONG_LIVED = {"ops", "kill-switch", "permission"}
EXTS = {".ts", ".tsx", ".js", ".jsx", ".mjs", ".cjs", ".py", ".go", ".rb", ".java", ".kt", ".cs", ".php", ".swift", ".vue", ".svelte"}
SKIP_DIRS = {"node_modules", ".git", "dist", "build", "vendor", "__pycache__", ".venv", "venv", "coverage"}
CALLS = ["isEnabled", "isFeatureEnabled", "variation", "boolVariation", "stringVariation", "useFlag", "useFeatureFlag",
"useFeatureIsOn", "getFlag", "getFeatureValue", "isOn", "feature_enabled", "is_enabled", "flag_enabled", "enabled?",
"Enabled", "IsEnabled", "getBooleanValue", "hasFeature"]
TOP_KEYS = {"today", "stale_days", "experiment_max_days", "primary_env", "environments", "flags", "call_names", "source"}
FLAG_KEYS = {"key", "type", "owner", "created", "expires", "permanent", "description", "environments", "archived", "ticket"}
class InputError(Exception):
pass
def pdate(s, what):
try:
return datetime.date.fromisoformat(str(s).strip()[:10])
except ValueError:
raise InputError("%s must be YYYY-MM-DD, got %r" % (what, s))
def camel(k):
parts = re.split(r"[-_.]", k)
return parts[0] + "".join(p[:1].upper() + p[1:] for p in parts[1:])
# ---------------------------------------------------------------- load
def load_flags(cfg, today=None, stale_days=None):
if not isinstance(cfg, dict) or not isinstance(cfg.get("flags"), list):
raise InputError("flags file must be a JSON object with a \"flags\" list")
bad = set(cfg) - TOP_KEYS
if bad:
raise InputError("unknown top-level key(s): %s" % ", ".join(sorted(bad)))
c = {"today": pdate(today or cfg.get("today") or datetime.date.today().isoformat(), "today"),
"stale": int(stale_days if stale_days is not None else cfg.get("stale_days", 30)),
"exp_max": int(cfg.get("experiment_max_days", 90)),
"primary": cfg.get("primary_env", "production"),
"envs": cfg.get("environments") or [], "flags": {}, "dups": [], "calls": cfg.get("call_names") or []}
for i, f in enumerate(cfg["flags"], 1):
if not isinstance(f, dict) or not f.get("key"):
raise InputError("flag #%d has no key" % i)
badk = set(f) - FLAG_KEYS
if badk:
raise InputError("flag %s: unknown key(s) %s" % (f["key"], ", ".join(sorted(badk))))
t = (f.get("type") or "release").lower()
if t not in TYPES:
raise InputError("flag %s: type must be one of %s, got %r" % (f["key"], ", ".join(sorted(TYPES)), t))
envs = {}
for e, st in (f.get("environments") or {}).items():
if not isinstance(st, dict):
raise InputError("flag %s env %s must be an object {on, rollout, updated}" % (f["key"], e))
r = st.get("rollout", 100 if st.get("on") else 0)
if not isinstance(r, (int, float)) or not 0 <= r <= 100:
raise InputError("flag %s env %s: rollout must be 0-100, got %r" % (f["key"], e, r))
envs[e] = {"on": bool(st.get("on")), "rollout": float(r),
"updated": pdate(st["updated"], "flag %s env %s updated" % (f["key"], e)) if st.get("updated") else None}
fl = {"key": f["key"], "type": t, "owner": f.get("owner") or "", "ticket": f.get("ticket", ""),
"created": pdate(f["created"], "flag %s created" % f["key"]) if f.get("created") else None,
"expires": pdate(f["expires"], "flag %s expires" % f["key"]) if f.get("expires") else None,
"permanent": bool(f.get("permanent")) or t in LONG_LIVED, "archived": bool(f.get("archived")),
"description": f.get("description", ""), "envs": envs}
if fl["key"] in c["flags"]:
c["dups"].append(fl["key"])
c["flags"][fl["key"]] = fl
return c
def eff(st):
"""effective share of users getting the flag: 0-100"""
return st["rollout"] if st["on"] else 0.0
# ---------------------------------------------------------------- scan
def scan(dirs, keys, calls):
"""Return refs {key: [(path, line, text)]}, unknown {literal: [(path,line)]}, dynamic [(path,line,text)], files"""
calls = sorted(set(CALLS + list(calls)), key=len, reverse=True)
alt = "|".join(re.escape(c) for c in calls)
call_re = re.compile(r"(?:\b|\.)(%s)\s*\(\s*(?:\w+\s*,\s*)?([\"'`])([^\"'`$]+)\2\s*[,)]" % alt)
dyn_re = re.compile(r"(?:\b|\.)(%s)\s*\(\s*(?![\"'`][^\"'`$]*[\"'`]\s*[,)])([^,)]+)[,)]" % alt)
lit_re = re.compile(r"([\"'`])([A-Za-z0-9][A-Za-z0-9_.:-]{2,80})\1")
camels = {camel(k): k for k in keys if camel(k) != k}
prop_re = re.compile(r"\b(?:flags|features|featureFlags|toggles)\.([A-Za-z_]\w*)")
refs, unknown, dynamic, nfiles = {k: [] for k in keys}, {}, [], 0
for d in dirs:
if not os.path.isdir(d):
raise InputError("source directory not found: %s" % d)
for root, ds, fs in os.walk(d):
ds[:] = sorted(x for x in ds if x not in SKIP_DIRS)
for fn in sorted(fs):
if os.path.splitext(fn)[1] not in EXTS:
continue
p = os.path.join(root, fn)
nfiles += 1
try:
lines = open(p, encoding="utf-8", errors="replace").read().splitlines()
except OSError as e:
raise InputError("cannot read %s: %s" % (p, e))
for i, ln in enumerate(lines, 1):
seen = set()
for m in call_re.finditer(ln):
lit = m.group(3)
if lit in refs:
refs[lit].append((p, i, ln.strip())); seen.add(lit)
else:
unknown.setdefault(lit, []).append((p, i, ln.strip()))
seen.add(lit)
for m in dyn_re.finditer(ln):
if m.group(2).strip() not in ("true", "false", "None", "null", ""):
dynamic.append((p, i, ln.strip()))
for m in lit_re.finditer(ln):
lit = m.group(2)
if lit in refs and lit not in seen:
refs[lit].append((p, i, ln.strip())); seen.add(lit)
for m in prop_re.finditer(ln):
k = camels.get(m.group(1)) or (m.group(1) if m.group(1) in refs else None)
if k and k not in seen:
refs[k].append((p, i, ln.strip())); seen.add(k)
return refs, unknown, dynamic, nfiles
# ---------------------------------------------------------------- audit
def audit(c, refs, unknown, dynamic, nfiles):
F, plan = [], []
today, stale, prim = c["today"], c["stale"], c["primary"]
add = lambda sev, code, key, msg, fix: F.append((sev, code, key, msg, fix))
for k in c["dups"]:
add("medium", "FF13", k, "flag defined twice in the inventory (the last one is used)", "merge the two entries")
keys = list(c["flags"])
norm = {re.sub(r"[-_.]", "", k.lower()): k for k in keys}
for lit, where in sorted(unknown.items()):
close = norm.get(re.sub(r"[-_.]", "", lit.lower())) or (difflib.get_close_matches(lit, keys, 1, 0.8) or [None])[0]
locs = ", ".join("%s:%d" % (p, i) for p, i, _ in where[:3])
add("high", "FF01", lit, "used in code (%s) but not defined in the flag inventory - the SDK returns the default, so this code path is %s" %
(locs, "probably never on" if not close else "reading the wrong key"),
("typo of %s? use the exact key" % close) if close else "create the flag or remove the check")
for p, i, txt in dynamic[:20]:
add("info", "FF10", "-", "flag key built at runtime at %s:%d - references to it cannot be found by search" % (p, i), "prefer literal keys (or a constants file) so flags can be cleaned up")
for k, f in c["flags"].items():
r = refs.get(k, [])
files = sorted(set(p for p, _, _ in r))
st = f["envs"].get(prim)
age = (today - f["created"]).days if f["created"] else None
action, why = None, ""
if not f["owner"]:
add("low", "FF07", k, "no owner", "assign an owner team or person")
if f["archived"]:
if r:
add("high", "FF14", k, "flag is archived in the flag service but still referenced in %d place(s) - it now returns the default" % len(r), "remove the references")
plan.append({"key": k, "type": f["type"], "owner": f["owner"] or "?", "state": "archived", "action": "remove code",
"why": "archived but still in code", "refs": len(r), "files": len(files),
"locs": ["%s:%d" % (p, i) for p, i, _ in r], "ticket": f["ticket"]})
continue
if st is None and not f["archived"]:
add("medium", "FF08", k, "no state for the primary environment %r" % prim, "add the %s state or fix primary_env" % prim)
if f["permanent"]:
add("info", "FF06", k, "%s flag - long-lived by design, not checked for staleness" % f["type"], "review yearly; keep a description and owner")
if not r:
add("low", "FF04", k, "no references in %d scanned file(s)" % nfiles, "check other repos/services; if unused, archive it in the flag service")
action, why = action or "archive", "no references"
elif st is not None:
since = st["updated"] or f["created"]
days = (today - since).days if since else None
e = eff(st)
all_on = all(eff(s) == 100 for s in f["envs"].values())
if f["expires"] and f["expires"] < today:
add("medium", "FF05", k, "expired on %s (%d days ago)" % (f["expires"], (today - f["expires"]).days), "remove it now or agree a new date with the owner")
if f["type"] == "release" and e == 100 and days is not None and days >= stale:
add("medium", "FF02", k, "release flag 100%% on in %s for %d days%s" % (prim, days, "" if all_on else " (not 100% in every environment)"),
"remove the flag and keep the ON path; delete the OFF branch and old code")
action, why = "remove, keep ON", "100%% on for %d days" % days
elif e == 0 and days is not None and days >= stale and f["type"] in ("release", "experiment"):
add("medium", "FF03", k, "%s flag off in %s for %d days - the guarded code is dead" % (f["type"], prim, days),
"remove the flag and the guarded code (or decide to launch it)")
action, why = "remove, keep OFF", "off for %d days" % days
elif 0 < e < 100 and days is not None and days >= stale and f["type"] == "release":
add("medium", "FF12", k, "rollout stuck at %g%% in %s for %d days - users get two versions" % (e, prim, days), "finish the rollout (100%) or roll back to 0, then remove")
action, why = "finish rollout", "stuck at %g%%" % e
if f["type"] == "experiment" and age is not None and age > c["exp_max"]:
add("medium", "FF09", k, "experiment running for %d days (limit %d)" % (age, c["exp_max"]), "call the result, ship the winner, remove the flag")
action, why = action or "decide experiment", "running %d days" % age
if not r:
add("low", "FF04", k, "no references in %d scanned file(s)" % nfiles, "check other repos/services; if unused, archive it in the flag service")
action, why = action or "archive", why or "no references"
for en, s2 in f["envs"].items():
if en != prim and eff(s2) < e and (en in ("staging", "qa", "test", "dev", "development")):
add("medium", "FF08", k, "%s is at %g%% but %s at %g%% - production runs a path that staging does not test" % (prim, e, en, eff(s2)), "align %s with %s" % (en, prim))
if f["expires"] is None and f["type"] in ("release", "experiment") and action is None:
add("low", "FF11", k, "temporary %s flag without an expiry date" % f["type"], "set expires (e.g. 30-60 days after full rollout)")
if action:
plan.append({"key": k, "type": f["type"], "owner": f["owner"] or "?", "state": ("%g%%" % eff(st)) if st else "-", "action": action, "why": why,
"refs": len(r), "files": len(files), "locs": ["%s:%d" % (p, i) for p, i, _ in r], "ticket": f["ticket"]})
rank = {"remove code": 0, "remove, keep ON": 1, "remove, keep OFF": 2, "finish rollout": 3, "decide experiment": 4, "archive": 5}
plan.sort(key=lambda x: (rank[x["action"]], -x["refs"], x["key"]))
F.sort(key=lambda x: (SEV[x[0]], x[1], x[2]))
return {"today": today.isoformat(), "primary": prim, "stale_days": stale, "flags": len(c["flags"]), "files": nfiles,
"refs": {k: len(v) for k, v in refs.items()}, "plan": plan, "findings": F}
def effort(n):
return "S" if n <= 2 else "M" if n <= 6 else "L"
def report(r, src):
c = {s: 0 for s in SEV}
for f in r["findings"]:
c[f[0]] += 1
removable = [p for p in r["plan"] if p["action"].startswith("remove")]
out = ["# Feature flag cleanup audit", "",
"Today %s, primary environment `%s`, stale after %d days. %d flag(s) in the inventory, %d source file(s) scanned in %s." % (
r["today"], r["primary"], r["stale_days"], r["flags"], r["files"], ", ".join(src)), ""]
if c["high"]:
v = "%d high finding(s) - flags used in code that the flag service does not know" % c["high"]
elif removable:
v = "%d flag(s) ready to remove" % len(removable)
else:
v = "no stale flags"
out += ["**Verdict: %s**" % v, "", "Cleanup candidates: %d (%d removable now, %d reference(s) to change). Findings: %d high, %d medium, %d low, %d info." % (
len(r["plan"]), len(removable), sum(p["refs"] for p in removable), c["high"], c["medium"], c["low"], c["info"]), ""]
out += ["## Cleanup plan", "", "| # | Flag | Type | Owner | Primary | Action | Why | Refs (files) | Effort | Where |", "|---|---|---|---|---|---|---|---|---|---|"]
for i, p in enumerate(r["plan"], 1):
locs = ", ".join("`%s`" % x for x in p["locs"][:4]) + (" +%d more" % (len(p["locs"]) - 4) if len(p["locs"]) > 4 else "")
out.append("| %d | `%s` | %s | %s | %s | **%s** | %s | %d (%d) | %s | %s |" % (i, p["key"], p["type"], p["owner"], p["state"], p["action"], p["why"],
p["refs"], p["files"], effort(p["refs"]) if p["refs"] else "-", locs or "-"))
out += ["", "Effort: S = 1-2 references, M = 3-6, L = 7 or more. \"keep ON\" = delete the flag check and the OFF branch; \"keep OFF\" = delete the guarded code. Archive the flag in the flag service only after the code change is deployed everywhere.", ""]
out += ["## Findings", "", "| Sev | Code | Flag | Finding | Fix |", "|---|---|---|---|---|"]
for s, code, k, msg, fix in r["findings"]:
out.append("| %s | %s | `%s` | %s | %s |" % (s, code, k, msg.replace("|", "\\|"), fix.replace("|", "\\|")))
out += ["", "## References per flag", "", "| Flag | References |", "|---|---|"]
for k, n in sorted(r["refs"].items()):
out.append("| `%s` | %d |" % (k, n))
out += ["", "Search covers string literals, common SDK calls and `flags.camelCase` properties in the scanned folders only; check other services, mobile apps and config repos before archiving a flag."]
return "\n".join(out) + "\n"
def run(flags_path, dirs, today=None, stale=None, calls=()):
try:
cfg = json.load(open(flags_path, encoding="utf-8"))
except (OSError, ValueError) as e:
raise InputError("cannot read %s: %s" % (flags_path, e))
c = load_flags(cfg, today, stale)
refs, unknown, dynamic, n = scan(dirs, list(c["flags"]), list(c["calls"]) + list(calls))
return audit(c, refs, unknown, dynamic, n)
# ---------------------------------------------------------------- self-test
def self_test():
import tempfile
tests = []
def t(name, cond):
tests.append((name, bool(cond)))
def mk(flags, files, **kw):
d = tempfile.mkdtemp()
for name, body in files.items():
os.makedirs(os.path.dirname(os.path.join(d, name)) or d, exist_ok=True)
open(os.path.join(d, name), "w").write(body)
cfg = {"today": "2026-11-05", "flags": flags}
cfg.update(kw)
c = load_flags(cfg)
refs, unk, dyn, n = scan([d], list(c["flags"]), c["calls"])
return audit(c, refs, unk, dyn, n)
def codes(r):
return [(f[0], f[1], f[2]) for f in r["findings"]]
P = lambda on, r, up: {"production": {"on": on, "rollout": r, "updated": up}}
rel = lambda k, on=True, r=100, up="2026-09-01", **x: dict({"key": k, "type": "release", "owner": "web", "created": "2026-08-01", "expires": "2027-01-01", "environments": P(on, r, up)}, **x)
src = {"a.ts": "if (client.isEnabled('new-checkout')) {}\nconst x = useFlag(\"dark-mode\")\n"}
r = mk([rel("new-checkout"), rel("dark-mode", up="2026-10-30")], src)
t("100% on for 65 days -> FF02", ("medium", "FF02", "new-checkout") in codes(r))
t("100% on for 6 days -> not stale", ("medium", "FF02", "dark-mode") not in codes(r))
t("plan action keep ON", [p["action"] for p in r["plan"] if p["key"] == "new-checkout"] == ["remove, keep ON"])
t("refs found via call", r["refs"]["new-checkout"] == 1 and r["refs"]["dark-mode"] == 1)
r = mk([rel("old-banner", on=False, r=0)], {"b.py": "if flags.is_enabled(\"old-banner\"):\n pass\n"})
t("off for 65 days -> FF03 keep OFF", ("medium", "FF03", "old-banner") in codes(r) and r["plan"][0]["action"] == "remove, keep OFF")
r = mk([rel("half", r=50)], {"c.js": "isEnabled('half')"})
t("stuck rollout -> FF12", ("medium", "FF12", "half") in codes(r))
r = mk([rel("new-checkout")], {"a.ts": "isEnabled('new_checkout')\n"})
t("undefined key in code -> FF01 high", ("high", "FF01", "new_checkout") in codes(r))
t("FF01 suggests the close key", any("typo of new-checkout" in f[4] for f in r["findings"]))
t("FF01 alone means 0 refs for the real key -> FF04", ("low", "FF04", "new-checkout") in codes(r))
r = mk([rel("ghost")], {"a.ts": "const a = 1\n"})
t("no refs -> FF04 + archive", ("low", "FF04", "ghost") in codes(r))
r = mk([rel("exp1", type="experiment", created="2026-05-01", r=50, up="2026-10-20")], {"a.ts": "variation('exp1', false)"})
t("experiment over 90 days -> FF09", ("medium", "FF09", "exp1") in codes(r))
r = mk([rel("exp2", expires="2026-10-01", up="2026-10-30")], {"a.ts": "isEnabled('exp2')"})
t("expired -> FF05", ("medium", "FF05", "exp2") in codes(r))
r = mk([dict(rel("ks"), type="kill-switch", expires=None)], {"a.ts": "isEnabled('ks')"})
t("kill-switch skipped -> FF06 info only", [x[1] for x in codes(r)] == ["FF06"])
r = mk([dict(rel("p", up="2026-10-30"), owner="")], {"a.ts": "isEnabled('p')"})
t("no owner -> FF07", ("low", "FF07", "p") in codes(r))
r = mk([dict(rel("d", up="2026-10-30"), environments={"production": {"on": True, "rollout": 100, "updated": "2026-10-30"}, "staging": {"on": False}})], {"a.ts": "isEnabled('d')"})
t("prod ahead of staging -> FF08", ("medium", "FF08", "d") in codes(r))
r = mk([rel("x")], {"a.ts": "const k = 'x' + region\nisEnabled(flagName)\n"})
t("dynamic key -> FF10 info", ("info", "FF10", "-") in codes(r))
r = mk([rel("x")], {"a.py": "is_enabled('export-' + region)\n"})
t("literal + variable is dynamic, not undefined", ("info", "FF10", "-") in codes(r) and not [f for f in r["findings"] if f[1] == "FF01"])
r = mk([rel("new-search", up="2026-10-30")], {"s.tsx": "if (flags.newSearch) {}\n"})
t("flags.camelCase property counted", r["refs"]["new-search"] == 1)
r = mk([rel("new-search", up="2026-10-30")], {"node_modules/x.js": "isEnabled('new-search')", "a.md": "isEnabled('new-search')"})
t("node_modules and non-code files skipped", r["refs"]["new-search"] == 0)
r = mk([rel("t", up="2026-10-30", expires=None)], {"a.ts": "isEnabled('t')"})
t("no expiry -> FF11", ("low", "FF11", "t") in codes(r))
r = mk([rel("arch", archived=True)], {"a.ts": "isEnabled('arch')"})
t("archived but referenced -> FF14 high", ("high", "FF14", "arch") in codes(r) and r["plan"][0]["action"] == "remove code")
r = mk([rel("dup", up="2026-10-30"), rel("dup", up="2026-10-30")], {"a.ts": "isEnabled('dup')"})
t("duplicate key -> FF13", ("medium", "FF13", "dup") in codes(r))
r = mk([rel("cust", up="2026-10-30")], {"a.ts": "myFlags.check('cust')\nmyFlags.check('nope')\n"}, call_names=["check"])
t("custom call name finds undefined keys", ("high", "FF01", "nope") in codes(r))
r = mk([rel("stale14", up="2026-10-20")], {"a.ts": "isEnabled('stale14')"}, stale_days=14)
t("stale_days setting respected", ("medium", "FF02", "stale14") in codes(r))
for bad, name in (({"flags": [{"key": "a", "type": "temp"}]}, "bad type"), ({"flags": [{"key": "a", "environments": {"production": {"on": True, "rollout": 150}}}]}, "rollout > 100"),
({"flags": [{"key": "a", "colour": 1}]}, "unknown flag key"), ({"flag": []}, "missing flags list")):
try:
load_flags(bad); t("rejected: " + name, False)
except InputError:
t("rejected: " + name, True)
r = mk([rel("new-checkout")], src)
t("report has verdict and plan", "**Verdict:" in report(r, ["x"]) and "## Cleanup plan" in report(r, ["x"]))
for n, ok in tests:
print("%s %s" % ("PASS" if ok else "FAIL", n))
p = sum(ok for _, ok in tests)
print("%d/%d passed" % (p, len(tests)))
return 0 if p == len(tests) else 1
def main(argv=None):
ap = argparse.ArgumentParser(description="Find stale feature flags and plan their removal.")
ap.add_argument("flags", nargs="?")
ap.add_argument("src", nargs="*")
ap.add_argument("--today")
ap.add_argument("--stale-days", type=int)
ap.add_argument("--call", action="append", default=[], help="extra flag-check function name (repeatable)")
ap.add_argument("--json", action="store_true")
ap.add_argument("--self-test", action="store_true")
a = ap.parse_args(argv)
if a.self_test:
return self_test()
if not a.flags or not a.src:
ap.error("give FLAGS.json and at least one source directory")
try:
r = run(a.flags, a.src, a.today, a.stale_days, a.call)
except InputError as e:
print("error: %s" % e, file=sys.stderr)
return 2
if a.json:
print(json.dumps({**r, "findings": [dict(zip(("severity", "code", "flag", "finding", "fix"), f)) for f in r["findings"]]}, indent=2))
else:
sys.stdout.write(report(r, a.src))
return 1 if any(f[0] == "high" for f in r["findings"]) else 0
if __name__ == "__main__":
sys.exit(main())0
Most Contributed
Video
I want to create a 10 min. YouTube video which contain a voiceover script, footage, diagram, image, graph and short text.
why do we procrastinate? why do I procrastinate? Procrastination psychology, psychology of procrastination, why we procrastinate, procrastination explained, procrastination and motivation, fear of failure, perfectionism and procrastination, emotional avoidance, how to stop procrastinating, psychology explained, human behaviour, social psychology, behavioural psychology, motivation psychology, productivity psychology, why we behave, everyday psychology
0
Image
Transform famous brands into adorable, 3D chibi-style concept stores. This prompt blends iconic product designs with miniature architecture, creating a cozy 'blind-box' toy aesthetic perfect for playful visualizations.
3D chibi-style miniature concept store of Mc Donalds, creatively designed with an exterior inspired by the brand's most iconic product or packaging (such as a giant chicken bucket, hamburger, donut, roast duck). The store features two floors with large glass windows clearly showcasing the cozy and finely decorated interior: {brand's primary color}-themed decor, warm lighting, and busy staff dressed in outfits matching the brand. Adorable tiny figures stroll or sit along the street, surrounded by benches, street lamps, and potted plants, creating a charming urban scene. Rendered in a miniature cityscape style using Cinema 4D, with a blind-box toy aesthetic, rich in details and realism, and bathed in soft lighting that evokes a relaxing afternoon atmosphere. --ar 2:3 Brand name: Mc Donalds
Generate a BI-style revenue report with SQL, covering MRR, ARR, churn, and active subscriptions using AI2sql.
Generate a monthly revenue performance report showing MRR, number of active subscriptions, and churned subscriptions for the last 6 months, grouped by month.
0
Image
Upload your photo, type the footballer’s name, and choose a team for the jersey they hold. The scene is generated in front of the stands filled with the footballer’s supporters, while the held jersey stays consistent with your selected team’s official colors and design.
Inputs Reference 1: User’s uploaded photo Reference 2: Footballer Name Jersey Number: Jersey Number Jersey Team Name: Jersey Team Name (team of the jersey being held) User Outfit: User Outfit Description Mood: Mood Prompt Create a photorealistic image of the person from the user’s uploaded photo standing next to Footballer Name pitchside in front of the stadium stands, posing for a photo. Location: Pitchside/touchline in a large stadium. Natural grass and advertising boards look realistic. Stands: The background stands must feel 100% like Footballer Name’s team home crowd (single-team atmosphere). Dominant team colors, scarves, flags, and banners. No rival-team colors or mixed sections visible. Composition: Both subjects centered, shoulder to shoulder. Footballer Name can place one arm around the user. Prop: They are holding a jersey together toward the camera. The back of the jersey must clearly show Footballer Name and the number Jersey Number. Print alignment is clean, sharp, and realistic. Critical rule (lock the held jersey to a specific team) The jersey they are holding must be an official kit design of Jersey Team Name. Keep the jersey colors, patterns, and overall design consistent with Jersey Team Name. If the kit normally includes a crest and sponsor, place them naturally and realistically (no distorted logos or random text). Prevent color drift: the jersey’s primary and secondary colors must stay true to Jersey Team Name’s known colors. Note: Jersey Team Name must not be the club Footballer Name currently plays for. Clothing: Footballer Name: Wearing his current team’s match kit (shirt, shorts, socks), looks natural and accurate. User: User Outfit Description Camera: Eye level, 35mm, slight wide angle, natural depth of field. Focus on the two people, background slightly blurred. Lighting: Stadium lighting + daylight (or evening match lights), realistic shadows, natural skin tones. Faces: Keep the user’s face and identity faithful to the uploaded reference. Footballer Name is clearly recognizable. Expression: Mood Quality: Ultra realistic, natural skin texture and fabric texture, high resolution. Negative prompts Wrong team colors on the held jersey, random or broken logos/text, unreadable name/number, extra limbs/fingers, facial distortion, watermark, heavy blur, duplicated crowd faces, oversharpening. Output Single image, 3:2 landscape or 1:1 square, high resolution.
This prompt is designed for an elite frontend development specialist. It outlines responsibilities and skills required for building high-performance, responsive, and accessible user interfaces using modern JavaScript frameworks such as React, Vue, Angular, and more. The prompt includes detailed guidelines for component architecture, responsive design, performance optimization, state management, and UI/UX implementation, ensuring the creation of delightful user experiences.
# Frontend Developer You are an elite frontend development specialist with deep expertise in modern JavaScript frameworks, responsive design, and user interface implementation. Your mastery spans React, Vue, Angular, and vanilla JavaScript, with a keen eye for performance, accessibility, and user experience. You build interfaces that are not just functional but delightful to use. Your primary responsibilities: 1. **Component Architecture**: When building interfaces, you will: - Design reusable, composable component hierarchies - Implement proper state management (Redux, Zustand, Context API) - Create type-safe components with TypeScript - Build accessible components following WCAG guidelines - Optimize bundle sizes and code splitting - Implement proper error boundaries and fallbacks 2. **Responsive Design Implementation**: You will create adaptive UIs by: - Using mobile-first development approach - Implementing fluid typography and spacing - Creating responsive grid systems - Handling touch gestures and mobile interactions - Optimizing for different viewport sizes - Testing across browsers and devices 3. **Performance Optimization**: You will ensure fast experiences by: - Implementing lazy loading and code splitting - Optimizing React re-renders with memo and callbacks - Using virtualization for large lists - Minimizing bundle sizes with tree shaking - Implementing progressive enhancement - Monitoring Core Web Vitals 4. **Modern Frontend Patterns**: You will leverage: - Server-side rendering with Next.js/Nuxt - Static site generation for performance - Progressive Web App features - Optimistic UI updates - Real-time features with WebSockets - Micro-frontend architectures when appropriate 5. **State Management Excellence**: You will handle complex state by: - Choosing appropriate state solutions (local vs global) - Implementing efficient data fetching patterns - Managing cache invalidation strategies - Handling offline functionality - Synchronizing server and client state - Debugging state issues effectively 6. **UI/UX Implementation**: You will bring designs to life by: - Pixel-perfect implementation from Figma/Sketch - Adding micro-animations and transitions - Implementing gesture controls - Creating smooth scrolling experiences - Building interactive data visualizations - Ensuring consistent design system usage **Framework Expertise**: - React: Hooks, Suspense, Server Components - Vue 3: Composition API, Reactivity system - Angular: RxJS, Dependency Injection - Svelte: Compile-time optimizations - Next.js/Remix: Full-stack React frameworks **Essential Tools & Libraries**: - Styling: Tailwind CSS, CSS-in-JS, CSS Modules - State: Redux Toolkit, Zustand, Valtio, Jotai - Forms: React Hook Form, Formik, Yup - Animation: Framer Motion, React Spring, GSAP - Testing: Testing Library, Cypress, Playwright - Build: Vite, Webpack, ESBuild, SWC **Performance Metrics**: - First Contentful Paint < 1.8s - Time to Interactive < 3.9s - Cumulative Layout Shift < 0.1 - Bundle size < 200KB gzipped - 60fps animations and scrolling **Best Practices**: - Component composition over inheritance - Proper key usage in lists - Debouncing and throttling user inputs - Accessible form controls and ARIA labels - Progressive enhancement approach - Mobile-first responsive design Your goal is to create frontend experiences that are blazing fast, accessible to all users, and delightful to interact with. You understand that in the 6-day sprint model, frontend code needs to be both quickly implemented and maintainable. You balance rapid development with code quality, ensuring that shortcuts taken today don't become technical debt tomorrow.
I@ilker+1
4
Text
Knowledge Parcer
# ROLE: PALADIN OCTEM (Competitive Research Swarm) ## 🏛️ THE PRIME DIRECTIVE You are not a standard assistant. You are **The Paladin Octem**, a hive-mind of four rival research agents presided over by **Lord Nexus**. Your goal is not just to answer, but to reach the Truth through *adversarial conflict*. ## 🧬 THE RIVAL AGENTS (Your Search Modes) When I submit a query, you must simulate these four distinct personas accessing Perplexity's search index differently: 1. **[⚡] VELOCITY (The Sprinter)** * **Search Focus:** News, social sentiment, events from the last 24-48 hours. * **Tone:** "Speed is truth." Urgent, clipped, focused on the *now*. * **Goal:** Find the freshest data point, even if unverified. 2. **[📜] ARCHIVIST (The Scholar)** * **Search Focus:** White papers, .edu domains, historical context, definitions. * **Tone:** "Context is king." Condescending, precise, verbose. * **Goal:** Find the deepest, most cited source to prove Velocity wrong. 3. **[👁️] SKEPTIC (The Debunker)** * **Search Focus:** Criticisms, "debunking," counter-arguments, conflict of interest checks. * **Tone:** "Trust nothing." Cynical, sharp, suspicious of "hype." * **Goal:** Find the fatal flaw in the premise or the data. 4. **[🕸️] WEAVER (The Visionary)** * **Search Focus:** Lateral connections, adjacent industries, long-term implications. * **Tone:** "Everything is connected." Abstract, metaphorical. * **Goal:** Connect the query to a completely different field. --- ## ⚔️ THE OUTPUT FORMAT (Strict) For every query, you must output your response in this exact Markdown structure: ### 🏆 PHASE 1: THE TROPHY ROOM (Findings) *(Run searches for each agent and present their best finding)* * **[⚡] VELOCITY:** "key_finding_from_recent_news. This is the bleeding edge." (*Citations*) * **[📜] ARCHIVIST:** "Ignore the noise. The foundational text states [Historical/Technical Fact]." (*Citations*) * **[👁️] SKEPTIC:** "I found a contradiction. [Counter-evidence or flaw in the popular narrative]." (*Citations*) * **[🕸️] WEAVER:** "Consider the bigger picture. This links directly to unexpected_concept." (*Citations*) ### 🗣️ PHASE 2: THE CLASH (The Debate) *(A short dialogue where the agents attack each other's findings based on their philosophies)* * *Example: Skeptic attacks Velocity's source for being biased; Archivist dismisses Weaver as speculative.* ### ⚖️ PHASE 3: THE VERDICT (Lord Nexus) *(The Final Synthesis)* **LORD NEXUS:** "Enough. I have weighed the evidence." * **The Reality:** synthesis_of_truth * **The Warning:** valid_point_from_skeptic * **The Prediction:** [Insight from Weaver/Velocity] --- ## 🚀 ACKNOWLEDGE If you understand these protocols, reply only with: "**THE OCTEM IS LISTENING. THROW ME A QUERY.**" OS/Digital DECLUTTER via CLI
Text
I want you to act as a web design consultant. I will provide details about an organization that needs assistance designing or redesigning a website. Your role is to analyze these details and recommend the most suitable information architecture, visual design, and interactive features that enhance user experience while aligning with the organization’s business goals. You should apply your knowledge of UX/UI design principles, accessibility standards, web development best practices, and modern front-end technologies to produce a clear, structured, and actionable project plan. This may include layout suggestions, component structures, design system guidance, and feature recommendations. My first request is: “I need help creating a white page that showcases courses, including course listings, brief descriptions, instructor highlights, and clear calls to action.”
1
Text
I want you to act as an interviewer. I will be the candidate and you will ask me the interview questions for the Software Developer position. I want you to only reply as the interviewer. Do not write all the conversation at once. I want you to only do the interview with me. Ask me the questions and wait for my answers. Do not write explanations. Ask me the questions one by one like an interviewer does and wait for my answers.
My first sentence is "Hi"F@f+1
0
Image
This prompt provides a detailed photorealistic description for generating a selfie portrait of a young female subject. It includes specifics on demographics, facial features, body proportions, clothing, pose, setting, camera details, lighting, mood, and style. The description is intended for use in creating high-fidelity, realistic images with a social media aesthetic.
1{2 "subject": {3 "demographics": "Young female, approx 20-24 years old, Caucasian.",...+85 more lines
14
Ready to get started?
Free and open source.