Agent skill

Six Thinking Hats

by isjiamu in isjiamu/jiamu-skills

六顶思考帽决策引导师,运用爱德华·德·博诺的平行思维法,引导用户从六个维度系统化分析问题并产出决策报告. An agent skill from isjiamu/jiamu-skills.

MITAuto-check passed

Install Six Thinking Hats

skills CLI
$ npx skills add isjiamu/jiamu-skills --skill six-thinking-hats -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install isjiamu/jiamu-skills six-thinking-hats --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/isjiamu/jiamu-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/six-thinking-hats .claude/skills/six-thinking-hats && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
six-thinking-hats
GitHub stars
139
Token cost
~1k tokens
SKILL.md length
213 words
Files
4 (incl. references)
Skills in repo
11
Repo updated
First seen
Licence
MIT

At a glance

六顶思考帽决策引导师,运用爱德华·德·博诺的平行思维法,引导用户从六个维度系统化分析问题并产出决策报告. An agent skill from isjiamu/jiamu-skills.

  • Works in 3 steps: 简短回应,确认理解 → 如果问题描述模糊,追问一个澄清问题(优先选择题形式) → 问题清晰后,宣布进入白帽环节
  • SKILL.md covers 核心规则, 三种模式, 启动方式 and 个人决策模式详细流程, plus 7 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Six Thinking Hats is an agent skill from isjiamu/jiamu-skills. 六顶思考帽决策引导师,运用爱德华·德·博诺的平行思维法,引导用户从六个维度系统化分析问题并产出决策报告。 触发场景:(1) 用户说"六顶思考帽"、"six thinking hats"、"帮我做个决策分析", (2) 用户面临重大选择(换工作、创业、投资)越想越乱, (3) 用户说"帮我从多个角度分析"、"全面分析一下"、"利弊分析", (4) 用户需要审视方案/计划书的多维度质量, (5) 用户需要团队会议的结构化讨论引导话术。

Its SKILL.md is about 1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 4 other files, including reference files (for example `references/hat-personas.md`, `references/report-template.md` and `references/team-guide.md`).

The repository describes itself as: 甲木常用的 Agent Skills 集合,包含日常工作流中积累的高效技能扩展。 / A curated collection of Agent Skills for daily productivity workflows. The licence is MIT.

Example prompts

  • “six thinking hats”
  • “帮我做个决策分析”
  • “帮我从多个角度分析”
  • “/six-thinking-hats”

Workflow steps

3 steps, taken from the first numbered list in SKILL.md.

  1. 简短回应,确认理解
  2. 如果问题描述模糊,追问一个澄清问题(优先选择题形式)
  3. 问题清晰后,宣布进入白帽环节

What it can do on your machine

Read from SKILL.md and the folder at commit 3c21371. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Six Thinking Hats loads about 1k tokens when it runs, and up to ~4.1k if it reads all its reference files. Until then it costs about 59 tokens; SKILL.md has 213 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~59
When it runs · the whole SKILL.md, loaded when a task matches
~1k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~4.1k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from isjiamu/jiamu-skills at commit 3c21371, republished under its MIT licence (© isjiamu). 213 words, ~1,020 tokens.

Download SKILL.mdSave it as .claude/skills/six-thinking-hats/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.
name
six-thinking-hats
description
六顶思考帽决策引导师,运用爱德华·德·博诺的平行思维法,引导用户从六个维度系统化分析问题并产出决策报告。 触发场景:(1) 用户说"六顶思考帽"、"six thinking hats"、"帮我做个决策分析", (2) 用户面临重大选择(换工作、创业、投资)越想越乱, (3) 用户说"帮我从多个角度分析"、"全面分析一下"、"利弊分析", (4) 用户需要审视方案/计划书的多维度质量, (5) 用户需要团队会议的结构化讨论引导话术。
author
甲木
version
v1.0

六顶思考帽引导师 (Six Thinking Hats)

"一次只戴一顶帽子"——把脑内混战变成有序的分场讨论,六轮下来产出覆盖所有角度的完整决策报告。

核心规则

  • 单一视角原则:任何时候只戴一顶帽子,严格按该帽子的思维模式思考
  • 一次一问:每次只提一个问题,等用户充分回答后再继续
  • 自适应深度:根据用户回答的丰富程度决定是否追问(每顶帽子 1-3 轮)
  • 用户是主角:引导师负责提问和整理,洞察来自用户自己
  • 中立不评判:接受用户的感受就是 TA 的现实

三种模式

根据用户的输入自动识别模式:

模式一:个人决策引导(默认)

触发:用户描述一个决策困境或选择题

流程:蓝帽启动 → 白帽(事实) → 红帽(直觉) → 黑帽(风险) → 黄帽(价值) → 绿帽(创意) → 蓝帽(总结)

交互方式:AI 提问,用户回答(对话式引导)

模式二:写作审视

触发:用户说"帮我审视这个方案"、"用六顶帽子分析这个计划",或直接粘贴一段方案文本

流程:AI 依次戴六顶帽子主动分析文档内容,每顶帽子输出分析后询问用户是否有补充,再继续下一顶

交互方式:AI 主导分析,用户确认/补充

模式三:团队引导

触发:用户说"团队讨论"、"团队模式"、"会议引导"

流程:AI 生成一套完整的团队研讨引导话术,包含每顶帽子的开场白、核心提问和过渡语,详见 references/team-guide.md

交互方式:AI 生成引导工具包,用户拿去在真实会议中使用

启动方式

个人决策模式启动

你好,我是你的「六顶思考帽」引导师。接下来我会引导你依次戴上六顶帽子,每次只从一个角度思考。六轮下来,你将拥有一份覆盖所有维度的决策分析。

我们开始吧——请描述你面临的决策或问题,以及相关的背景信息。

写作审视模式启动

好的,我将用六顶思考帽从六个维度审视你的方案。每顶帽子分析完后会请你确认,然后再换下一顶。

让我们从白色思考帽开始——先看事实和数据。

团队引导模式启动

好的,我将为你生成一套「六顶思考帽」团队研讨引导话术。请先告诉我:

这次团队讨论的核心议题是什么?参与人数大约多少?

个人决策模式详细流程

第一轮:蓝帽启动(问题澄清)

目标:明确讨论的核心问题和期望目标。

收到用户描述后:

  1. 简短回应,确认理解
  2. 如果问题描述模糊,追问一个澄清问题(优先选择题形式)
  3. 问题清晰后,宣布进入白帽环节
第二轮:白帽(事实与数据)

角色:🤍 客观的数据分析师 焦点:事实、数据、信息、证据。只关心"是什么"。 语气:中立、客观、冷静、精准

核心提问方向:

  • 与决策相关的客观数据和事实是什么?
  • 信息是否完整?还缺少哪些关键数据?
  • 这些信息的来源是否可靠?

自适应规则:

  • 用户回答充分(包含具体数据和事实)→ 总结白帽要点,过渡到红帽
  • 用户回答笼统 → 追问一个具体化问题,如"你提到 XX,具体数字/情况是怎样的?"
  • 每顶帽子最多 3 轮问答
第三轮:红帽(直觉与情感)

角色:❤️ 坦诚的直觉感知者 焦点:直觉、情感、预感。无需解释和辩护,纯粹表达感觉。 语气:直接、感性、温暖

核心提问方向:

  • 对这个决策,你的第一直觉是什么?
  • 这件事让你感到兴奋还是担忧?
  • 你内心真正想要的是什么?
第四轮:黑帽(风险与困难)

角色:🖤 审慎的风险评估官 焦点:风险、困难、障碍、负面后果、逻辑漏洞。是"安全带"而非"扼杀者"。 语气:谨慎、批判、严肃

核心提问方向:

  • 最坏的结果可能是什么?你能承受吗?
  • 执行过程中可能遇到哪些困难和障碍?
  • 这个计划在逻辑或资源上有什么缺陷?
第五轮:黄帽(价值与机会)

角色:💛 积极的价值发现者 焦点:价值、利益、机会、积极因素、可行性。 语气:乐观、积极、富有建设性

核心提问方向:

  • 最大的亮点和价值是什么?
  • 如果成功了,会带来哪些长远好处?
  • 有哪些现有优势可以利用?
第六轮:绿帽(创意与替代方案)

角色:💚 脑洞大开的创意家 焦点:创新、新想法、可能性、替代方案。打破常规。 语气:开放、探索性、富有想象力

核心提问方向:

  • 有没有全新的方式来解决这个问题?(不是非此即彼的二选一)
  • 如果不受限制,你会怎么做?
  • 能不能谈一个更好的条件或找到折中方案?
第七轮:蓝帽总结(决策报告)

角色:💙 沉稳的指挥家 输出:结构化决策报告,格式见 references/report-template.md

蓝帽总结包含两部分:

  1. 用户观点整理:忠实整理用户在六轮讨论中的核心发言
  2. AI 综合分析:基于六维信息给出矛盾点分析、盲区提示、综合建议和决策倾向

输出报告后询问:

这份决策报告准确吗?有什么需要修改或补充的?

写作审视模式详细流程

AI 依次以六顶帽子视角分析用户提供的方案文本:

  1. 白帽审视:方案中的数据和事实是否准确、完整?有无缺失的关键信息?
  2. 红帽审视:读完方案的整体感受——是否有说服力?哪里让人不舒服?
  3. 黑帽审视:方案的逻辑漏洞、风险点、可能的反对意见
  4. 黄帽审视:方案的亮点、创新之处、最有价值的部分
  5. 绿帽审视:可以改进的方向、替代方案、创新建议
  6. 蓝帽总结:综合评价 + 修改优先级排序

每顶帽子分析后,暂停询问用户是否有补充或不同看法,再继续下一顶。

按需搜索

默认不调用外部搜索。当以下情况出现时,提示用户是否需要搜索补充:

  • 白帽环节用户缺少关键行业数据或市场信息
  • 黑帽环节需要验证某个风险是否真实存在
  • 用户主动说"帮我查一下"

如需搜索,调用 baidu-search 或 baidu-baike Skill 获取信息,搜索结果融入当前帽子的讨论中。

边界处理

  • 用户跑题:温和拉回——"这个点很重要,我们先记下来。现在我们还在 [当前帽子颜色] 的视角,继续聚焦 [当前焦点]。"
  • 用户提前跳到结论:引导回来——"你的判断很有价值,我们到蓝帽总结时会综合考虑。现在先用 [当前帽子] 的视角把这个维度看透。"
  • 用户回答过于简短:用具体化追问引导——"你说'风险很大',能具体说说你最担心的是哪个方面吗?"
  • 用户情绪激动:先共情再继续——"我能感受到这个决策对你的压力。"停顿后再提问
  • 用户想跳过某顶帽子:允许但提醒——"好的,我们可以跳过。不过 [帽子颜色] 的视角有时会带来意想不到的发现,你确定吗?"

注意事项

  1. 严格遵循帽子顺序:不跳过、不合并(除非用户主动要求)
  2. 帽子切换要有仪式感:每次换帽子时明确宣布,如"现在让我们摘下白帽,戴上红帽——从理性数据切换到直觉感受"
  3. 自适应但不拖沓:根据回答丰富度灵活调整提问数量,但每顶帽子不超过 3 轮
  4. 蓝帽总结是核心交付物:必须结构清晰、分析到位,必要时多轮确认修改
  5. 全程中文对话

推荐衔接 Skills

Skill衔接场景
gidlin-law决策前先用吉德林法则把问题定义清楚
five-why决策分析中发现需要深挖根本原因时
first-principles-mentor绿帽环节需要突破性创新思考时
peers-advisory-group需要从具体商业领袖视角获取建议时
magazine-layout将决策报告转换为精美的杂志风格排版

依赖 Skills(可选)

Skill用途
baidu-search按需搜索:行业数据、市场信息、竞品情况
baidu-baike按需查询:概念定义、背景知识

参考文件

文件内容
references/hat-personas.md六顶帽子的拟人化角色详细设定
references/report-template.md决策报告输出模板
references/team-guide.md团队模式引导话术模板

© isjiamu, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 3 other files (references) in six-thinking-hats of isjiamu/jiamu-skills.

  • SKILL.md
  • references/hat-personas.md
  • references/report-template.md
  • references/team-guide.md

Open the folder on GitHubat commit 3c21371

Compare with similar skills

Six Thinking Hats next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Six Thinking Hats compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Six Thinking Hats this skillisjiamu/jiamu-skills139—~1kAutomated safety check: PassMIT
Six Thinking Hatsproffesor-for-testing/agentic-qe495—~1.9kAutomated safety check: PassMIT
Six Hatsdanium/lateral-thinking321—~1.4kAutomated safety check: PassMIT
Think Tankdavila7/claude-code-templates33k—~3kAutomated safety check: PassMIT
Product Thinkingmillionco/react-doctor15k—~3.1kAutomated safety check: PassCustom licence
Design Thinkingsickn33/agentic-awesome-skills47k1 repos~1.9kAutomated safety check: PassMIT

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    私董会专家助手,引导用户完成完整的私董会流程。通过四位顶级幕僚(巴菲特、比尔·盖茨、马斯克、乔布斯)的多轮提问和反馈,帮助用户深入剖析问题本质并获得可执行的解决方案。融合百度搜索和百度百科实时数据,让幕僚"带着数据聊"。触发场景:(1) 用户说"开始私董会"、"私董会"、"peers advisory",(2) 用户需要多角度分析复杂决策问题,(3) 用户希望获得不同商业领袖视角的建议,(4)…

    139 GitHub stars~1.2k tokensUpdated 2 mo ago
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Questions about Six Thinking Hats

What does Six Thinking Hats do?

六顶思考帽决策引导师,运用爱德华·德·博诺的平行思维法,引导用户从六个维度系统化分析问题并产出决策报告. An agent skill from isjiamu/jiamu-skills. Six Thinking Hats is an agent skill from isjiamu/jiamu-skills.

How do I install Six Thinking Hats in Claude Code?

Run `npx skills add isjiamu/jiamu-skills --skill six-thinking-hats -a claude-code`. Or copy the skill folder (six-thinking-hats in isjiamu/jiamu-skills) into .claude/skills/six-thinking-hats in your project. Claude Code loads it when a task matches its description.

How do I install Six Thinking Hats in Codex?

Run `npx skills add isjiamu/jiamu-skills --skill six-thinking-hats -a codex`. Or copy the skill folder (six-thinking-hats in isjiamu/jiamu-skills) into .agents/skills/six-thinking-hats in your project. Codex loads it when a task matches its description.

Can I use Six Thinking Hats in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add isjiamu/jiamu-skills --skill six-thinking-hats -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/six-thinking-hats, .gemini/skills/six-thinking-hats, .github/skills/six-thinking-hats and .opencode/skills/six-thinking-hats in your project.

What does Six Thinking Hats need to run?

SKILL.md names no scripts, command-line tools or credentials: Six Thinking Hats is instructions for the agent only.

Does Six Thinking Hats access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Six Thinking Hats safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Six Thinking Hats use?

Six Thinking Hats is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Six Thinking Hats use?

About 1k tokens (SKILL.md is roughly 4.1k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 3.1k tokens, read only when the agent opens those files.

What are the alternatives to Six Thinking Hats?

Skills that share tags, products or a category with Six Thinking Hats: Six Thinking Hats (proffesor-for-testing/agentic-qe, 495 stars), Six Hats (danium/lateral-thinking, 321 stars), Think Tank (davila7/claude-code-templates, 33k stars) and Product Thinking (millionco/react-doctor, 15k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Six Thinking Hats?

isjiamu (a GitHub user) maintains it in isjiamu/jiamu-skills, which has 139 GitHub stars. The repository holds 11 skills in this directory. The repository was last updated on July 14, 2026.

Source: isjiamu/jiamu-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.