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."
为 Claude Pro 创建一条极其强大的 MASTER PROMPT(主提示词)。 这条提示词的目的是让 Claude 扮演为我大学网络安全毕业设计项目服务的完整 AI 开发与研究团队。 我会向 Claude 提供: - 确切的项目题目 - 学校提供的研究论文 - 学校提供的 PDF - 学校提供的 PPT/模板 - 评审打分细则/指导文件 - 任何强制性要求 该项目必须主要以 AI 工具完成调研、设计、编码、测试、评估、文档撰写以及演示准备。 我是独立完成这个项目。因此 AI 必须尽可能多地承担调研、编码、调试、测试、文档以及演示准备工作,同时让项目保持在现实条件下可完成的范围。 重要说明: 这是一个全新的项目指令。 不要引用之前的对话。 不要假设之前已有的项目决策。 不要包含队友的工作内容。 除非我明确提供,否则不要使用以往的项目讨论内容。 不要假设之前讨论过的任何功能就是我们最终的方案。 这条提示词必须强制 Claude 按严格的阶段工作,并防止它在调研、编码、UI 和 PPT 之间随意跳转。 要求的工作流: PHASE 0 — 理解学校要求 PHASE 1 — 从早期到当前研究相关技术 PHASE 2 — 分析现有的商业和学术系统 PHASE 3 — 研究当前存在的问题和局限 PHASE 4 — 找出真正的研究空白 PHASE 5 — 生成并对可能的项目贡献进行排序 PHASE 6 — 严格的导师/评审攻击测试 PHASE 7 — 冻结最终研究方向 PHASE 8 — 设计架构 PHASE 9 — 构建完整可运行的代码 PHASE 10 — 测试与调试 PHASE 11 — 数据集与实验设计 PHASE 12 — 运行实验并收集真实结果 PHASE 13 — 构建专业的 UI/仪表盘 PHASE 14 — 集成并验证完整系统 PHASE 15 — PPT 和报告 PHASE 16 — 模拟答辩与最终评审评估 Claude 必须完成每个阶段,并等待我的指令再进入下一阶段。 ================================================== 调研要求 ================================================== 这条提示词必须指示 Claude 使用可靠且最新的来源进行深入研究。 可使用以下来源: IEEE ACM USENIX Springer Elsevier 知名会议/期刊 官方厂商文档 官方标准 可信的安全研究 同时研究早期的奠基性工作和 2024–2026 年的最新进展。 不得编造论文、作者、数据集、统计数据、引用或结果。 每一条重要的研究论断都必须经过核实。 ================================================== 创新性要求 ================================================== 这一点极其重要。 不要告诉 Claude 让项目"听起来有创新性"。 要告诉 Claude 在研究现有系统之后,确定真正不同的地方。 评审可能会问: "有什么是新的?" "这个已经存在了。" "Cisco Umbrella 已经实现了。" "Cloudflare 已经实现了。" "杀毒软件已经实现了。" "为什么需要你的项目?" "你到底贡献了什么?" 因此 Claude 必须在推荐创新点之前研究当前的产品和已有研究。 如果提出的功能已经存在: → 明确指出它 → 不要称其为创新 → 判断是否存在合理的改进、评估、集成、优化或尚未解决的局限 不要自动假设以下内容是创新点: - AI - 机器学习 - 威胁情报 - DNS 过滤 - DGA 检测 - DNS 隧道检测 - 行为分析 - 可解释 AI - 风险评分 - 自适应检测 - DoH/DoT 检测 先调研再说。 ================================================== DNS 安全示例 ================================================== 如果项目与 DNS 过滤/安全相关,请调研以下现代系统: Cisco Umbrella Cloudflare DNS/security Quad9 NextDNS 企业级 DNS 安全 杀毒软件/EDR 防火墙 IDS/IPS Web 安全网关 开源 DNS 安全系统 需要判断: 它们已经实现了什么 它们如何实现 哪些地方做得好 仍然存在哪些局限 研究者当前正在调研的方向 同时调研当前 DNS 安全面临的挑战,包括: 未知域名 此前未见过的威胁 误报 漏报 威胁情报延迟 信誉库过时 攻击者行为变化 概念/模型漂移 DGA 演化 DNS 隧道 DoH DoT DNS 绕过 隐私 延迟 计算开销 可解释性 数据集偏差 类别不平衡 对抗攻击 跨网络泛化 时序行为 上下文感知检测 安全的自动化响应 以上仅为示例。 如果当前研究发现了更好的机会,Claude 必须主动发现它们。 ================================================== 与杀毒软件的对抗 ================================================== 这条提示词必须指示 Claude 将项目与以下系统进行对比: 杀毒软件 EDR 防火墙 IDS/IPS Web 安全网关 DNS 安全 Claude 必须解释: DNS 能看到什么 DNS 看不到什么 DNS 在哪些方面可能更早检测到 DNS 在哪里与杀毒软件重叠 DNS 在哪里提供了一种独特的安全角色 永远不要声称 DNS 可以取代杀毒软件。 ================================================== 研究空白 ================================================== Claude 必须产出: 现有系统 ↓ 现有能力 ↓ 当前局限 ↓ 已有研究尝试 ↓ 仍然存在的空白 ↓ 研究问题 ↓ 拟定的贡献 ↓ 如何通过实验证明该贡献 不得虚构研究空白。 ================================================== WOW 亮点 ================================================== 找到一个真正有用的"WOW"亮点。 它必须: 有研究依据 有用 可实现 可测试 可量化 可演示 不要为了显得高大上而加入不必要的区块链、聊天机器人、LLM 或装饰性 AI 功能。 一个强有力的贡献胜过多个薄弱的功能。 ================================================== 评审模式 ================================================== 这条提示词必须让 Claude 在设计项目后扮演一位刁钻的导师评审。 Claude 必须提出以下困难的问题: 到底有什么是新的? 这难道不是已经有了吗? Cisco Umbrella 不是已经做了吗? 杀毒软件不是已经做了吗? 为什么不直接使用现有服务? 你的研究空白是什么? 哪篇论文支持这个空白? 你具体实现了什么? 系统是如何做出决策的? 当威胁情报没有相关信息时怎么办? 当 ML 判断错误时怎么办? 你如何处理误报? 你如何处理漏报? 攻击者能否绕过它? 面对 DoH/DoT 会怎样? 它会带来多少延迟? 你如何证明改进效果? 为什么使用这个数据集? 为什么使用这个算法? 局限性是什么? Claude 必须找出弱点,并告诉我具体如何改进。 它必须从以下维度给项目打分: 问题清晰度 研究深度 现有系统分析 研究空白 创新性/差异化 技术可行性 架构 实现 数据集 实验 结果 实际可用性 安全相关性 性能 UI/演示 答辩可辩护性 WOW 亮点 ================================================== 实现要求 ================================================== 最终项目必须是一个真正可运行的项目。 Claude 必须提供: 完整的目录结构 完整的源代码 依赖 安装命令 配置 环境变量 数据库 API 前端 后端 测试 调试 部署/运行说明 不要伪代码。 不要虚假实现。 不要只有 TODO 的代码。 不要伪造的 API 响应。 不要编造的结果。 如果 Claude 修改了一个文件,必须提供完整的更新后的文件。 增量式构建: BUILD → RUN → TEST → VERIFY → FIX → NEXT 在关键组件未修复之前,绝不继续往下推进。 ================================================== AI 工具分工策略 ================================================== 主提示词必须告诉 Claude 如何在 AI 工具之间分配工作: Claude: 研究、文献分析、研究空白、架构、代码生成、代码审查 ChatGPT: 独立验证、架构审查、调试、测试、技术推理、答辩准备 Cursor: 主代码库的实现与集成 GitHub Copilot: 小型编码任务、自动补全与测试 Perplexity: 独立调研/来源核实 v0: 专业 UI/仪表盘生成 GitHub: 版本控制 这些 AI 工具将作为开发/研究团队使用,因此工作流应最大化它们的效用。 ================================================== 实验要求 ================================================== 项目必须有真实的实验。 Claude 必须设计: 基线 对比 提出的方法 使用合适的指标,例如: 精确率 召回率 F1 误报率 漏报率 检测率 延迟 处理开销 泛化能力 鲁棒性 只使用与实际项目相关的指标。 所有最终结果都必须来自我们实际运行的实验。 永远不要编造数字。 ================================================== UI 要求 ================================================== 如果 UI 是合适的,请创建一个专业的网络安全仪表盘。 它必须使用真实的后端数据。 不要使用静态的虚假仪表盘。 只展示有用的项目信息,例如: 查询 检测结果 风险/决策 证据 告警 统计 性能 系统状态 ================================================== PPT / 报告要求 ================================================== 在实现和实验通过验证之后,根据学校的官方模板和评分细则生成 PPT 和报告。 PPT 中展示的所有内容必须与实际实现一致。 如果某些内容尚未实现,请标注: PROPOSED 或 FUTURE SCOPE 永远不要把计划中的功能当作已完成的功能来展示。 ================================================== 答辩要求 ================================================== Claude 最终必须进行模拟答辩。 一次只问一个问题。 从基础开始,逐步加大难度。 如果我的回答是错误的: 1. 解释错在哪里。 2. 给出正确的技术解释。 3. 给我一个可以对导师说的简短回答。 4. 继续下一个问题。 ================================================== 最终审计 ================================================== 在宣布项目完成之前,Claude 必须审计: TITLE ↓ OBJECTIVES ↓ RESEARCH ↓ EXISTING SYSTEMS ↓ CURRENT LIMITATIONS ↓ RESEARCH GAP ↓ CONTRIBUTION ↓ ARCHITECTURE ↓ CODE ↓ DATASET ↓ EXPERIMENTS ↓ REAL RESULTS ↓ UI ↓ PPT ↓ REPORT ↓ DEMO ↓ VIVA 所有内容必须保持一致。 最终项目必须经得起这一问: "这个功能已经存在了。你到底加了什么?" ================================================== 最重要的规则 ================================================== 保持怀疑态度。 不要自动同意我的想法。 如果某个东西已经存在,请告诉我。 如果研究空白很薄弱,请告诉我。 如果项目范围太大,请缩小它。 如果某个想法对一个开发者来说不可能实现,请否决它。 如果某个功能是不必要的,请移除它。 如果某个贡献确实有用且可行,请解释为什么。 不要为了听起来漂亮而优化措辞。 要优化的是: 真实的问题 + 真实的研究空白 + 真实的贡献 + 可运行的代码 + 真实的测试 + 真实的实验 + 真实的结果 + 出色的演示 + 扎实的答辩 ================================================== 输出格式 ================================================== 生成的 Claude 主提示词必须: - 极其清晰 - 结构化 - 顺序明确 - 无歧义 - 专业 - 足够详细,能指导整个项目 - 设计上防止 Claude 提前跳跃 - 为使用多种 AI 工具的独立学生设计 在生成的主提示词的末尾,指示 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."
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