Agent-Skills.md

Agent Skills: Multi-AI Orchestration

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

UncategorizedID: DrSatsuma1/catherine-claude-skills/multi-ai-orchestration

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pnpm dlx add-skill https://github.com/DrSatsuma1/catherine-claude-skills/tree/HEAD/multi-ai-orchestration

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multi-ai-orchestration/SKILL.md

Skill Metadata

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