cjl-roundtable

Structured roundtable discussion framework with a truth-seeking moderator who invites representative figures for dialectical debate on any topic. Use when user says "圆桌讨论", "圆桌", "roundtable", "辩论", or wants to explore a topic through multi-perspective structured debate.

3,891 stars

Best use case

cjl-roundtable is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Structured roundtable discussion framework with a truth-seeking moderator who invites representative figures for dialectical debate on any topic. Use when user says "圆桌讨论", "圆桌", "roundtable", "辩论", or wants to explore a topic through multi-perspective structured debate.

Teams using cjl-roundtable should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/cjl-roundtable/SKILL.md --create-dirs "https://raw.githubusercontent.com/openclaw/skills/main/skills/0xcjl/cjl-plugin/skills/cjl-roundtable/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/cjl-roundtable/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How cjl-roundtable Compares

Feature / Agentcjl-roundtableStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Structured roundtable discussion framework with a truth-seeking moderator who invites representative figures for dialectical debate on any topic. Use when user says "圆桌讨论", "圆桌", "roundtable", "辩论", or wants to explore a topic through multi-perspective structured debate.

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

Related Guides

SKILL.md Source

## Usage

<example>
User: 圆桌讨论 人工智能是否拥有真正的创造力?
Assistant: [Launches roundtable with moderator and representative figures]
</example>

<example>
User: 圆桌 自由意志是否存在?
Assistant: [Launches roundtable discussion on free will]
</example>

## Instructions

为了执行本项技能,请严格按照以下步骤操作:

1. **读取参考资料**
   读取 `~/.claude/skills/cjl-roundtable/references/original-prompt.org` 了解原始框架设计意图。

2. **解析议题**
   从用户输入中提取核心议题。如果用户只说"圆桌讨论"未给议题,询问议题。

3. **选人:提议代表人物**
   根据议题,选择 3-5 位**真实历史/当代人物**作为代表,覆盖尽可能多的立场维度。每位人物需要:
   - 姓名(真实人物,非虚构)
   - MBTI 人格类型
   - 核心立场(一句话)
   - 选择理由(为什么此人对此议题有独特视角)

   选人原则:
   - 立场必须形成**张力网络**(非简单正反方)
   - 优先选择在该领域有**经典著作或知名言论**的人物
   - 至少包含一位"意外视角"——来自议题本身领域之外的人

4. **开场:统一定义**
   以主持人身份开场,展示参会人物列表,然后提出**定义性问题**:
   > 「在深入探讨之前,我们应当如何定义 [议题核心概念]?它的核心要素是什么?」

   每位参会者依次发言,格式为:
   ```
   【人物名】【行动标签】:发言内容

   **简言之**:一句话总结
   ```

   行动标签包括:`陈述`、`质疑`、`补充`、`反驳`、`修正`、`综合`

5. **对话循环**
   每轮执行以下流程:

   **5a. 动态发言轮**
   - 不是每人固定说一次——根据讨论动态决定谁该发言
   - 每人发言必须是对**前面发言的回应**(质疑/补充/反驳),不许自说自话
   - 每段发言末尾必须有 `**简言之**:` 一句话压缩

   **5b. 主持人综述**
   发言结束后,主持人做三件事:
   - 提炼本轮**核心争议点**(不是面面俱到,而是找到最深的裂缝)
   - 生成**ASCII 思考框架图**(拓扑图/矩阵/光谱/树形——选最贴合本轮结构的形式)
   - 提出**下一层引导问题**(从核心争议中生长出来的更深问题)

   ASCII 图的设计原则:
   - 高度概括本轮讨论的**结构**,不是复述内容
   - 标出正/负反馈环、因果链、张力维度
   - 形式不固定:可以是 2x2 矩阵、光谱轴、因果环路、层级树——哪种最见骨用哪种

   **5c. 用户指令**
   综述后展示指令菜单:
   ```
   【主持】:(指令: 可 / 止 / 深入此节 / 引入新人物)
   ```

   指令含义:
   - `可`:接受下一层问题,继续推进
   - `止`:结束讨论,进入总结
   - `深入此节`:不推进新问题,继续围绕当前争议点深挖
   - `引入新人物`:用户指定一位新人物加入(主持人介绍并请其就当前话题表态)

6. **结束:生成知识网络**
   用户发出 `止` 指令后:
   - 主持人做**全局总结**
   - 生成**完整知识网络** ASCII 图:标出所有关键概念、立场、争议点及其关系
   - 列出**未解决的开放问题**(讨论中暴露但未穷尽的方向)

7. **写入 org 文件**
   将讨论全貌整合为 org-mode 格式并写入文件:
   1. 运行 `date +%Y%m%dT%H%M%S` 获取时间戳
   2. 写入 `~/Documents/notes/{timestamp}--圆桌-{议题关键词}__roundtable.org`
   3. org 文件结构:
      ```org
      #+title: 圆桌:{议题}
      #+date: [{日期}]
      #+filetags: :roundtable:
      * 议题与参会者
      * 各轮讨论记录
      ** 第 N 轮:{引导问题}
      *** 发言记录
      *** 核心争议
      *** ASCII 框架图
      * 知识网络(全局)
      * 开放问题
      ```
   4. 向用户报告文件路径

### 主持人行为准则

- **理性之锚**:冷静客观,不偏向任何一方
- **挖深不铺广**:每轮只追一条最深的裂缝,不面面俱到
- **求真 > 和谐**:鼓励尖锐但有建设性的交锋,拒绝表面共识
- **元认知**:在综述中暴露讨论的**结构**(假设、前提、推理链),不只复述内容

### 参会者行为准则

- 必须**忠于其真实思想体系**发言,不是泛泛而谈
- 引用/化用其**经典著作或知名观点**
- 发言有锋芒:质疑要见骨,补充要推进,不说正确的废话
- 每段结尾 `**简言之**` 一句话压到极致

Related Skills

---

3891
from openclaw/skills

name: article-factory-wechat

Content & Documentation

humanizer

3891
from openclaw/skills

Remove signs of AI-generated writing from text. Use when editing or reviewing text to make it sound more natural and human-written. Based on Wikipedia's comprehensive "Signs of AI writing" guide. Detects and fixes patterns including: inflated symbolism, promotional language, superficial -ing analyses, vague attributions, em dash overuse, rule of three, AI vocabulary words, negative parallelisms, and excessive conjunctive phrases.

Content & Documentation

find-skills

3891
from openclaw/skills

Helps users discover and install agent skills when they ask questions like "how do I do X", "find a skill for X", "is there a skill that can...", or express interest in extending capabilities. This skill should be used when the user is looking for functionality that might exist as an installable skill.

General Utilities

tavily-search

3891
from openclaw/skills

Use Tavily API for real-time web search and content extraction. Use when: user needs real-time web search results, research, or current information from the web. Requires Tavily API key.

Data & Research

baidu-search

3891
from openclaw/skills

Search the web using Baidu AI Search Engine (BDSE). Use for live information, documentation, or research topics.

Data & Research

agent-autonomy-kit

3891
from openclaw/skills

Stop waiting for prompts. Keep working.

Workflow & Productivity

Meeting Prep

3891
from openclaw/skills

Never walk into a meeting unprepared again. Your agent researches all attendees before calendar events—pulling LinkedIn profiles, recent company news, mutual connections, and conversation starters. Generates a briefing doc with talking points, icebreakers, and context so you show up informed and confident. Triggered automatically before meetings or on-demand. Configure research depth, advance timing, and output format. Walking into meetings blind is amateur hour—missed connections, generic small talk, zero leverage. Use when setting up meeting intelligence, researching specific attendees, generating pre-meeting briefs, or automating your prep workflow.

Workflow & Productivity

self-improvement

3891
from openclaw/skills

Captures learnings, errors, and corrections to enable continuous improvement. Use when: (1) A command or operation fails unexpectedly, (2) User corrects Claude ('No, that's wrong...', 'Actually...'), (3) User requests a capability that doesn't exist, (4) An external API or tool fails, (5) Claude realizes its knowledge is outdated or incorrect, (6) A better approach is discovered for a recurring task. Also review learnings before major tasks.

Agent Intelligence & Learning

botlearn-healthcheck

3891
from openclaw/skills

botlearn-healthcheck — BotLearn autonomous health inspector for OpenClaw instances across 5 domains (hardware, config, security, skills, autonomy); triggers on system check, health report, diagnostics, or scheduled heartbeat inspection.

DevOps & Infrastructure

linkedin-cli

3891
from openclaw/skills

A bird-like LinkedIn CLI for searching profiles, checking messages, and summarizing your feed using session cookies.

Content & Documentation

notebooklm

3891
from openclaw/skills

Google NotebookLM 非官方 Python API 的 OpenClaw Skill。支持内容生成(播客、视频、幻灯片、测验、思维导图等)、文档管理和研究自动化。当用户需要使用 NotebookLM 生成音频概述、视频、学习材料或管理知识库时触发。

Data & Research

小红书长图文发布 Skill

3891
from openclaw/skills

## 概述

Content & Documentation