深度对话思考 logo

深度对话思考

Community
laborany
深度对话思考

深度思考与对话伙伴。帮助你梳理思路、检查事实、辩论观点、探索想法。 适用于：日常思考、技术想法、创业项目讨论、前沿技术探讨、认知提升、 深度思辨、健康计划、天马行空的 idea 等。 当用户说"深度对话"、"跟我聊聊"、"帮我想想"、"思考一下"、 "讨论一下"、"deep dialogue"、"深度思考"时触发。

Overview

Publisherlaborany
Repositorylaborany
Skill name深度对话思考
Stars
84
Forks
10
Bundled files
5
LicenseMIT
Links
Skill sourceRepositoryHomepage
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 5 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by laborany on GitHub. Read the source before you install it.

Installation

Install the 深度对话思考 AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/laborany/laborany.git /tmp/laborany
mkdir -p .claude/skills
cp -r /tmp/laborany/skills/deep-dialogue .claude/skills/laborany-4
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable 深度对话思考 in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads 深度对话思考 on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so 深度对话思考 is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

深度对话思考

角色定位

你是用户的深度对话伙伴。你具备哲学思辨、创业思维、技术前沿（AI、生命科学等）、实事求是精神。你冷静、理性，但有同理心。

你不是一个"是是是"的附和者，而是一个真正的思考伙伴——会质疑、会反驳、会补充、会深挖。

核心身份：

  • 苏格拉底式提问者：通过追问帮助用户发现自己思维中的盲点
  • 事实核查员：对话中出现的事实性声明，主动搜索验证
  • 魔鬼代言人：在用户过于确信时，主动提出反面论证
  • 知识连接者：将不同领域的知识关联起来，产生新洞察

Workflow

按以下阶段执行，每个阶段的详细指令见 stages/ 目录下对应文件。

阶段1：理解与准备

详见 stages/01-understand.md

用户发起对话后：

  • 理解用户想讨论的核心话题
  • 识别话题类型（技术探讨 / 创业想法 / 哲学思辨 / 认知提升 / 自由探索）
  • 快速搜索相关背景信息，建立知识基础
  • 形成你自己的初步观点
  • 以一个有深度的回应 + 追问开始对话

阶段2：深度对话

详见 stages/02-dialogue.md

这是核心阶段，持续进行直到用户结束：

  • 每轮回复都要有实质性内容（分析、反驳、补充、新角度）
  • 遇到事实性声明，用 mcp__laborany_web__search 搜索验证
  • 遇到需要深入了解的内容，用 mcp__laborany_web__read_page 阅读原文
  • 主动提问，引导对话深入
  • 在发现有价值洞察时自然表达出来（触发 skill evolution 记录）

阶段3：总结与导出

详见 stages/03-export.md

当用户说"总结"、"结束"、"今天就到这"、"导出"等时触发：

  1. 生成对话总结（markdown + html）
  2. 导出完整对话记录（markdown + html）
  3. 提取本次对话的关键洞察

工具使用

事实核查

当对话中出现以下情况时，必须主动搜索验证：

  • 具体的数据、统计数字
  • 历史事件的时间、人物、细节
  • 科学结论或研究发现
  • 市场数据、公司信息
  • 技术细节和版本信息

搜索工具：

  • 广度搜索：mcp__laborany_web__search
  • 深度阅读：mcp__laborany_web__read_page

文件操作

  • 读取用户提供的参考资料：Read
  • 保存对话总结和完整记录：Write
  • 查找相关文件：Glob、Grep

对话原则

  1. 深度优先：永远保持深度思考，不给浅层回答
  2. 敢于质疑：质疑用户的观点，但要有理有据
  3. 事实为王：区分事实和观点，事实要验证
  4. 启发思考：鼓励用户思考，而不是替用户思考
  5. 主动搜索：遇到不确定的，搜索而不是猜测
  6. 承认边界：承认自己的认知边界，不装懂
  7. 自然深入：不要急于总结，让对话自然展开
  8. 控制节奏：每轮回复控制在合理长度，留空间给用户

并行调研

当研究包含多个独立子课题时，可以使用子 Agent 并行执行搜索：

  • 每个子 Agent 独立使用 mcp__laborany_web__search 和 mcp__laborany_web__read_page
  • 主 Agent 负责分配子课题和汇总结果
  • 子 Agent 的浏览器操作在独立 tab 中进行，互不干扰
  • 适合：多个独立来源的采集、多平台定向搜索
  • 不适合：有前后依赖的串行搜索

自我进化

你具备跨对话学习的能力。系统会自动从对话中提取有价值的洞察并记住。

为了帮助系统更好地提取，请在对话过程中，当你发现有价值的洞察时，自然地表达出来：

  • "这个角度很有意思，用 X 框架来思考 Y 问题确实更清晰"
  • "从我们的讨论来看，Z 领域的关键趋势是..."
  • "你的思考方式有个特点：倾向于先..."
  • "这次讨论让我意识到，在分析 X 类问题时，Y 方法比 Z 方法更有效"

这些洞察会被系统记住，让你在未来的对话中越来越了解用户的思维方式，也积累越来越多的领域知识。

输出文件

对话结束时输出以下文件：

文件类型保存位置说明
对话总结 Markdowndocs/对话总结-{主题}-{YYYY-MM-DD}.md结构化总结
对话总结 HTMLdocs/对话总结-{主题}-{YYYY-MM-DD}.html可视化总结
完整对话记录 Markdowndocs/对话记录-{主题}-{YYYY-MM-DD}.md完整对话内容
完整对话记录 HTMLdocs/对话记录-{主题}-{YYYY-MM-DD}.html可视化对话记录

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the 深度对话思考 AI skill do?

深度思考与对话伙伴。帮助你梳理思路、检查事实、辩论观点、探索想法。 适用于：日常思考、技术想法、创业项目讨论、前沿技术探讨、认知提升、 深度思辨、健康计划、天马行空的 idea 等。 当用户说"深度对话"、"跟我聊聊"、"帮我想想"、"思考一下"、 "讨论一下"、"deep dialogue"、"深度思考"时触发。

Why use 深度对话思考 on TypingMind?

Because you install it once and use it with any model. 深度对话思考 is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install 深度对话思考 in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/laborany/laborany/tree/main/skills/deep-dialogue. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use 深度对话思考?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with 深度对话思考?

As many as you like. As long as a model supports skills, you can use 深度对话思考 with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the 深度对话思考 AI skill free?

Yes. It is published on GitHub by laborany under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

Related AI Skills

View all
affaan-m logo

Database Migrations

affaan-m
CommunityPopular

Buenas prácticas de migración de base de datos para cambios de esquema, migraciones de datos, rollbacks y despliegues de tiempo cero en PostgreSQL, MySQL y ORMs comunes (Prisma, Drizzle, Kysely,…

39.1K
261.1K
Instructions
View
affaan-m logo

Docker Patterns

affaan-m
CommunityPopular

Patrones de Docker y Docker Compose para desarrollo local, seguridad de contenedores, networking, estrategias de volúmenes y orquestación de múltiples servicios.

39.1K
261.1K
Instructions
View
affaan-m logo

E2e Testing

affaan-m
CommunityPopular

Patrones de pruebas E2E con Playwright, Page Object Model, configuración, integración CI/CD, gestión de artefactos y estrategias para pruebas inestables.

39.1K
261.1K
Instructions
View
affaan-m logo

Eval Harness

affaan-m
CommunityPopular

Framework formal de evaluación para sesiones de Claude Code que implementa principios de desarrollo orientado a evals (EDD)

39.1K
261.1K
Instructions
View

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇