multi-ai-consultant

安装量: 59
排名: #12565

安装

npx skills add https://github.com/secondsky/claude-skills --skill multi-ai-consultant
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:
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?"
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..."
Security changes
Authentication logic
Authorization rules
Cryptography
Input validation
→ Auto-consult: "Consulting Gemini to verify security approach..."
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
AI
Tool
When to Use
Special Features
Cost
Gemini 2.5 Pro
gemini
CLI
Web research, latest docs, thinking
Google Search, extended reasoning, grounding
~$0.10-0.50
OpenAI GPT-4
codex
CLI
Repo-aware analysis, code review
Auto-scans directory, OpenAI reasoning
~$0.05-0.30
Fresh Claude
Task tool
Quick second opinion, budget-friendly
Same capabilities, fresh perspective
Free
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):
🤖 My Analysis
- Claude's original reasoning and attempts
💎/🔷/🔄 Other AI's Analysis
- External AI's complete response
🔍 Key Differences
- Agreement, divergence, what each AI caught/missed
⚡ Synthesis
- Combined perspective, root cause, trade-offs
✅ 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
:
Install CLIs
:
bun add -g @google/generative-ai-cli
(Gemini),
bun add -g codex
(Codex, optional)
Set API keys
:
export GEMINI_API_KEY="..."
,
export OPENAI_API_KEY="..."
Install skill
Symlink to
~/.claude/skills/multi-ai-consultant
Copy templates
:
GEMINI.md
,
codex.md
,
.geminiignore
to project root
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
:
JWT authentication bug (saved ~30 min, found platform-specific issue)
State management choice (informed decision with 2025 patterns)
Refactoring review (found 3 consistency issues)
Security validation (found 2 critical issues via OWASP 2025)
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):
GEMINI.md
- System instructions for Gemini (enforces 5-part format, web search)
codex.md
- System instructions for Codex (enforces repo-aware analysis)
.geminiignore
- Privacy exclusions beyond
.gitignore
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
:
CLI not installed
:
gemini: command not found
→ Fix:
bun add -g @google/generative-ai-cli
API key invalid
Authentication failed → Fix:
export GEMINI_API_KEY="..."
Context too large
Token limit exceeded → Fix: Use specific files, not entire repo
Privacy leak
:
.env
file sent → Fix: Add to
.gitignore
and
.geminiignore
Skill not discovered
Not working → Fix: Check
~/.claude/skills/multi-ai-consultant
Token Efficiency
Without This Skill
Typical scenario
(stuck on bug):
Try approach 1 (~4k tokens)
Research CLI syntax (~3k tokens)
Try approach 2 (~4k tokens)
Research documentation (~3k tokens)
Try approach 3 (~4k tokens)
Total
~20k tokens, 30-45 minutes
With This Skill
Same scenario
:
Try approach 1 (~4k tokens)
Execute
/consult-gemini
(~1k tokens)
Gemini finds issue (<5k tokens, billed separately)
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)?
Aspect
MCP Server
CLI Approach
Setup time
4-6 hours
60-75 minutes
Complexity
High (MCP protocol)
Low (bash + CLIs)
Maintenance
Update MCP SDK
Update CLI (rare)
Flexibility
Locked to AIs
Any AI with CLI
Debugging
MCP protocol
Standard bash
Dependencies
MCP SDK, npm
Just 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 | maintainers@example.com
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