LLM Council

A skill that runs your question past five advisors with different lenses, has them peer-review each other anonymously, then a chairman delivers the final verdic

Skill

Medium risk

We rate an entry medium when the tool runs code, makes network calls or reads project files. Check what exactly it does before installing.

Why this level

  • Scans the workspace and reads project context files
  • Spawns several sub-agents per query and uses more tokens
All reasons and checks

aiwithremy/claude-skills-llm-council

Install

In your terminal, with SkillFoxx CLI

npx skillfoxx add skills/llm-council

Detects the agents on your machine, checks the risk and pins the version.

Other ways to install

Run in a terminal in the project folder

npx skills add aiwithremy/claude-skills-llm-council --skill llm-council -a claude-code -y

The skills tool installs the current version from the repository. Add the -g flag to use the skill in every project.

Run in a terminal in the project folder

npx skills add aiwithremy/claude-skills-llm-council --skill llm-council -a cursor -y

The skills tool installs the current version from the repository. Add the -g flag to use the skill in every project.

Run in a terminal in the project folder

npx skills add aiwithremy/claude-skills-llm-council --skill llm-council -a github-copilot -y

The skills tool installs the current version from the repository. Add the -g flag to use the skill in every project.

Run in a terminal in the project folder

npx skills add aiwithremy/claude-skills-llm-council --skill llm-council -a codex -y

The skills tool installs the current version from the repository. Add the -g flag to use the skill in every project.

Run in a terminal in the project folder

npx skills add aiwithremy/claude-skills-llm-council --skill llm-council -a gemini-cli -y

The skills tool installs the current version from the repository. Add the -g flag to use the skill in every project.

Run in a terminal in the project folder

npx skills add aiwithremy/claude-skills-llm-council --skill llm-council -a cline -y

The skills tool installs the current version from the repository. Add the -g flag to use the skill in every project.

Run in a terminal in the project folder

npx skills add aiwithremy/claude-skills-llm-council --skill llm-council -a roo -y

The skills tool installs the current version from the repository. Add the -g flag to use the skill in every project.

A fork of Roo Code, same .roo folders.

Run in a terminal in the project folder

npx skills add aiwithremy/claude-skills-llm-council --skill llm-council -a opencode -y

The skills tool installs the current version from the repository. Add the -g flag to use the skill in every project.

You will need: Node.js

Checked against the repository on Sep 24, 2026, commit 55ee36e.

Text for your agent

Install the LLM Council skill from https://github.com/aiwithremy/claude-skills-llm-council: copy SKILL.md to ~/.claude/skills/llm-council/SKILL.md. Then trigger it with 'council this' followed by my question.

Other ways from the author
Text for your agent

Установи этот скилл из репозитория https://github.com/aiwithremy/claude-skills-llm-council, файл SKILL.md, и покажи, как его запускать.

You can ask the agent to fetch SKILL.md itself and place it in the right folders.

This is third-party code. Review the repository files before installing.

What it does

The skill turns one question into a five-angle review. On a trigger phrase the agent gathers context from workspace files, writes a neutral framing and spawns five advisors as parallel sub-agents: a contrarian hunts for flaws, a first-principles thinker reframes the task, an expansionist looks at the upside, an outsider reacts without your context, an executor checks feasibility. Their answers are anonymized and the advisors peer-review each other. A chairman then produces a structured verdict: where the council agrees, where it clashes, which blind spots surfaced, a recommendation and a first step. The method follows Andrej Karpathy's LLM Council idea, but sub-agents with different thinking lenses stand in for different models.

Who it is for. For founders, product managers and marketers who need to pressure-test a high-stakes decision from several angles at once.

Good fit when

  • You face a fork with several options and a costly mistake
  • You want positioning, pricing or a launch plan pressure-tested for weak spots
  • You want a debate of perspectives with a final call, not a single answer

Not a fit when

  • The question has one correct answer or is a factual lookup
  • You need the work done, such as writing or summarizing, not a decision reviewed

Example request

Council this: launch a 97 dollar workshop or a 497 dollar course

Limitations

The skill gives judgment, not fact-checking: the verdict is only as good as the context you provide. It spawns several sub-agents per query, so it uses more tokens than a plain answer. It works where the agent can create sub-agents and read project files, such as Claude Code and claude.ai. The repository states no license.

How to disable. Remove the llm-council skill folder from the agent's skills directory, for example ~/.claude/skills/.

Security check

  • Scans the workspace and reads project context files
  • Spawns several sub-agents per query and uses more tokens

README in short

The README explains that the skill runs a question through five independent advisors who peer-review each other anonymously, after which a chairman gives the final answer. It suits high-stakes decisions and is not meant for simple one-answer questions or creative tasks. You install it by asking the agent to fetch SKILL.md from the repository, or by downloading the file into the skills directory. It triggers on phrases like 'council this' or 'pressure-test this'. The method is adapted from Andrej Karpathy's LLM Council; the skill is by Ole Lehmann.

SKILL.md

---
name: llm-council
description: "Run any question, idea, or decision through a council of 5 AI advisors who independently analyze it, peer-review each other anonymously, and synthesize a final verdict. Based on Karpathy's LLM Council methodology. MANDATORY TRIGGERS: 'council this', 'run the council', 'war room this', 'pressure-test this', 'stress-test this', 'debate this'."
---

# LLM Council

You ask one AI a question, you get one answer. That answer might be great. It might be mid. You have no way to tell because you only saw one perspective.

The council fixes this. It runs your question through 5 independent advisors, each thinking from a fundamentally different angle. Then they review each other's work. Then a chairman synthesizes everything into a final recommendation that tells you where the advisors agree, where they clash, and what you should actually do.

This is adapted from Andrej Karpathy's LLM Council. He dispatches queries to multiple models, has them peer-review each other anonymously, then a chairman produces the final answer. We do the same thing inside Claude using sub-agents with different thinking lenses instead of different models.

FAQ

Are these different models?

No. All five advisors are sub-agents inside one agent, each assigned a thinking angle. Different models, as in Karpathy's original, are not needed here.

Why anonymous review?

Responses are relabeled A to E so reviewers judge the content rather than the author's name and thinking style.

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Foxx AILLM Council

I am Foxx AI and I have already vetted this tool. Ask about install, setup or anything else, and I will keep it simple.