orchestra

name	orchestra
description	Round-robin multi-LLM consultation with full-context debate. GPT proposes, Gemini refines, Grok challenges — each sees the full chain including wheat/chaff verdicts and justifications. Nothing is filtered between rounds.
version	1.0.0

The Orchestra — Round-Robin Multi-LLM Debate

Ask the orchestra. Let them debate. Take what survives.

Usage

/orchestra "task description"

Mode: recipe (auto-detected from this repository) Domain: recipe aggregation and cross-collection features

How It Works

Unlike /orchestrate (linear pipeline), /orchestra runs a round-robin debate where each model sees EVERYTHING from prior rounds — proposals, verdicts, justifications, and rejections. Nothing is filtered. What one model calls chaff, the next might rescue.

cd /home/user/ken/orchestrator && python3 orchestra.py recipe "task description"

The Rounds

Round 1: GPT Proposes

• Receives: task + relevant memories
• Produces: proposals (with confidence + justification), low-hanging fruit

Round 2: Gemini Refines

• Receives: task + GPT's FULL response
• For each GPT proposal: WHEAT | CHAFF | WHEAT_WITH_REFINEMENT (with justification)
• Adds own proposals + low-hanging fruit
• May rescue ideas it thinks GPT undervalued

Round 3: Grok Challenges

• Receives: task + GPT's FULL response + Gemini's FULL response (including verdicts)
• For EVERY prior proposal: verdict + justification
• Specifically looks for dismissed ideas worth rescuing
• Adds own proposals + identifies blind spots + low-hanging fruit

Blind Spot Check

• The most contrarian model (Grok) reviews the emerging synthesis
• "What is the single most important thing we're all still missing?"

Claude Synthesizes

• Sees the full debate chain: every proposal, every verdict, every justification
• Produces attributed plan: "GPT proposed X, Gemini refined to Y, Grok challenged Z"
• Encodes key decisions to cognitive-memory

Why Full Context Matters

If Claude filters between rounds, rejected ideas die silently. With full context:

• Gemini can disagree with GPT's reasoning, not just its conclusions
• Grok can rescue an idea Gemini dismissed, explaining WHY Gemini was wrong
• The final synthesis is informed by the debate, not just the survivors

Cost Reporting

Every run reports:

• Per-round costs (model, tokens, dollars)
• Total pipeline cost
• Idea survival rate (wheat vs chaff vs rescued)
• Low-hanging fruit from all models

Typical cost: $0.03–$0.08 per full orchestra run.

Integration

• cognitive-memory — recalls relevant memories before Round 1, encodes decisions after
• consult — for quick single-model questions (use /orchestra for the full debate)
• orchestrate — the older linear pipeline (still available for simpler tasks)

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Soli Deo Gloria — Let the orchestra play. Take what glorifies God.