llm-council
Multi-agent planning council that orchestrates independent implementation plans, anonymizes them, then merges into one final plan.
- Supports configurable planner agents (Codex, Claude, Gemini, OpenCode, or custom CLI commands) running in parallel, with optional judge override
- Conducts structured intake questioning before plan generation to clarify ambiguities, constraints, and success criteria
- Produces validated Markdown outputs with automatic retry logic (up to 2 attempts) and failure handling across all agents
- Anonymizes and randomizes planner outputs before judging to reduce bias, then saves judge feedback and final merged plan to timestamped run directories
LLM Council Skill
Quick start
- Always check for an existing agents config file first (
$XDG_CONFIG_HOME/llm-council/agents.jsonor~/.config/llm-council/agents.json). If none exists, tell the user to run./setup.shto configure or update agents. - The orchestrator must always ask thorough intake questions first, then generates prompts so planners do not ask questions.
- Even if the initial prompt is strong, ask at least a few clarifying questions about ambiguities, constraints, and success criteria.
- Tell the user that answering intake questions is optional, but more detail improves the quality of the final plan.
- Use
python3 scripts/llm_council.py run --spec /path/to/spec.jsonto run the council. - Plans are produced as Markdown files for auditability.
- Run artifacts are saved under
./llm-council/runs/<timestamp>relative to the current working directory. - Configure defaults interactively with
python3 scripts/llm_council.py configure(writes$XDG_CONFIG_HOME/llm-council/agents.jsonor~/.config/llm-council/agents.json).
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