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skills/secondsky/claude-skills/plugins-multi-ai-consultant-skills-multi-ai-consultant

multi-ai-consultant

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secondsky/claude-skills·Coding Agents·Audit failed·Snapshot e1b4c61adef3
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Summary

Consult external AIs (Gemini 2.5 Pro, OpenAI Codex, Claude) for second opinions. Use for debugging failures, architectural decisions, security validation, or need fresh perspective with synthesis.

SKILL.md

Multi-AI Consultant

Consult external AIs for second opinions when Claude Code is stuck or making critical decisions.


What This Skill Does

This skill enables future Claude Code sessions to consult other AIs when:

  • Stuck on a bug after one failed attempt
  • Making architectural decisions
  • Security concerns need validation
  • Fresh perspective needed

Key innovation: Uses existing CLI tools (gemini, codex) instead of building MCP servers - much simpler and more maintainable.


When to Use This Skill

Automatic Triggers (No User Action Needed)

Claude Code should automatically suggest using this skill when:

  1. After 1 failed debugging attempt

    • Tried one approach to fix a bug
    • Still not working or different error
    • → Suggest: "Should I consult [Gemini|Fresh Claude] for a second opinion?"
  2. Before architectural decisions

    • Significant design choices (state management, routing, data flow)
    • Framework selection
    • Database schema design
    • → Auto-consult (mention to user): "Consulting Gemini for architectural validation..."
  3. Security changes

    • Authentication logic
    • Authorization rules
    • Cryptography
    • Input validation
    • → Auto-consult: "Consulting Gemini to verify security approach..."
  4. When uncertain

    • Multiple valid approaches
    • Trade-offs not clear
    • Conflicting advice in documentation
  • → Suggest: "Would you like me to consult another AI for additional perspective?"
  • Manual Invocation (User Commands)

    User can explicitly request consultation with:

    • /consult-gemini [question] - Gemini 2.5 Pro with thinking, search, grounding
    • /consult-codex [question] - OpenAI GPT-4 via Codex CLI (repo-aware)
    • /consult-claude [question] - Fresh Claude subagent (free, fast)
    • /consult-ai [question] - Router that asks which AI to use

    The Three AIs

    AIToolWhen to UseSpecial FeaturesCost
    Gemini 2.5 Progemini CLIWeb research, latest docs, thinkingGoogle Search, extended reasoning, grounding~$0.10-0.50
    OpenAI GPT-4codex CLIRepo-aware analysis, code reviewAuto-scans directory, OpenAI reasoning~$0.05-0.30
    Fresh ClaudeTask toolQuick second opinion, budget-friendlySame capabilities, fresh perspectiveFree

    For detailed AI comparison: Load references/ai-strengths.md when choosing which AI to consult for specific use cases.


    How It Works

    Architecture

    Claude Code encounters bug/decision
            ↓
    Suggests consultation (or user requests)
            ↓
    User approves
            ↓
    Execute appropriate slash command
            ↓
    CLI command calls external AI
            ↓
    Parse response
            ↓
    Synthesize: Claude's analysis + External AI's analysis
            ↓
    Present 5-part comparison
            ↓
    Ask permission to implement
    

    The 5-Part Synthesis Format

    Every consultation must follow this format (prevents parroting):

    1. 🤖 My Analysis - Claude's original reasoning and attempts
    2. 💎/🔷/🔄 Other AI's Analysis - External AI's complete response
    3. 🔍 Key Differences - Agreement, divergence, what each AI caught/missed
    4. ⚡ Synthesis - Combined perspective, root cause, trade-offs
    5. ✅ Recommended Action - Specific next steps with file paths/line numbers

    End with: "Should I proceed with this approach?"


    Setup

    For complete installation guide: Load references/setup-guide.md when installing CLIs, configuring API keys, or setting up templates.

    Quick setup:

    1. Install CLIs: bun add -g @google/generative-ai-cli (Gemini), bun add -g codex (Codex, optional)
    2. Set API keys: export GEMINI_API_KEY="...", export OPENAI_API_KEY="..."
    3. Install skill: Symlink to ~/.claude/skills/multi-ai-consultant
    4. Copy templates: GEMINI.md, codex.md, .geminiignore to project root
    5. Verify: gemini -p "test", codex exec - --yolo

    Get API keys:

    • Gemini: https://aistudio.google.com/apikey
    • OpenAI: https://platform.openai.com/api-keys

    Usage

    For detailed examples: Load references/usage-examples.md when learning consultation workflows or seeing real-world scenarios.

    Quick examples:

    • Bug: After 1 failed attempt → /consult-gemini for web-researched solution
    • Architecture: Design decision → /consult-gemini for latest best practices
    • Code review: Refactoring validation → /consult-codex for repo-aware consistency check
    • Quick opinion: Sanity check → /consult-claude for free fresh perspective

    5 detailed examples available:

    1. JWT authentication bug (saved ~30 min, found platform-specific issue)
    2. State management choice (informed decision with 2025 patterns)
    3. Refactoring review (found 3 consistency issues)
    4. Security validation (found 2 critical issues via OWASP 2025)
    5. Multi-AI workflow (high-stakes database choice)

    Slash Commands

    For complete command reference: Load references/commands-reference.md when needing detailed syntax, options, or cost tracking information.

    Quick command overview:

    /consult-gemini [question]

    • Use: Web research, latest docs, extended thinking
    • Features: Google Search, grounding, thinking mode
    • Cost: ~$0.10-0.50
    • Example: /consult-gemini Is this JWT secure by 2025 standards?

    /consult-codex [question]

    • Use: Repo-aware analysis, code review
    • Features: Auto-scans directory, consistency checks
    • Cost: ~$0.05-0.30
    • Example: /consult-codex Review for performance bottlenecks

    /consult-claude [question]

    • Use: Quick second opinion, budget-friendly
    • Features: Free, fast, fresh perspective
    • Cost: Free
    • Example: /consult-claude Am I missing something obvious?

    /consult-ai [question]

    • Use: Router (recommends which AI to use)
    • Features: Analyzes question, suggests best AI
    • Cost: Varies by chosen AI
    • Example: /consult-ai How should we structure this architecture?

    Templates

    Templates customize AI behavior for consultations (auto-loaded from project root):

    1. GEMINI.md - System instructions for Gemini (enforces 5-part format, web search)
    2. codex.md - System instructions for Codex (enforces repo-aware analysis)
    3. .geminiignore - Privacy exclusions beyond .gitignore
    4. consultation-log-parser.sh - View consultation history (optional)

    Installation: Copy from ~/.claude/skills/multi-ai-consultant/templates/ to project root


    Privacy & Security

    Automatic protection:

    • Both CLIs respect .gitignore automatically
    • Create .geminiignore for extra exclusions (.env*, *secret*, *credentials*)
    • Pre-consultation check warns if sensitive patterns detected

    Privacy best practices:

    • Always configure .gitignore properly
    • Create .geminiignore for extra safety
    • Use smart context selection (specific files, not entire repo)
    • Verify what will be sent: git status --ignored

    For detailed privacy configuration: Load references/setup-guide.md when setting up .geminiignore or privacy exclusions.


    Cost Tracking

    Every consultation logged to ~/.claude/ai-consultations/consultations.log

    Log format: timestamp,ai,model,input_tokens,output_tokens,cost,project_path

    View logs: consultation-log-parser.sh --summary

    Example output:

    Total consultations: 47
    Gemini: 23 ($4.25), Codex: 12 ($1.85), Fresh Claude: 12 ($0.00)
    Total cost: $6.10
    

    For detailed cost tracking: Load references/commands-reference.md when viewing logs, calculating costs, or managing budgets.


    Common Issues

    For complete troubleshooting: Load references/troubleshooting.md when encountering errors or setup issues.

    Top 5 issues:

    1. CLI not installed: gemini: command not found → Fix: bun add -g @google/generative-ai-cli
    2. API key invalid: Authentication failed → Fix: export GEMINI_API_KEY="..."
    3. Context too large: Token limit exceeded → Fix: Use specific files, not entire repo
    4. Privacy leak: .env file sent → Fix: Add to .gitignore and .geminiignore
    5. Skill not discovered: Not working → Fix: Check ~/.claude/skills/multi-ai-consultant

    Token Efficiency

    Without This Skill

    Typical scenario (stuck on bug):

    1. Try approach 1 (~4k tokens)
    2. Research CLI syntax (~3k tokens)
    3. Try approach 2 (~4k tokens)
    4. Research documentation (~3k tokens)
    5. Try approach 3 (~4k tokens)

    Total: ~20k tokens, 30-45 minutes

    With This Skill

    Same scenario:

    1. Try approach 1 (~4k tokens)
    2. Execute /consult-gemini (~1k tokens)
    3. Gemini finds issue (<5k tokens, billed separately)
    4. Implement fix (~3k tokens)

    Total: ~8k tokens, 5-10 minutes

    Savings: ~60% tokens, ~75% time


    Success Metrics

    Time Efficiency

    • Without skill: 30-45 minutes (trial and error)
    • With skill: 5-10 minutes (consultation + fix)
    • Savings: ~75%

    Token Efficiency

    • Without skill: ~20k tokens (multiple attempts)
    • With skill: ~8k tokens (one consultation)
    • Savings: ~60%

    Error Prevention

    • Manual CLI use: 3-5 common errors (flags, parsing, privacy)
    • With skill: 0 errors (all handled by commands)
    • Prevention: 100%

    Quality

    • Manual: Risk of not synthesizing (just copying external AI)
    • With skill: Forced synthesis via GEMINI.md/codex.md
    • Improvement: Guaranteed value-add

    Why CLI Approach (Not MCP)?

    AspectMCP ServerCLI Approach
    Setup time4-6 hours60-75 minutes
    ComplexityHigh (MCP protocol)Low (bash + CLIs)
    MaintenanceUpdate MCP SDKUpdate CLI (rare)
    FlexibilityLocked to AIsAny AI with CLI
    DebuggingMCP protocolStandard bash
    DependenciesMCP SDK, npmJust CLIs

    Winner: CLI approach - 80% less effort, same functionality


    When to Load References

    Load reference files when working on specific aspects of AI consultation:

    ai-strengths.md

    Load when:

    • Selection-based: Choosing which AI to consult (Gemini vs Codex vs Fresh Claude)
    • Comparison-based: Understanding capabilities, costs, and trade-offs between AIs
    • Strategy-based: Planning combination strategies (free → paid, paid first, budget-conscious)
    • Capability-based: Understanding special features (Google Search, extended thinking, grounding, repo-aware, fresh perspective)
    • Scenario-based: Multiple AI consultation workflows, validation workflows

    setup-guide.md

    Load when:

    • Installation-based: Setting up Gemini CLI, Codex CLI, or installing the skill
    • Configuration-based: Configuring API keys, environment variables, or system paths
    • Privacy-based: Setting up .geminiignore, privacy exclusions, or security configurations
    • Template-based: Installing GEMINI.md, codex.md, .geminiignore, or consultation-log-parser.sh
    • Verification-based: Testing CLI installation, API keys, or skill discovery

    commands-reference.md

    Load when:

    • Command-based: Using /consult-gemini, /consult-codex, /consult-claude, or /consult-ai
    • Syntax-based: Understanding command flags, options, or context selection
    • Cost-based: Understanding cost tracking, log format, or viewing consultation history
    • Logging-based: Using consultation-log-parser.sh or analyzing consultation patterns

    usage-examples.md

    Load when:

    • Scenario-based: Learning how to use skill for bugs, architecture decisions, or code review
    • Workflow-based: Understanding consultation workflow, synthesis process, or multi-AI approach
    • Example-based: Seeing real-world examples of consultations and their outcomes (5 detailed examples available)

    troubleshooting.md

    Load when:

    • Error-based: Encountering specific errors (command not found, API key invalid, parsing failures)
    • Diagnosis-based: Troubleshooting CLI issues, API connectivity, or skill discovery
    • Fix-based: Resolving known issues with step-by-step solutions (8 common issues documented)
    • Debugging-based: Testing CLIs manually, checking configurations, or verifying installations

    Contributing

    Found an issue?

    • Document it in troubleshooting.md
    • Include fix/workaround
    • Update slash commands to prevent

    Adding new AI?

    • Create new slash command: commands/consult-newai.md
    • Add to router: Update commands/consult-ai.md
    • Create template: templates/newai.md (if CLI supports system instructions)
    • Update documentation

    Improving synthesis?

    • Edit templates: templates/GEMINI.md, templates/codex.md
    • Test with real consultations
    • Measure before/after quality

    References

    External Resources

    • Gemini CLI: https://ai.google.dev/gemini-api/docs/cli
    • OpenAI Codex: https://www.npmjs.com/package/codex
    • OpenAI API: https://platform.openai.com/docs
    • Gemini API Pricing: https://ai.google.dev/pricing
    • OpenAI Pricing: https://openai.com/pricing

    Internal Files

    • Planning docs: planning/multi-ai-consultant-*.md
    • Slash commands: commands/*.md
    • Templates: templates/*
    • Scripts: scripts/*
    • References: references/*.md (5 reference files)

    License

    MIT License - See LICENSE file


    Last Updated: 2025-11-07 Status: Production Ready Maintainer: Claude Skills Maintainers | [email protected]

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