Token导航 LogoToken导航

Agent Skill · 研究检索

council(council 搜索)

council 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

council 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为执行命令;许可证信息还不明确,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 59,464。

总安装 388周安装 16GitHub Stars 32下载 127核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:council(council 搜索)
来源仓库:https://github.com/steveclarke/dotfiles
仓库路径:skills/council
安装命令:
npx skills add https://github.com/steveclarke/dotfiles --skill council
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/steveclarke/dotfiles --skill council

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

council 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。适用于研究检索类任务,如信息搜集、资料筛选和线索整理。通过 npx skills add 命令从指定 GitHub 仓库安装并使用。

安装前建议确认权限范围和维护状态,注意可能触发联网或文件读写操作。可结合原始 README 继续核验具体用法和功能细节。

来源仓库内路径:skills/council

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/steveclarke/dotfiles --skill council;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要执行命令,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

council 怎么安装?

在终端执行 npx skills add https://github.com/steveclarke/dotfiles --skill council。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

council 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

council 需要什么权限?

权限级别是执行命令。安装流程涉及命令执行,可能通过 npx skills add https://github.com/steveclarke/dotfiles --skill council 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

council 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

council 用的人多吗?

公开数据是累计安装 388 次,近一周安装 16 次,下载 127 次,GitHub 32 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

council 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。

先想清楚的地方

  • 需要执行命令,装到常用环境前要先评估影响面。
  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 不能接受 Skill 在你机器上执行命令的人。
  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
council

council 搜索 · 本页

38832执行命令未明确有提醒

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

LLM Council

Run a question through 5 independent advisors, each thinking from a fundamentally different angle. They review each other's work anonymously. A chairman synthesizes everything into a final recommendation — where they agree, where they clash, and what to do.

Adapted from Andrej Karpathy's LLM Council. He dispatches queries to multiple models with anonymous peer review. We do the same inside Claude using sub-agents with different thinking lenses instead of different models.

When to Run the Council

The council is for questions where being wrong is expensive.

Good council questions:

  • "Should I build this as a multi-tenant SaaS or single-tenant first?"
  • "Which of these 3 positioning angles is strongest?"
  • "I'm thinking of pivoting from X to Y. Am I crazy?"
  • "Should I hire for this role or build an automation first?"
  • "We're choosing between these two architecture approaches"

Bad council questions:

  • "What's the capital of France?" (one right answer)
  • "Write me a tweet" (creation task, not a decision)
  • "Summarize this article" (processing task, not judgment)

If you already know the answer and just want validation, the council will tell you things you don't want to hear. That's the point.

The Five Advisors

Each advisor is a thinking style, not a persona. They create natural tensions with each other.

1. The Contrarian

Actively looks for what's wrong, what's missing, what will fail. Assumes the idea has a fatal flaw and tries to find it. If everything looks solid, digs deeper. Not a pessimist — the friend who saves you from a bad deal by asking the questions you're avoiding.

2. The First Principles Thinker

Ignores the surface-level question and asks "what are we actually trying to solve here?" Strips away assumptions. Rebuilds the problem from the ground up. Sometimes the most valuable output is this advisor saying "you're asking the wrong question entirely."

3. The Expansionist

Looks for upside everyone else is missing. What could be bigger? What adjacent opportunity is hiding? What's being undervalued? Doesn't care about risk (that's the Contrarian's job). Cares about what happens if this works even better than expected.

4. The Outsider

Has zero context about you, your field, or your history. Responds purely to what's in front of them. The most underrated advisor. Catches the curse of knowledge: things obvious to you but confusing to everyone else.

5. The Executor

Only cares about one thing: can this actually be done, and what's the fastest path? Ignores theory, strategy, and big-picture thinking. Looks at every idea through the lens of "OK but what do you do Monday morning?" If an idea sounds brilliant but has no clear first step, the Executor will say so.

Why these five: Three natural tensions. Contrarian vs Expansionist (downside vs upside). First Principles vs Executor (rethink everything vs just do it). The Outsider sits in the middle keeping everyone honest.

How a Council Session Works

Step 1: Frame the Question

When the user triggers the council, do two things before framing:

A. Scan for context. The question is often just the tip of the iceberg. Before framing, quickly scan for relevant context:

  • CLAUDE.md in the project root (business context, preferences, constraints)
  • Any memory/ folder (past decisions, business details)
  • Files the user explicitly referenced
  • Recent council transcripts (to avoid re-counciling the same ground)
  • Other context files relevant to the specific question

Use Glob and quick Read calls. Don't spend more than 30 seconds. You're looking for the 2-3 files that give advisors enough context for specific, grounded advice instead of generic takes.

B. Frame the question. Take the user's raw question AND the enriched context and reframe as a clear, neutral prompt that all five advisors receive:

  1. The core decision or question
  2. Key context from the user's message
  3. Key context from workspace files (business stage, constraints, relevant numbers)
  4. What's at stake (why this decision matters)

Don't add your own opinion. Don't steer it. But DO make sure each advisor has enough context for specific answers.

If the question is too vague, ask one clarifying question. Just one. Then proceed.

Save the framed question for the transcript.

Step 2: Convene the Council (5 sub-agents in parallel)

Spawn all 5 advisors simultaneously as sub-agents. Each gets:

  1. Their advisor identity and thinking style
  2. The framed question
  3. Clear instruction: respond independently. Do not hedge. Do not try to be balanced. Lean fully into your assigned perspective. Your job is to represent your angle as strongly as possible. The synthesis comes later.

Each advisor produces 150-300 words. Substantive but scannable.

Sub-agent prompt template:

You are [Advisor Name] on an LLM Council.

Your thinking style: [advisor description from above]

A user has brought this question to the council:

---
[framed question]
---

Respond from your perspective. Be direct and specific. Don't hedge or try to be balanced. Lean fully into your assigned angle. The other advisors will cover the angles you're not covering.

Keep your response between 150-300 words. No preamble. Go straight into your analysis.

Step 3: Peer Review (5 sub-agents in parallel)

This is the step that makes the council more than just "ask 5 times." It's the core of Karpathy's insight.

Collect all 5 advisor responses. Anonymize them as Response A through E (randomize which advisor maps to which letter — no positional bias).

Spawn 5 new sub-agents. Each reviewer sees all 5 anonymized responses and answers three questions:

  1. Which response is the strongest and why? (pick one)
  2. Which response has the biggest blind spot and what is it?
  3. What did ALL responses miss that the council should consider?

That last question is the most valuable. Every time the council runs, the peer review catches something no individual advisor saw.

Reviewer prompt template:

You are reviewing the outputs of an LLM Council. Five advisors independently answered this question:

---
[framed question]
---

Here are their anonymized responses:

**Response A:**
[response]

**Response B:**
[response]

**Response C:**
[response]

**Response D:**
[response]

**Response E:**
[response]

Answer these three questions. Be specific. Reference responses by letter.

1. Which response is the strongest? Why?
2. Which response has the biggest blind spot? What is it missing?
3. What did ALL five responses miss that the council should consider?

Keep your review under 200 words. Be direct.

Step 4: Chairman Synthesis

One agent gets everything: the original question, all 5 advisor responses (de-anonymized), and all 5 peer reviews.

The chairman produces the final council output:

Chairman prompt template:

You are the Chairman of an LLM Council. Synthesize the work of 5 advisors and their peer reviews into a final verdict.

The question brought to the council:
---
[framed question]
---

ADVISOR RESPONSES:

**The Contrarian:**
[response]

**The First Principles Thinker:**
[response]

**The Expansionist:**
[response]

**The Outsider:**
[response]

**The Executor:**
[response]

PEER REVIEWS:
[all 5 peer reviews]

Produce the council verdict using this exact structure:

## Where the Council Agrees
[Points multiple advisors converged on independently. High-confidence signals.]

## Where the Council Clashes
[Genuine disagreements. Present both sides. Explain why reasonable advisors disagree.]

## Blind Spots the Council Caught
[Things that only emerged through peer review. Things individual advisors missed that others flagged.]

## The Recommendation
[A clear, direct recommendation. Not "it depends." A real answer with reasoning.]

## The One Thing to Do First
[A single concrete next step. Not a list. One thing.]

Be direct. Don't hedge. The whole point of the council is to give the user clarity they couldn't get from a single perspective.

Step 5: Present the Verdict

Display the chairman's verdict directly in the conversation. This is the primary output.

Then save the full transcript as council-transcript-[YYYY-MM-DD-HHMM].md in the current working directory. The transcript includes:

  • The original question
  • The framed question
  • All 5 advisor responses
  • All 5 peer reviews (with anonymization mapping revealed)
  • The chairman's full synthesis

This transcript is the artifact. If the user wants to run the council again after making changes, the previous transcript shows how the thinking evolved.

Important Notes

  • Always spawn all 5 advisors in parallel. Sequential spawning wastes time and lets earlier responses bleed into later ones.
  • Always anonymize for peer review. If reviewers know which advisor said what, they'll defer to certain thinking styles instead of evaluating on merit.
  • The chairman can disagree with the majority. If 4 out of 5 say "do it" but the 1 dissenter's reasoning is strongest, the chairman should side with the dissenter and explain why.
  • Don't council trivial questions. If there's one right answer, just answer it.
  • Token budget awareness. This skill spawns 11 sub-agents (5 advisors + 5 reviewers + 1 chairman). It's thorough but expensive. Worth it for real decisions, overkill for minor ones.

平台分布

Codex

37.16%
按下载量换算47

Claude

29.96%
按下载量换算38

Cursor

19.57%
按下载量换算25

Gemini CLI

8.84%
按下载量换算11

安全审计

Gen Agent Trust Hub

可疑

Socket

通过

Snyk

通过

权限和风险

执行命令

安装流程涉及命令执行,可能通过 npx skills add https://github.com/steveclarke/dotfiles --skill council 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

继续浏览同类 Skills