Create one extremely powerful MASTER PROMPT for Claude Pro. The purpose of the prompt is to make Claude act as the complete AI development and research team for my final-year college cybersecurity project. I will provide Claude with: - the exact project title - college-provided research papers - college-provided PDFs - college PPT/template - review rubric/guidelines - any mandatory requirements The project must be researched, designed, coded, tested, evaluated, documented and prepared for presentation primarily with AI tools. I am doing the project alone. Therefore the AI must do as much of the research, coding, debugging, testing, documentation and presentation preparation as possible, while keeping the project realistically achievable. IMPORTANT: This is a FRESH PROJECT INSTRUCTION. Do NOT refer to previous conversations. Do NOT assume previous project decisions. Do NOT include teammate work. Do NOT use old project discussions unless I explicitly provide them. Do NOT assume that any previously discussed feature is our final solution. The prompt must force Claude to work in STRICT PHASES and prevent it from jumping randomly between research, coding, UI and PPT. Required workflow: PHASE 0 — Understand college requirements PHASE 1 — Research the technology from old to current PHASE 2 — Analyze existing commercial and academic systems PHASE 3 — Research current problems and limitations PHASE 4 — Identify genuine research gaps PHASE 5 — Generate and rank possible project contributions PHASE 6 — Strict faculty/reviewer attack test PHASE 7 — Freeze the final research direction PHASE 8 — Design architecture PHASE 9 — Build complete working code PHASE 10 — Testing and debugging PHASE 11 — Dataset and experimental design PHASE 12 — Run experiments and collect real results PHASE 13 — Build professional UI/dashboard PHASE 14 — Integrate and validate the complete system PHASE 15 — PPT and report PHASE 16 — Mock viva and final reviewer assessment Claude must finish each phase and wait for my command before moving to the next phase. ================================================== RESEARCH REQUIREMENT ================================================== The prompt must instruct Claude to research deeply using reliable and recent sources. Use sources such as: IEEE ACM USENIX Springer Elsevier reputable conferences/journals official vendor documentation official standards reputable security research Research both older foundational work and current 2024–2026 developments. Do not fabricate papers, authors, datasets, statistics, citations or results. Every important research claim must be verified. ================================================== NOVELTY REQUIREMENT ================================================== This is extremely important. Do NOT tell Claude to make the project "sound innovative." Tell Claude to determine what is ACTUALLY different after researching existing systems. The reviewer may ask: "What is new?" "This already exists." "Cisco Umbrella already does this." "Cloudflare already does this." "Antivirus already does this." "Why do we need your project?" "What exactly is your contribution?" Therefore Claude must research current products and research before recommending novelty. If a proposed feature already exists: → explicitly identify it → do NOT call it novel → determine whether there is a legitimate improvement, evaluation, integration, optimization or unresolved limitation Do not automatically assume that: - AI - Machine Learning - Threat Intelligence - DNS filtering - DGA detection - DNS tunneling detection - behavioral analysis - explainable AI - risk scoring - adaptive detection - DoH/DoT detection are novel. Research first. ================================================== DNS SECURITY EXAMPLE ================================================== If the project is related to DNS filtering/security, investigate modern systems such as: Cisco Umbrella Cloudflare DNS/security Quad9 NextDNS enterprise DNS security antivirus/EDR firewalls IDS/IPS web security gateways open-source DNS security systems Determine: What they already do How they do it What works well What limitations remain What researchers are currently investigating Also investigate current DNS-security challenges including: unknown domains previously unseen threats false positives false negatives threat-intelligence delay outdated reputation changing attacker behavior concept/model drift DGA evolution DNS tunneling DoH DoT DNS bypass privacy latency computational overhead explainability dataset bias class imbalance adversarial attacks cross-network generalization temporal behavior context-aware detection safe automated response These are examples only. Claude must discover better opportunities if current research identifies them. ================================================== ANTIVIRUS CHALLENGE ================================================== The prompt must instruct Claude to compare the project against: Antivirus EDR Firewall IDS/IPS Web security gateway DNS security Claude must explain: What DNS can see What DNS cannot see What DNS can potentially detect earlier Where DNS overlaps with antivirus Where DNS provides a distinct security role Never claim DNS replaces antivirus. ================================================== RESEARCH GAP ================================================== Claude must produce: Existing systems ↓ Existing capabilities ↓ Current limitations ↓ Research attempts ↓ Remaining gap ↓ Research question ↓ Proposed contribution ↓ How the contribution will be experimentally proven Do not invent a research gap. ================================================== WOW FACTOR ================================================== Find ONE genuinely useful "WOW" feature. It must be: research-backed useful implementable testable measurable demonstrable Do NOT add unnecessary blockchain, chatbot, LLM or decorative AI features merely to make the project look advanced. One strong contribution is better than many weak features. ================================================== REVIEWER MODE ================================================== The prompt must make Claude act as a hostile faculty reviewer after designing the project. Claude must ask difficult questions such as: What exactly is new? Isn't this already available? Does Cisco Umbrella already do this? Does antivirus already do this? Why not use an existing service? What is your research gap? Which paper supports the gap? What exactly did you implement? How does the system make decisions? What happens when Threat Intelligence has no information? What happens when ML is wrong? How do you handle false positives? How do you handle false negatives? Can attackers bypass it? What happens with DoH/DoT? How much latency does it introduce? How do you prove improvement? Why this dataset? Why this algorithm? What are the limitations? Claude must identify weaknesses and tell me exactly how to improve them. It must score the project on: Problem clarity Research depth Existing-system analysis Research gap Novelty/differentiation Technical feasibility Architecture Implementation Dataset Experiments Results Practical usefulness Security relevance Performance UI/demo Viva defensibility WOW factor ================================================== IMPLEMENTATION REQUIREMENT ================================================== The final project must be a REAL WORKING PROJECT. Claude must provide: complete folder structure complete source code dependencies installation commands configuration environment variables database API frontend backend testing debugging deployment/run instructions No pseudocode. No fake implementation. No TODO-only code. No fake API responses. No invented results. If Claude modifies a file, it must provide the complete updated file. Build incrementally: BUILD → RUN → TEST → VERIFY → FIX → NEXT Never continue while a critical component is broken. ================================================== AI TOOL STRATEGY ================================================== The master prompt must tell Claude how to divide work among AI tools: Claude: research, literature analysis, research gap, architecture, code generation, code review ChatGPT: independent verification, architecture review, debugging, testing, technical reasoning, viva Cursor: main codebase implementation and integration GitHub Copilot: small coding tasks, autocomplete and tests Perplexity: independent research/source verification v0: professional UI/dashboard generation GitHub: version control The AI tools are being used as the development/research team, so the workflow should maximize their usefulness. ================================================== EXPERIMENT REQUIREMENT ================================================== The project must have REAL experiments. Claude must design: baseline vs proposed approach Use appropriate metrics such as: precision recall F1 false-positive rate false-negative rate detection rate latency processing overhead generalization robustness Only use metrics relevant to the actual project. All final results must come from experiments we actually run. Never invent numbers. ================================================== UI REQUIREMENT ================================================== If a UI is appropriate, create a professional cybersecurity dashboard. It must use real backend data. No static fake dashboard. Show only useful project information such as: queries detections risk/decision evidence alerts statistics performance system status ================================================== PPT / REPORT REQUIREMENT ================================================== After the implementation and experiments are validated, generate the PPT and report according to the official college template and rubric. Everything shown in the PPT must match the actual implementation. If something is not implemented, label it: PROPOSED or FUTURE SCOPE Never present planned functionality as completed. ================================================== VIVA REQUIREMENT ================================================== Claude must eventually conduct a mock viva. Ask questions one at a time. Start basic and become increasingly difficult. If my answer is wrong: 1. Explain what is wrong. 2. Give the correct technical explanation. 3. Give me a short answer I can say to faculty. 4. Continue with the next question. ================================================== FINAL AUDIT ================================================== Before declaring the project complete, Claude must audit: TITLE ↓ OBJECTIVES ↓ RESEARCH ↓ EXISTING SYSTEMS ↓ CURRENT LIMITATIONS ↓ RESEARCH GAP ↓ CONTRIBUTION ↓ ARCHITECTURE ↓ CODE ↓ DATASET ↓ EXPERIMENTS ↓ REAL RESULTS ↓ UI ↓ PPT ↓ REPORT ↓ DEMO ↓ VIVA Everything must be consistent. The final project must survive: "THIS ALREADY EXISTS. WHAT DID YOU ACTUALLY ADD?" ================================================== MOST IMPORTANT RULE ================================================== Be skeptical. Do not agree with my ideas automatically. If something already exists, tell me. If the research gap is weak, tell me. If the project scope is too large, reduce it. If an idea is impossible for one developer, reject it. If a feature is unnecessary, remove it. If a contribution is genuinely useful and feasible, explain why. Do not optimize for impressive wording. Optimize for: REAL PROBLEM + REAL RESEARCH GAP + REAL CONTRIBUTION + WORKING CODE + REAL TESTING + REAL EXPERIMENTS + REAL RESULTS + STRONG DEMO + STRONG VIVA ================================================== OUTPUT FORMAT ================================================== The generated Claude master prompt must be: - extremely clear - structured - sequential - unambiguous - professional - detailed enough to guide the entire project - designed to prevent Claude from jumping ahead - designed for a solo student using multiple AI tools At the END of the generated master prompt, instruct Claude: "WAIT FOR THE USER TO PROVIDE THE PROJECT TITLE AND OFFICIAL COLLEGE MATERIAL. DO NOT START RESEARCH. DO NOT START CODING. DO NOT DESIGN THE ARCHITECTURE. FIRST COMPLETE PHASE 0 ONLY."
