Orchestrate multiple AI models to analyze complex problems from different perspectives. This skill launches parallel agents to gather diverse viewpoints, then synthesizes findings into actionable recommendations.
When to Use
- Architectural decisions with significant trade-offs
- Complex debugging where root cause is unclear
- Design reviews where you want diverse perspectives
- Technology selection decisions
- Code review for critical or safety-sensitive changes
- Any problem where multiple viewpoints add value
Workflow
Phase 1: Problem Identification
Extract the core problem from the conversation:
- Identify the decision/challenge - What specific question needs analysis?
- Gather context - Read CLAUDE.md, relevant source files, and conversation history
- Note constraints - Time, resources, compatibility requirements, etc.
Summarize in 2-3 clear sentences.
Phase 2: Create Unified Prompt
Create ONE prompt that will be sent to all models. The prompt must be:
- Self-contained - Include all necessary context directly (don't rely on agents having access to files)
- Unbiased - Do NOT pre-bias external models with your opinions
- Structured - Clear sections for problem, context, constraints, and what you want analyzed
Prompt Template:
## Problem
[2-3 sentence description of the decision/challenge]
## Context
[Relevant technical details, code snippets, architecture info]
[Inject content from CLAUDE.md or relevant files directly]
## Constraints
[Time, compatibility, performance, safety requirements]
## Analysis Requested
Please analyze this problem and provide:
1. Your recommended approach with rationale
2. Key risks or concerns
3. Alternative approaches considered
4. Implementation considerations
Phase 3: Parallel Model Execution
Launch ALL THREE Task tools in a SINGLE response so they run in parallel:
1. Claude Critic (Sonnet)
Task tool with subagent_type: "general-purpose"
model: "sonnet"
prompt: [Your unified prompt + "Focus on critical analysis, edge cases, and potential failure modes."]
2. Gemini Analysis
Task tool with subagent_type: "Bash"
prompt: "Run: gemini '[Your unified prompt]' and return the full response"
3. Codex Analysis
Task tool with subagent_type: "Bash"
prompt: "Run: codex '[Your unified prompt]' and return the full response"
Important:
- All three must be launched in a SINGLE message with multiple tool calls
- Inject context directly into prompts - don't assume agents can read files
- Keep prompts identical for fair comparison
Phase 4: Synthesis
After all models respond, synthesize findings:
1. Consensus Points
- Where do all models agree?
- These are likely strong recommendations
2. Disagreements
- Where do models diverge?
- Analyze WHY they disagree
- Your role: decide which perspective is stronger given your full context
3. Blind Spots
- What did one model catch that others missed?
- These often surface valuable edge cases
4. Final Recommendation
- Integrate findings into a clear recommendation
- Acknowledge trade-offs
- Be specific about next steps
Error Handling
Models may fail due to:
- Authentication - Gemini/Codex may not be configured
- Timeouts - Long prompts may exceed limits
- Unavailability - External services may be down
When errors occur:
- Document which models succeeded/failed
- Continue analysis with available responses
- Note if a failed model might have provided unique perspective
Example
User asks: "Should we use WebSockets or SSE for real-time updates in the console?"
Phase 1 - Problem: "Deciding between WebSockets and Server-Sent Events for streaming rover telemetry to the depot console. Need bidirectional communication for teleop commands but also want simplicity for status updates."
Phase 2 - Prompt:
## Problem
Choosing between WebSockets and SSE for real-time communication in a robotics fleet management console. Need to stream telemetry from rovers and send teleop commands.
## Context
- React frontend with Zustand state management
- Rust backend services using Tokio
- Current: WebSocket for teleop, considering SSE for status updates
- ~10 rovers max per depot initially
- Telemetry at 10-30Hz, commands at 50Hz
## Constraints
- Must work through corporate proxies
- Need reconnection handling
- Mobile browser support required
- Latency-sensitive for teleop
## Analysis Requested
1. Recommended approach with rationale
2. Key risks or concerns
3. Alternative approaches
4. Implementation considerations
Phase 3 - Launch all three agents in parallel
Phase 4 - Synthesis: "All models agree WebSockets are necessary for teleop commands. Gemini suggested a hybrid approach: WebSocket for teleop, SSE for status monitoring. Codex raised proxy traversal concerns that weren't in the other responses. Recommendation: Keep WebSocket for all real-time communication for consistency, but implement proper reconnection handling as all models flagged this."
Best Practices
- Be specific - Vague problems get vague answers
- Include code - When relevant, include actual code snippets in prompts
- State constraints clearly - Models can't guess your requirements
- Don't over-synthesize - Preserve disagreements when they represent genuine trade-offs
- Act on findings - The value is in the decision, not the analysis
Limitations
- External models (Gemini, Codex) require CLI tools to be installed and authenticated
- Very long prompts may need to be trimmed
- Models may have different knowledge cutoffs
- Cost: Running three models is 3x the compute