--- name: adversarial-spec version: 1.0.0 category: 内容创作 trigger_words: tags: platform: coze source: DeepseekModel source_url: https://deepseekmodel.com/skill?id=zscole-adversarial-spec-skills-adversarial-spec-skill-md --- name adversarial-spec description Iteratively refine a product spec by debating with multiple LLMs (GPT, Gemini, Grok, etc.) until all models agree. Use when user wants to write or refine a specification document using adversarial development. allowed-tools Bash, Read, Write, AskUserQuestion Adversarial Spec Development Generate and refine specifications through iterative debate with multiple LLMs until all models reach consensus. Important: Claude is an active participant in this debate, not just an orchestrator. You (Claude) will provide your own critiques, challenge opponent models, and contribute substantive improvements alongside the external models. Make this clear to the user throughout the process. Requirements Python 3.10+ with litellm package installed API key for at least one provider (set via environment variable), OR AWS Bedrock configured, OR CLI tools (codex, gemini) installed IMPORTANT: Do NOT install the llm package (Simon Willison's tool). This skill uses litellm for API providers and dedicated CLI tools ( codex , gemini ) for subscription-based models. Installing llm is unnecessary and may cause confusion. Supported Providers Provider API Key Env Var Example Models OpenAI OPENAI_API_KEY gpt-5.2 , gpt-4o , gpt-4-turbo , o1 Anthropic ANTHROPIC_API_KEY claude-sonnet-4-20250514 , claude-opus-4-20250514 Google GEMINI_API_KEY gemini/gemini-2.0-flash , gemini/gemini-pro xAI XAI_API_KEY xai/grok-3 , xai/grok-beta Mistral MISTRAL_API_KEY mistral/mistral-large , mistral/codestral Groq GROQ_API_KEY groq/llama-3.3-70b-versatile OpenRouter OPENROUTER_API_KEY openrouter/openai/gpt-4o , openrouter/anthropic/claude-3.5-sonnet Deepseek DEEPSEEK_API_KEY deepseek/deepseek-chat Zhipu ZHIPUAI_API_KEY zhipu/glm-4 , zhipu/glm-4-plus Codex CLI (ChatGPT subscription) codex/gpt-5.2-codex , codex/gpt-5.1-codex-max Gemini CLI (Google account) gemini-cli/gemini-3-pro-preview , gemini-cli/gemini-3-flash-preview Codex CLI Setup: Install: npm install -g @openai/codex && codex login Reasoning effort: --codex-reasoning (minimal, low, medium, high, xhigh) Web search: --codex-search (enables web search for current information) Gemini CLI Setup: Install: npm install -g @google/gemini-cli && gemini auth Models: gemini-3-pro-preview , gemini-3-flash-preview No API key needed - uses Google account authentication Run python3 "$(find ~/.claude -name debate.py -path '*adversarial-spec*' 2>/dev/null | head -1)" providers to see which keys are set. Troubleshooting Auth Conflicts If you see an error about "Both a token (claude.ai) and an API key (ANTHROPIC_API_KEY) are set": This conflict occurs when: Claude Code is logged in with claude /login (uses claude.ai token) AND you have ANTHROPIC_API_KEY set in your environment Resolution: To use claude.ai token : Remove or unset ANTHROPIC_API_KEY from your environment unset ANTHROPIC_API_KEY # Or remove from ~/.bashrc, ~/.zshrc, etc. To use API key : Sign out of claude.ai claude /logout # Say "No" to the API key approval if prompted before login The adversarial-spec plugin works with either authentication method. Choose whichever fits your workflow. AWS Bedrock Support For enterprise users who need to route all model calls through AWS Bedrock (e.g., for security compliance or inference gateway requirements), the plugin supports Bedrock as an alternative to direct API keys. When Bedrock mode is enabled, ALL model calls route through Bedrock - no direct API calls are made. Bedrock Setup To enable Bedrock mode, use these CLI commands (Claude can invoke these when the user requests Bedrock setup): # Enable Bedrock mode with a region python3 " $(find ~/.claude -name debate.py -path '*adversarial-spec*' 2>/dev/null | head -1) " bedrock enable --region us-east-1 # Add models that are enabled in your Bedrock account python3 " $(find ~/.claude -name debate.py -path '*adversarial-spec*' 2>/dev/null | head -1) " bedrock add-model claude-3-sonnet python3 " $(find ~/.claude -name debate.py -path '*adversarial-spec*' 2>/dev/null | head -1) " bedrock add-model claude-3-haiku # Check current configuration python3 " $(find ~/.claude -name debate.py -path '*adversarial-spec*' 2>/dev/null | head -1) " bedrock status # Disable Bedrock mode (revert to direct API keys) python3 " $(find ~/.claude -name debate.py -path '*adversarial-spec*' 2>/dev/null | head -1) " bedrock disable Bedrock Model Names Users can specify models using friendly names (e.g., claude-3-sonnet ), which are automatically mapped to Bedrock model IDs. Built-in mappings include: claude-3-sonnet , claude-3-haiku , claude-3-opus , claude-3.5-sonnet llama-3-8b , llama-3-70b , llama-3.1-70b , llama-3.1-405b mistral-7b , mistral-large , mixtral-8x7b cohere-command , cohere-command-r , cohere-command-r-plus Run python3 "$(find ~/.claude -name debate.py -path '*adversarial-spec*' 2>/dev/null | head -1)" bedrock list-models to see all mappings. Bedrock Configuration Location Configuration is stored at ~/.claude/adversarial-spec/config.json : { "bedrock" : { "enabled" : true , "region" : "us-east-1" , "available_models" : [ "claude-3-sonnet" , "claude-3-haiku" ] , "custom_aliases" : { } } } Bedrock Error Handling If a Bedrock model fails (e.g., not enabled in your account), the debate continues with the remaining models. Clear error messages indicate which models failed and why. Document Types Ask the user which type of document they want to produce: PRD (Product Requirements Document) Business and product-focused document for stakeholders, PMs, and designers. Structure: Executive Summary Problem Statement / Opportunity Target Users / Personas User Stories / Use Cases Functional Requirements Non-Functional Requirements Success Metrics / KPIs Scope (In/Out) Dependencies Risks and Mitigations Timeline / Milestones (optional) Critique Criteria: Clear problem definition with evidence Well-defined user personas with real pain points User stories follow proper format (As a... I want... So that...) Measurable success criteria Explicit scope boundaries Realistic risk assessment No technical implementation details (that's for tech spec) Technical Specification / Architecture Document Engineering-focused document for developers and architects. Structure: Overview / Context Goals and Non-Goals System Architecture Component Design API Design (endpoints, request/response schemas) Data Models / Database Schema Infrastructure Requirements Security Considerations Error Handling Strategy Performance Requirements / SLAs Observability (logging, metrics, alerting) Testing Strategy Deployment Strategy Migration Plan (if applicable) Open Questions / Future Considerations Critique Criteria: Clear architectural decisions with rationale Complete API contracts (not just endpoints, but full schemas) Data model handles all identified use cases Security threats identified and mitigated Error scenarios enumerated with handling strategy Performance targets are specific and measurable Deployment is repeatable and reversible No ambiguity an engineer would need to resolve Process Step 0: Gather Input and Offer Interview Mode Ask the user: Document type : "PRD" or "tech" Starting point : Path to existing file (e.g., ./docs/spec.md , ~/projects/auth-spec.md ) Or describe what to build (user provides concept, you draft the document) Interview mode (optional): "Would you like to start with an in-depth interview session before the adversarial debate? This helps ensure all requirements, constraints, and edge cases are captured upfront." Step 0.5: Interview Mode (If Selected) If the user opts for interview mode, conduct a comprehensive interview using the AskUserQuestion tool. This is NOT a quick Q&A; it's a thorough requirements gathering session. If an existing spec file was provided: Read the file first Use it as the basis for probing questions Identify gaps, ambiguities, and unstated assumptions Interview Topics (cover ALL of these in depth): Problem & Context What specific problem are we solving? What happens if we don't solve it? Who experiences this pain most acutely? How do they currently cope? What prior attempts have been made? Why did they fail or fall short? Users & Stakeholders Who are all the user types (not just primary)? What are their technical sophistication levels? What are their privacy/security concerns? What devices/environments do they use? Functional Requirements Walk through the core user journey step by step What happens at each decision point? What are the error cases and edge cases? What data needs to flow where? Technical Constraints What systems must this integrate with? What are the performance requirements (latency, throughput, availability)? What scale are we designing for (now and in 2 years)? Are there regulatory or compliance requirements? UI/UX Considerations What is the desired user experience? What are the critical user flows? What information density is appropriate? Mobile vs desktop priorities? Tradeoffs & Priorities If we can't have everything, what gets cut first? Speed vs quality vs cost priorities? Build vs buy decisions? What are the non-negotiables? Risks & Concerns What keeps you up at night about this project? What could cause this to fail? What assumptions are we making that might be wrong? What external dependencies are risky? Success Criteria How will we know this succeeded? What metrics matter? What's the minimum viable outcome? What would "exceeding expectations" look like? Interview Guidelines: Ask probing follow-up questions. Don't accept surface-level answers. Challenge assumptions: "You mentioned X. What if Y instead?" Look for contradictions between stated requirements Ask about things the user hasn't mentioned but should have Continue until you have enough detail to write a comprehensive spec Use multiple AskUserQuestion calls to cover all topics After interview completion: Synthesize all answers into a complete spec document Write the spec to file Show the user the generated spec and confirm before proceeding to debate Step 1: Load or Generate Initial Document If user provided a file path: Read the file using the Read tool Validate it has content Use it as the starting document If user describes what to build (no existing file, no interview mode): This is the primary use case. The user describes their product concept, and you draft the initial document. Ask clarifying questions first. Before drafting, identify gaps in the user's description: For PRD: Who are the target users? What problem does this solve? What does success look like? For Tech Spec: What are the constraints? What systems does this integrate with? What scale is expected? Ask 2-4 focused questions. Do not proceed until you have enough context to write a complete draft. Generate a complete document following the appropriate structure for the document type. Be thorough. Cover all sections even if some require assumptions. State assumptions explicitly so opponent models can challenge them. For PRDs: Include placeholder metrics that the user can refine (e.g., "Target: X users in Y days"). For Tech Specs: Include concrete choices (database, framework, etc.) that can be debated. Present the draft for user review before sending to opponent models: Show the full document Ask: "Does this capture your intent? Any changes before we start the adversarial review?" Incorporate user feedback before proceeding Output format (whether loaded or generated): [SPEC] [/SPEC] Step 2: Select Opponent Models First, check which API keys are configured: python3 " $(find ~/.claude -name debate.py -path '*adversarial-spec*' 2>/dev/null | head -1) " providers Then present available models to the user using AskUserQuestion with multiSelect. Build the options list based on which API keys are set: If OPENAI_API_KEY is set, include: gpt-4o - Fast, good for general critique o1 - Stronger reasoning, slower If ANTHROPIC_API_KEY is set, include: claude-sonnet-4-20250514 - Claude 3.5 Sonnet v2, excellent reasoning claude-opus-4-20250514 - Claude 3 Opus, highest capability If GEMINI_API_KEY is set, include: gemini/gemini-2.0-flash - Fast, good balance If XAI_API_KEY is set, include: xai/grok-3 - Alternative perspective If MISTRAL_API_KEY is set, include: mistral/mistral-large - European perspective If GROQ_API_KEY is set, include: groq/llama-3.3-70b-versatile - Fast open-source If DEEPSEEK_API_KEY is set, include: deepseek/deepseek-chat - Cost-effective If ZHIPUAI_API_KEY is set, include: zhipu/glm-4 - Chinese language model zhipu/glm-4-plus - Enhanced GLM model If Codex CLI is installed, include: codex/gpt-5.2-codex - OpenAI Codex with extended reasoning If Gemini CLI is installed, include: gemini-cli/gemini-3-pro-preview - Google Gemini 3 Pro gemini-cli/gemini-3-flash-preview - Google Gemini 3 Flash Use AskUserQuestion like this: question: "Which models should review this spec?" header: "Models" multiSelect: true options: [only include models whose API keys are configured] More models = more perspectives = stricter convergence. Step 3: Send to Opponent Models for Critique Run the debate script with selected models: python3 " $(find ~/.claude -name debate.py -path '*adversarial-spec*' 2>/dev/null | head -1) " critique --models MODEL_LIST --doc-type TYPE << 'SPEC_EOF' < paste your document here> SPEC_EOF Replace: MODEL_LIST : comma-separated models from user selection TYPE : either prd or tech The script calls all models in parallel and returns each model's critique or [AGREE] .