How do I install the LLM Council skill?

Run npx skillmds@latest add majiayu000/llm-council in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is LLM Council safe to use?

This skill has not completed SkillMD's automated safety review yet. Independent scanners report: SkillSpector: PASS, Skill Scanner: PASS. Capability flags: docs only. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with LLM Council?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is LLM Council free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published LLM Council?

majiayu000 (@majiayu000) published this skill. Their other Agent Skills are listed on their SkillMD profile.

LLM Council by majiayu000 — Agent Skill

Name: LLM Council
Rating: 4.666666666666667 (3 reviews)
Author: majiayu000

File contents

Overview

LLM Council is a Skill that organizes multiple LLMs as "council members" and generates high-quality responses through a 3-stage process.

Use Cases

When you need multiple perspectives for important decisions
When you want multiple AIs to review code
When comparing and evaluating design proposals
When you need objective responses with reduced bias

3-Stage Process

Stage 1: Opinion Collection - Each member (LLM) responds independently
Stage 2: Peer Review - Anonymized responses are mutually ranked
Stage 3: Synthesis - Chairman integrates all opinions and reviews into final response

Quick Start

# Basic question
python scripts/run.py council_skill.py "What's the optimal caching strategy?"

# With TUI dashboard
python scripts/run.py cli.py --dashboard "What's the optimal caching strategy?"

# Code fix (diff only)
python scripts/run.py council_skill.py --dry-run "Fix the bug in buggy.py"

# Auto-merge
python scripts/run.py council_skill.py --auto-merge "Add error handling"

Command Options

Option	Description
`--dashboard`, `-d`	TUI dashboard for real-time monitoring
`--worktrees`	Git worktree mode - each member works independently
`--dry-run`	Show diff without merging
`--auto-merge`	Auto-merge the top-ranked proposal
`--merge N`	Merge member N's proposal
`--confirm`	Show confirmation prompt before merge
`--no-commit`	Apply changes without staging
`--list`	Show conversation history
`--continue N`	Continue conversation N

Setup

Create scripts/.env to configure models
Install and configure OpenCode CLI
Run python scripts/run.py council_skill.py --setup for details

Resources

See README.md for more details.

---name: llm-councildescription: Orchestrate multiple LLMs as a council, generating collective intelligence through peer review and chairman synthesis--- ## Overview LLM Council is a Skill that organizes multiple LLMs as "council members" and generates high-quality responses through a 3-stage process. ### Use Cases - When you need multiple perspectives for important decisions - When you want multiple AIs to review code - When comparing and evaluating design proposals - When you need objective responses with reduced bias ## 3-Stage Process 1. **Stage 1: Opinion Collection** - Each member (LLM) responds independently 2. **Stage 2: Peer Review** - Anonymized responses are mutually ranked 3. **Stage 3: Synthesis** - Chairman integrates all opinions and reviews into final response ## Quick Start ```bash # Basic question python scripts/run.py council_skill.py "What's the optimal caching strategy?" # With TUI dashboard python scripts/run.py cli.py --dashboard "What's the optimal caching strategy?" # Code fix (diff only) python scripts/run.py council_skill.py --dry-run "Fix the bug in buggy.py" # Auto-merge python scripts/run.py council_skill.py --auto-merge "Add error handling" ``` ## Command Options | Option | Description | |--------|-------------| | `--dashboard`, `-d` | TUI dashboard for real-time monitoring | | `--worktrees` | Git worktree mode - each member works independently | | `--dry-run` | Show diff without merging | | `--auto-merge` | Auto-merge the top-ranked proposal | | `--merge N` | Merge member N's proposal | | `--confirm` | Show confirmation prompt before merge | | `--no-commit` | Apply changes without staging | | `--list` | Show conversation history | | `--continue N` | Continue conversation N | ## Setup 1. Create `scripts/.env` to configure models 2. Install and configure OpenCode CLI 3. Run `python scripts/run.py council_skill.py --setup` for details ## Resources See `README.md` for more details.

Frequently asked questions

LLM Council