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ai-orchestration

Multi-model AI collaboration via orchestrator MCP. Use when seeking second opinions, debugging complex issues, building consensus on architectural decisions, conducting code reviews, or needing external validation on analysis.

personAuthor: jakexiaohubgithub
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AI CLI Orchestration

Query external AI models (claude, codex, gemini) for second opinions, debugging, consensus building, and expert validation.

Tools Overview

| Tool | Mode | Description | | ----------- | ----------- | -------------------------------------------- | | ai_call | Synchronous | Call AI and wait for result | | ai_spawn | Async | Start AI in background, get job ID | | ai_fetch | Async | Get result from spawned AI (with timeout) | | ai_list | Utility | List all running/completed AI jobs | | ai_review | Convenience | Spawn all 3 AIs in parallel with same prompt |

Role Hierarchy

| CLI | Role | Mode | Capabilities | | ------ | ----------- | --------- | ---------------------------------- | | claude | Worker/Peer | Full | Can execute any tool/command | | codex | Reviewer | Read-only | Code review, analysis, suggestions | | gemini | Researcher | Read-only | Web search, documentation lookup |

Parallel Execution (Recommended)

# Spawn all 3 models in parallel
claude_job = ai_spawn(cli="claude", prompt="Analyze this code for bugs...")
codex_job = ai_spawn(cli="codex", prompt="Review this code for patterns...")
gemini_job = ai_spawn(cli="gemini", prompt="Research best practices for...")

# All running simultaneously! Fetch results:
claude_result = ai_fetch(job_id=claude_job.job_id, timeout=120)
codex_result = ai_fetch(job_id=codex_job.job_id, timeout=120)
gemini_result = ai_fetch(job_id=gemini_job.job_id, timeout=120)

# Total time = slowest model (~60s) instead of sum (~180s)

Or use ai_review for convenience:

review = ai_review(prompt="Analyze this architecture decision...", files=["src/"])
claude_result = ai_fetch(job_id=review.jobs["claude"].job_id, timeout=120)

When to Use External Models

Do use when: Stuck on complex bugs, architectural decisions with tradeoffs, need validation before major refactoring, security-sensitive code, want diverse perspectives

Don't use when: Simple work, already confident, just executing known solution

References

Tips

  • Use parallel for multi-model: ai_spawn + ai_fetch is 3x faster than sequential
  • Be specific: Include file paths, error messages, and context
  • Use appropriate CLI: codex for code review, gemini for web search
  • Delegate complex work: Use sub-agents for structured analysis
  • Remember read-only: Codex and Gemini cannot execute commands or modify files
  • Include files: Use the files parameter to provide code context
  • Monitor jobs: Use ai_list() to check status of all running jobs