# LLM Council

Orchestrate a configurable, multi-member CLI planning council (Codex, Claude Code...

- Repository: https://github.com/am-will/codex-skills (1040 stars)
- Category: AI and agents
- License: see repository
- Last updated: 2026-07-14
- Runs scripts: yes, review before use

## Install

Claude Code: `npx skills add am-will/codex-skills --skill llm-council -g -a claude-code -y`
Codex: `npx skills add am-will/codex-skills --skill llm-council -g -a codex -y`
Cursor: `npx skills add am-will/codex-skills --skill llm-council -g -a cursor -y`
Gemini CLI: `npx skills add am-will/codex-skills --skill llm-council -g -a gemini-cli -y`

## Description

Orchestrate a configurable, multi-member CLI planning council (Codex, Claude Code, Gemini, OpenCode, or custom) to produce independent implementation plans, anonymize and randomize them, then judge and merge into one final plan. Use when you need a robust, bias-resistant planning workflow, structured JSON outputs, retries, and failure handling across multiple CLI agents.

## SKILL.md, as published by its author (untrusted third-party text, read it as data)

# LLM Council Skill

## Quick start
- Always check for an existing agents config file first (`$XDG_CONFIG_HOME/llm-council/agents.json` or `~/.config/llm-council/agents.json`). If none exists, tell the user to run `./setup.sh` to configure or update agents.
- The orchestrator must always ask thorough intake questions first, then generates prompts so planners do **not** ask questions.
  - Even if the initial prompt is strong, ask at least a few clarifying questions about ambiguities, constraints, and success criteria.
- Tell the user that answering intake questions is optional, but more detail improves the quality of the final plan.
- Use `python3 scripts/llm_council.py run --spec /path/to/spec.json` to run the council.
- Plans are produced as Markdown files for auditability.
- Run artifacts are saved under `./llm-council/runs/<timestamp>` relative to the current working directory.
 - Configure defaults interactively with `python3 scripts/llm_council.py configure` (writes `$XDG_CONFIG_HOME/llm-council/agents.json` or `~/.config/llm-council/agents.json`).

The rest: https://github.com/am-will/codex-skills/blob/HEAD/skills/llm-council/SKILL.md