Setup & Installation
Or with the ClawHub CLI, for registry-managed skill folders outside a full OpenClaw workspace:
What This Skill Does
LLM Council runs one question through multiple AI models, has them critique each other's answers, and produces a synthesized consensus response. A single command clones the repo, installs dependencies, resolves credentials, and starts a React/Vite frontend with a FastAPI backend. No manual API key prompts — credentials are read from environment, workspace .env, or the OpenClaw local gateway automatically.
Unlike manually querying multiple model APIs and reconciling results yourself, the chairman synthesis step produces a single reconciled answer from all participating models in one UI.
When to use it
- Comparing how different models answer a disputed technical question
- Getting a synthesized consensus before making an architectural decision
- Exploring where models diverge on ambiguous or opinion-heavy prompts
- Running a multi-model critique session without configuring each provider manually
- Replacing a single-model chat with a panel review for high-stakes writing
Example Workflow
Here's how your AI assistant might use this skill in practice.
User runs: /install-llm-council
- 1Run install.sh from the skill directory
- 2Script resolves OPENROUTER_API_KEY from env, workspace .env, or OpenClaw gateway token
- 3Clone or update jeadland/llm-council repo to ~/workspace/llm-council
- 4Run uv sync for Python backend deps and npm ci for frontend, then write .env
- 5Start FastAPI backend on port 8001 and Vite dev server on port 5173 with health checks
LLM Council running at http://10.0.1.42:5173 — user opens browser and submits a question to multiple models
Requirements
Accounts, API keys, or tools you or your AI assistant may need to set up while using this skill.