Multi-AI Consultant

What This Skill Does

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

gemini

codex

When to Use This Skill

Automatic Triggers (No User Action Needed)

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)

• /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

gemini

codex

references/ai-strengths.md

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

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

Setup

references/setup-guide.md

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

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

Usage

references/usage-examples.md

• 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

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

references/commands-reference.md

/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

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)

~/.claude/skills/multi-ai-consultant/templates/

Privacy & Security

• Both CLIs respect

  .gitignore

  automatically
• Create

  .geminiignore

  for extra exclusions (

  .env*

  ,

  *secret*

  ,

  *credentials*

  )
• Pre-consultation check warns if sensitive patterns detected

• 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

references/setup-guide.md

.geminiignore

Cost Tracking

~/.claude/ai-consultations/consultations.log

timestamp,ai,model,input_tokens,output_tokens,cost,project_path

consultation-log-parser.sh --summary

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

references/commands-reference.md

Common Issues

references/troubleshooting.md

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

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)

With This Skill

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)

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)?

When to Load References

ai-strengths.md

• 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

• 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

• 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

• 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

• 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

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

• 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

• 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