Mikeparcewski Wicked Garden Multi Model

Multi-Model Collaboration Skill

Orchestrate multi-model AI collaboration using external LLM CLIs. Each council member is a different model provider for genuine perspective diversity.

How It Works

The multi-model system uses external LLM CLIs discovered at runtime:

1. CLI Discovery — which codex copilot gemini opencode pi aider llm aichat goose detects installed CLIs
2. Quorum Check — Council requires 2+ external CLIs; 0 = refuse, 1 = warn
3. Question Scaffold — All models answer the same fixed 4-question set
4. Parallel Dispatch — Each CLI receives the scaffold via stdin pipe, runs independently
5. Synthesis — Claude synthesizes all perspectives with model attribution

Quick Start

# Council mode — dispatches to external CLIs in parallel
/jam:council "Should we use JWT or sessions for auth?"

# Quick jam — single model, 4 personas, fast
/jam:quick "How should we improve the visual design?"

# Full brainstorm — single model, 4-6 personas, 2-3 rounds
/jam:brainstorm "Architecture for the notification system"

Supported CLIs

Claude always participates as a council member alongside the external CLIs.

Architecture

┌─────────────────────────────────────────────────────┐
│  /jam:council Command                                │
│  - Parses topic, options, criteria                   │
│  - Dispatches to council agent                       │
├─────────────────────────────────────────────────────┤
│  Council Agent (agents/jam/council.md)               │
│  - Detects CLIs via `which`                          │
│  - Builds question scaffold (4 fixed questions)      │
│  - Pipes scaffold to each CLI in parallel            │
│  - Claude answers the same scaffold independently    │
├─────────────────────────────────────────────────────┤
│  External CLI Dispatch                               │
│  - cat scaffold.md | codex exec "..."                │
│  - cat scaffold.md | gemini "..."                    │
│  - cat scaffold.md | opencode run "..."              │
│  - pi -p "..." @scaffold.md                          │
│  - aider --message-file scaffold --no-git --yes     │
│  - cat scaffold.md | llm "..."                       │
│  - cat scaffold.md | aichat "..."                    │
│  - cat scaffold.md | goose run -i -                  │
├─────────────────────────────────────────────────────┤
│  Synthesis (3-stage)                                 │
│  - Stage 1: Raw responses per model                  │
│  - Stage 2: Synthesis matrix + risk convergence      │
│  - Stage 3: Verdict (consensus or fault lines)       │
└─────────────────────────────────────────────────────┘

Synthesis Framework

After gathering perspectives from different models, synthesize using:

Persistence

Automatic (via save_transcript.py)

Council responses are persisted as transcript entries:

• Each model's response stored with persona_type: council
• Synthesis appended as entry_type: synthesis
• Retrievable via /jam:transcript and /jam:thinking

Manual (via wicked-brain:memory)

Store decisions with full attribution:

Skill(skill="wicked-brain:memory", args="store \"Auth: JWT with 15min/7day expiry.\nConsensus: Claude, Gemini, Codex (idempotency critical).\nUnique: Gemini flagged session store scaling concern.\nDissent: none.\" --type decision --tags auth,multi-model-review")

When to Use Multi-Model

Fallback Behavior

If no external CLIs are detected, council refuses and suggests /jam:brainstorm (single-model, multi-persona) as an alternative. With only 1 CLI, it runs as "brainstorm with external guest" with a warning.

References

Orchestration:

• Orchestration Patterns — CLI dispatch, parallel execution, synthesis
• Context Management — Session state, cross-AI handoffs, context windows

CLI Providers:

• Codex | Copilot | Gemini | OpenCode | Pi
• Aider | llm | aichat | Goose

Quality:

• Auditability — Audit trails, compliance, decision tracking
• Examples — ADR templates, synthesis patterns, review templates

Source: mikeparcewski/wicked-garden — distributed by TomeVault.