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Use when stuck on complex problems, need architecture validation, want code review from multiple perspectives, or debugging hits a wall - guides leveraging multiple AI models in parallel for better results

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1Download skill
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3Upload to Claude

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SKILL.md

name multi-ai-orchestration
description Use when stuck on complex problems, need architecture validation, want code review from multiple perspectives, or debugging hits a wall - guides leveraging multiple AI models in parallel for better results

Multi-AI Orchestration

When to Use

Trigger conditions:

  • Stuck after 2+ failed attempts
  • Architecture decisions with multiple valid approaches
  • Code review before major commits
  • Debugging with no clear root cause
  • Need validation from different reasoning styles

Quick Tools (Zero Setup)

Tool Models Best For
chat.lmstudio.ai Grok, Claude, Gemini, GPT-4o, Llama Parallel responses in 10 seconds
poe.com Multi-bot 10+ models Custom chains (Claude → Grok → Gemini)
ChatHub extension All major models One browser tab, one hotkey

Orchestration Patterns

Pattern 1: Parallel Fan-Out (Fastest)

When you need multiple perspectives quickly:

User problem → [Claude, Grok, Gemini] → Compare answers → Pick best

Use for: Architecture decisions, debugging hypotheses, API design choices

Pattern 2: Sequential Review Chain

When you need validation of work:

Claude writes code → Grok reviews → Gemini tests edge cases → Final version

Use for: Production code, critical bug fixes, security-sensitive changes

Pattern 3: Specialist Routing

Route based on problem type:

Problem Type Best Model
Complex reasoning Claude, o1
Code generation Grok, Claude
Quick lookups/facts Gemini, GPT-4o
Math/logic puzzles o1, DeepSeek-R1
Creative solutions Claude, Grok

Pattern 4: Debate Protocol

When models disagree:

  1. State the disagreement clearly
  2. Ask each model to steelman the other's position
  3. Ask for synthesis: "Given both perspectives, what's the best approach?"
  4. Human decides based on combined insight

Context Handoff Template

When passing context between models:

## Context
[Brief problem description - 2-3 sentences]

## What's Been Tried
- Approach 1: [result]
- Approach 2: [result]

## Current Best Hypothesis
[What the previous model concluded]

## What I Need From You
[Specific ask: validate, find holes, alternative approach, etc.]

Automation Options

10-minute setup:

  • Poe.com custom multi-bot
  • ChatHub browser extension

30-minute setup (fully automatic):

  • LangGraph / CrewAI (Python)
  • LazyLLM local orchestrator

Example CrewAI flow:

crew = Crew(
    agents=[
        Agent("Planner", model="grok"),
        Agent("Coder", model="claude"),
        Agent("Reviewer", model="gemini"),
        Agent("Tester", model="gpt-4o")
    ],
    process="sequential"  # or "parallel"
)

Anti-Patterns

Don't Do Instead
Copy-paste everything manually Use multi-chat tools
Ask same question to all models Specialize the ask per model
Ignore disagreements Use debate protocol
Over-orchestrate simple problems Single model is fine for routine tasks

When NOT to Use

  • Simple, well-defined tasks
  • Tasks one model handles confidently
  • Time-sensitive with clear solution path
  • Model-specific features (Claude artifacts, GPT DALL-E, etc.)

Integration with Other Skills

  • systematic-debugging: Fan out hypotheses to multiple models
  • react-architecture-enforcer: Get extraction plan validation
  • brainstorming: Parallel ideation across models
  • code-review: Multi-model review before merge