PingPong Workflow

A pre-built 9-step workflow that orchestrates multi-model debate with analysis, challenge, and consensus phases. Four models collaborate to refine ideas through structured iteration.

What is PingPong?

PingPong is a YAML workflow that runs your question through 4 AI models (Grok, Gemini, Qwen, Perplexity) in 3 phases: initial analysis, critical challenge, and final consensus. Each model builds on previous outputs to refine solutions through structured debate.

How to Use

Execute the pingpong workflow using the workflow tool:

Or via Claude Code MCP:

Three-Phase Structure

Phase 1: Analysis (4 steps)

Each model analyzes your question independently from its unique perspective:

• Grok - First-principles reasoning
• Gemini - Creative brainstorming
• Qwen - Technical code-focused analysis
• Perplexity - Analytical reasoning with research

Phase 2: Challenge (4 steps)

Models critique and refine each other's analyses:

• Grok - Finds flaws, edge cases, hidden assumptions
• Gemini - Synthesizes analyses and proposes alternatives
• Qwen - Identifies technical risks and implementation challenges
• Perplexity - Research validation with current evidence

Phase 3: Consensus (1 step)

OpenAI GPT-5 compares all perspectives and generates final recommendation with consensus analysis.

Output Files

The workflow automatically saves all outputs to workflow-output/pingpong/<timestamp>/*.md:

• analyze-grok.md - Grok's initial analysis
• analyze-gemini.md - Gemini's brainstorming
• analyze-qwen.md - Qwen's technical perspective
• analyze-perplexity.md - Perplexity's research-backed analysis
• challenge-*.md - Critical refinements from each model
• consensus.md - Final multi-model comparison and recommendation

Required API Keys

The pingpong workflow requires all 4 provider API keys:

• XAI_API_KEY - For Grok reasoning
• GOOGLE_API_KEY - For Gemini analysis
• OPENROUTER_API_KEY - For Qwen coder
• PERPLEXITY_API_KEY - For research validation
• OPENAI_API_KEY - For final consensus (GPT-5)

Chaining with Other Workflows

Use pingpong's output as input to other workflows, or chain multiple analyses:

Or create a custom workflow that includes pingpong as a step:

Best Practices

• Clear, specific questions - Better input = better analysis across all 9 steps
• Review all phase outputs - Each model provides unique insights worth examining
• Focus on consensus.md - Final step synthesizes all perspectives with recommendations
• Cost awareness - 9 steps × 5 models = 45 API calls per workflow run
• Use for complex decisions - Architecture choices, technical tradeoffs, design debates

Example: Architecture Decision

Performance Notes