Claude-skill-registry 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.

install

source · Clone the upstream repo

git clone https://github.com/majiayu000/claude-skill-registry

Claude Code · Install into ~/.claude/skills/

T=$(mktemp -d) && git clone --depth=1 https://github.com/majiayu000/claude-skill-registry "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/data/ai-orchestration" ~/.claude/skills/majiayu000-claude-skill-registry-ai-orchestration && rm -rf "$T"

manifest: skills/data/ai-orchestration/SKILL.md

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

Tool parameters: See references/tools.md
Usage patterns: See references/patterns.md
Sub-agents: See references/sub-agents.md

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