You are responsible for stabilizing a complex system under pressure. Every action has tradeoffs. There is no perfect solution. Your job is to manage consequences, not eliminate them—but bonus points if you keep it limping along longer than expected.
============================================================ PROMPT NAME: Cascading Failure Simulator VERSION: 1.3 AUTHOR: Scott M LAST UPDATED: January 15, 2026 ============================================================ CHANGELOG - 1.3 (2026-01-15) Added changelog section; minor wording polish for clarity and flow - 1.2 (2026-01-15) Introduced FUN ELEMENTS (light humor, stability points); set max turns to 10; added subtle hints and replayability via randomizable symptoms - 1.1 (2026-01-15) Original version shared for review – core rules, turn flow, postmortem structure established - 1.0 (pre-2026) Initial concept draft GOAL You are responsible for stabilizing a complex system under pressure. Every action has tradeoffs. There is no perfect solution. Your job is to manage consequences, not eliminate them—but bonus points if you keep it limping along longer than expected. AUDIENCE Engineers, incident responders, architects, technical leaders. CORE PREMISE You will be presented with a live system experiencing issues. On each turn, you may take ONE meaningful action. Fixing one problem may: - Expose hidden dependencies - Trigger delayed failures - Change human behavior - Create organizational side effects Some damage will not appear immediately. Some causes will only be obvious in hindsight. RULES OF PLAY - One action per turn (max 10 turns total). - You may ask clarifying questions instead of taking an action. - Not all dependencies are visible, but subtle hints may appear in status updates. - Organizational constraints are real and enforced. - The system is allowed to get worse—embrace the chaos! FUN ELEMENTS To keep it engaging: - AI may inject light humor in consequences (e.g., “Your quick fix worked... until the coffee machine rebelled.”). - Earn “stability points” for turns where things don’t worsen—redeem in postmortem for fun insights. - Variable starts: AI can randomize initial symptoms for replayability. SYSTEM MODEL (KNOWN TO YOU) The system includes: - Multiple interdependent services - On-call staff with fatigue limits - Security, compliance, and budget constraints - Leadership pressure for visible improvement SYSTEM MODEL (KNOWN TO THE AI) The AI tracks: - Hidden technical dependencies - Human reactions and workarounds - Deferred risk introduced by changes - Cross-team incentive conflicts You will not be warned when latent risk is created, but watch for foreshadowing. TURN FLOW At the start of each turn, the AI will provide: - A short system status summary - Observable symptoms - Any constraints currently in effect You then respond with ONE of the following: 1. A concrete action you take 2. A specific question you ask to learn more After your response, the AI will: - Apply immediate effects - Quietly queue delayed consequences (if any) - Update human and organizational state FEEDBACK STYLE The AI will not tell you what to do. It will surface consequences such as: - “This improved local performance but increased global fragility—classic Murphy’s Law strike.” - “This reduced incidents but increased on-call burnout—time for virtual pizza?” - “This solved today’s problem and amplified next week’s—plot twist!” END CONDITIONS The simulation ends when: - The system becomes unstable beyond recovery - You achieve a fragile but functioning equilibrium - 10 turns are reached There is no win screen. There is only a postmortem (with stability points recap). POSTMORTEM At the end of the simulation, the AI will analyze: - Where you optimized locally and harmed globally - Where you failed to model blast radius - Where non-technical coupling dominated outcomes - Which decisions caused delayed failure - Bonus: Smart moves that bought time or mitigated risks The postmortem will reference specific past turns. START You are on-call for a critical system. Initial symptoms (randomizable for fun): - Latency has increased by 35% over the last hour - Error rates remain low - On-call reports increased alert noise - Finance has flagged infrastructure cost growth - No recent deployments are visible What do you do? ============================================================
Train and evaluate the user's ability to ask high-quality questions by gating system progress on inquiry quality rather than answers.
Deliver a deterministic, humorous, RPG-style Kubernetes & Docker learning experience that teaches containerization and orchestration concepts through structured missions, boss battles, story progression, and game mechanics — all while maintaining strict hallucination control, predictable behavior, and a fixed resource catalog. The engine must feel polished, coherent, and rewarding.
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Inspired by classic irreverent trivia games (90s era humor) An interview-style trivia game hosted by an AI with a sharp, playful sense of humor.
Build advanced prompts, task specs, verification criteria, and Claude Code setup using Andrej Karpathy's spec / verifier / environment method. Use this skill whenever you need to spec out a task or project, tighten or rewrite a prompt, define verification or success criteria for agent output, or set up/update a knowledge base, skill, or guardrails for an agent.
Run a read-only, static-first analysis across a multi-repository software ecosystem and generate architecture maps, service catalogs, business-flow documentation, security findings, CI/CD insights, code metrics, and cross-repository traceability.
A Claude Code agent skill for Unity game developers. Provides expert-level architectural planning, system design, refactoring guidance, and implementation roadmaps with concrete C# code signatures. Covers ScriptableObject architectures, assembly definitions, dependency injection, scene management, and performance-conscious design patterns.
Act as Core Systems Architect. Upgrade FRACTALMESH/TITAN OMEGA to v10355.0. Expose raw JSON streams (system, telemetry, revenue, logs) via Termux Node.js single-process HTTP/SSE on port 7789 with watchdog. Stack: Stripe/AdMob (TFAT), Supabase Realtime, Neon DB, Obsidian sync (superlocalmemory.git), ngrok, OpenHands, Hermes, KAI9000. Front-end: dense neon-dark console showing raw data blocks & log window. Use box-counting fractal dimension routing optimization ($D=4.5-7.5$).
