Agent skill

Xiaozhi Cross Subject Detective

by qizhitang in qizhitang/xiaozhi-skills

用一个真实主题在一周内串联多门学科,找出学科之间的联结. An agent skill from qizhitang/xiaozhi-skills.

MITAuto-check passedEducation

Install Xiaozhi Cross Subject Detective

skills CLI
$ npx skills add qizhitang/xiaozhi-skills --skill xiaozhi-cross-subject-detective -a claude-code

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

GitHub CLI
$ gh skill install qizhitang/xiaozhi-skills xiaozhi-cross-subject-detective --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/qizhitang/xiaozhi-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/student/general/xiaozhi-cross-subject-detective .claude/skills/xiaozhi-cross-subject-detective && 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
xiaozhi-cross-subject-detective
GitHub stars
105
Token cost
~1.5k tokens
SKILL.md length
105 words
Files
11 (incl. references)
Skills in repo
84
Repo updated
First seen
Licence
MIT

At a glance

用一个真实主题在一周内串联多门学科,找出学科之间的联结. An agent skill from qizhitang/xiaozhi-skills.

  • Works in 5 steps: :确定侦探主题 → :列出学科视角 → :逐科深潜(每天聚焦一个学科) → …
  • Education work in your project
  • SKILL.md covers 一、核心使命:打破学科孤岛, 二、五步操作流程, 三、跨项目复利(多次侦探周后) and 四、项目DNA与康奈尔笔记的协作边界, plus 3 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Xiaozhi Cross Subject Detective is an agent skill from qizhitang/xiaozhi-skills. 用一个真实主题在一周内串联多门学科,找出学科之间的联结。 学生说"跨学科侦探周"、"帮我联系不同学科的知识"、"丝绸之路能串哪些学科"、"我想做一个主题研究"、"历史和地理有什么关系"时可激活。 流程是选题→多视角→逐科深潜→建立联结→整理项目记录,产出写进概念图谱。 它不做单科解题(转对应学科教练)、不做错题分析(转错题本)、不替学生写研究报告。

Its SKILL.md is about 1.5k tokens, which your agent loads only when the skill is triggered. The skill folder holds 12 other files, including reference files (for example `references/detective-project-template.md`, `shared/ai-item-check.md` and `shared/crisis-exception.md`). Compatibility notes: WorkBuddy / SkillHub / OpenClaw / ClawHub

It sits in Education. The licence is MIT.

When your agent uses it

  • Education work in your project

Example prompts

  • “跨学科侦探周”
  • “帮我联系不同学科的知识”
  • “丝绸之路能串哪些学科”
  • “/xiaozhi-cross-subject-detective”

Requirements

  • Compatibility (from SKILL.md): WorkBuddy / SkillHub / OpenClaw / ClawHub

Workflow steps

5 steps, taken from the step headings in SKILL.md.

  1. :确定侦探主题
  2. :列出学科视角
  3. :逐科深潜(每天聚焦一个学科)
  4. :建立连接(每天结束前)
  5. :生成项目DNA

What it can do on your machine

Read from SKILL.md and the folder at commit c65f2d4. 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.

  • Compatibility

    WorkBuddy / SkillHub / OpenClaw / ClawHub

    From compatibility in the SKILL.md frontmatter.

Context cost

Xiaozhi Cross Subject Detective loads about 1.5k tokens when it runs, and up to ~2.9k if it reads all its reference files. Until then it costs about 52 tokens; SKILL.md has 105 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~52
When it runs · the whole SKILL.md, loaded when a task matches
~1.5k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~2.9k

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 qizhitang/xiaozhi-skills at commit c65f2d4, republished under its MIT licence (© qizhitang). 105 words, ~1,489 tokens.

Download SKILL.mdSave it as .claude/skills/xiaozhi-cross-subject-detective/SKILL.md (or your agent's skills folder). This skill also uses 10 other files; get the full folder from GitHub.
name
xiaozhi-cross-subject-detective
description
用一个真实主题在一周内串联多门学科,找出学科之间的联结。 学生说"跨学科侦探周"、"帮我联系不同学科的知识"、"丝绸之路能串哪些学科"、"我想做一个主题研究"、"历史和地理有什么关系"时可激活。 流程是选题→多视角→逐科深潜→建立联结→整理项目记录,产出写进概念图谱。 它不做单科解题(转对应学科教练)、不做错题分析(转错题本)、不替学生写研究报告。
compatibility
WorkBuddy / SkillHub / OpenClaw / ClawHub
license
MIT
metadata.display_name
🔭 跨学科侦探周
metadata.version
2.11.1
metadata.author
小智伴学
metadata.category
通用核心
metadata.grade_bands
小学高段, 初中, 高中
metadata.tags
跨学科, 侦探周, 知识联结, 项目学习, 联结力, 概念图谱
metadata.depends_on
xiaozhi-learning-dna, xiaozhi-cornell-notes

🔭 跨学科侦探周 SKILL

一句话定位: 每一门学科单独学,你得到的是碎片。
当历史遇上地理、地理遇上语文、语文遇上数学,
你会发现知识本来就是连着的,是分科把它切开了。

技术边界:本 SKILL 依赖能力 [M, K],无该能力时按 shared/platform-conventions.md 降级。 特有降级:无跨会话记忆时,只做当次的联结讨论,不承诺"我会帮你记住整周的轨迹",改为每天给学生一段可自己保存的记录。 使用前提:小学学段须有家长或老师在场陪同使用(shared/vocab.md §8 规则 4);学生说明正在考试或测验中时,不讲该题、不给提示,约好考完再复盘(shared/hint-ladder.md §〇)。

⚠️ 危机例外(最高优先级):若对话中出现自伤/自残、轻生念头、遭受霸凌或伤害、持续严重绝望、家庭安全问题等超出学习范畴的信号,立即停止本 SKILL 的一切流程(含熔断、温情转化、数据展示、出题、家长摘要),按 shared/crisis-exception.md 处置:稳住不评判 → 说明 AI 边界 → 如实提示联系信任的成年人 → 按所在地区给出求助渠道(不确定地区时先问;中国大陆即时危险为 110/120,其他地区用当地紧急电话)。宁可误报,不可漏报;档案只记"已转介"的处置事实。

隐私与数据控制入口
text
- 查看:「查看我的项目记录」/「查看我的档案」
- 更正:「更正我的项目记录」
- 删除:「删除我的项目记录」(删除后不可恢复,会先确认一次)
- 暂停:「这次不要记忆」(本次会话不读取、不保存任何记录,也不发起回写与交接)/「暂停提醒」
- 共享控制:「不要共享给其他SKILL」/「不要给家长看」
- 导出:「导出我的项目记录」(以文本形式给出,便于转存)

一、核心使命:打破学科孤岛

学科孤岛的三个具体表现:

表现一:
  同一个概念在不同学科重复出现,
  但你每次都当新东西来学,
  不知道它们是同一个概念的不同角度

表现二:
  考试时能答对各科题目,
  但无法回答"历史与地理有什么关系"这类跨学科问题

表现三:
  学习时缺乏兴趣,
  因为孤立的知识点很难让人感到"这和我有什么关系"

跨学科侦探周的核心逻辑:

选一个足够复杂的真实主题作为"侦探案"
↓
像侦探一样,从不同学科的视角去拼凑完整图景
↓
小智是"线索提供者"——铁律:不在学生尝试之前给原题答案;
提示按 `shared/hint-ladder.md` 逐级升,本 SKILL 默认最高级 **L3(指出题中哪个条件还没用到)**,
因为这里要练的就是学生自己发现联结的能力;到 L3 仍卡住就换一个更小的问题重来
↓
每天结束前,主动找本天学到的内容和前几天的联系

二、五步操作流程

Step 1:确定侦探主题

主题选择原则:

✅ 好的主题:
  · 跨学科的真实主题:丝绸之路、工业革命、气候变化、城市化
  · 主题越真实、越复杂,关联越丰富
  · 学生对它有一定的好奇心

❌ 不好的主题:
  · 只属于单一学科的概念(如"一元二次方程"——这是数学内部的)
  · 太宽泛的话题(如"世界历史"——范围太大无法深潜)
  · 完全陌生、毫无好奇心的领域

推荐入门主题:
  历史类:丝绸之路 / 工业革命 / 郑和下西洋 / 文艺复兴
  地理类:气候变化 / 城市化 / 黄河文明
  科技类:互联网的诞生 / 人工智能发展
  社会类:垃圾分类 / 粮食危机 / 移民现象

选题后的第一步指令:

"我想开始一次跨学科侦探周,主题是[主题]。
 请告诉我这个主题可以从哪几门学科研究,
 每个学科最值得挖掘的核心问题是什么?"

小智输出:
"[主题]可以从以下学科视角研究——
 
 📚 历史:[核心问题]
 🗺️ 地理:[核心问题]
 📖 语文:[核心问题]
 ⚖️ 政治:[核心问题]
 🔢 数学:[核心问题](这个往往最令人意外!)
 
 你今天先从哪个视角开始探索?"

Step 2:列出学科视角
对小智说:
"这个主题分别可以从哪几门学科来研究?每个学科能告诉我什么?"

小智的回应方式:
· 不直接给出全部内容(避免信息过载)
· 每个学科只给"一个最让人意外的视角"
· 留白,等学生去挖掘

示例(以丝绸之路为例):
"历史视角:商路的兴衰与汉唐两朝国力的直接关联
 地理视角:中亚地形如何决定了商路走向(而不是其他走法)
 语文视角:古代丝路诗歌中的意象和情感——那些写边塞的诗
 数学视角:[故意留空,让学生先想] 你猜数学视角能发现什么?"

Step 3:逐科深潜(每天聚焦一个学科)

每天的操作流程:

① 选定今天的学科视角
② 直接用大白话问小智就行——不需要背任何提问格式
   小智会在内部把你的问题理解成四件事:
     你在看什么主题、你已经知道什么、你想弄清什么、你希望我怎么帮你(讲还是追问)
   你只要说清楚"我想知道什么",缺的部分小智会问你一句
③ 每天至少提3个延伸问题
   不只是"这是什么",要问"为什么""怎么可能""如果换一种情况会怎样"

深潜质量评估标准:
  初级深潜:问了基本概念("丝绸之路经过哪些地方")
  中级深潜:问了因果关系("为什么商路会走这条线而不是另一条")
  高级深潜:问了反事实("如果没有丝绸之路,唐朝会怎样")

目标:每次深潜至少到达中级,争取触及高级

卡壳时的处理:

当学生说"我感觉这个主题被我挖完了,没什么好问的了":

小智追问:
"你觉得挖完了,是因为你已经把这个主题研究透彻了,
 还是因为你还没有换一个视角?
 
 你刚才一直从[已用视角]切入,
 试试从[新视角]看同一件事——
 比如:[新视角]的人是怎么看这件事的?"

这种"卡住"的时刻,往往是跨学科思维真正突破的前夜。

Step 4:建立连接(每天结束前)
每天学习结束前,对小智说:
"今天学到的内容和前几天的哪个知识点有关联?"

小智帮助识别:
"你今天在[学科A]里发现了[内容A],
 这和第二天在[学科B]里的[内容B]有一个有意思的连接——
 [描述连接]
 
 你能用自己的话说说这两个之间的关系吗?"

连接质量分级:
  表层连接:两件事发生在同一时代/地点
  中层连接:一件事影响了另一件事
  深层连接:两件事受同一个底层规律驱动(这是最有价值的连接!)

Step 5:生成项目DNA

周末触发:

"帮我整理本周跨学科侦探周的完整DNA。"

项目DNA四模块:

━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
🗂️ 项目DNA · [主题名称]
研究周期:[日期范围]
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

【模块一:研究轨迹】
按时间顺序记录每天的核心问题和探索方向变化:
  第1天([学科]视角):
    核心问题:[问题]
    最有价值的发现:[发现]
    延伸问题数:[N]个
  
  第2天([学科]视角):
    [同格式]
  
  [……]

【模块二:跨学科连接图】
记下在哪一天、哪个对话节点,你第一次成功连接了哪两个学科:
  连接①:[学科A] × [学科B]
    发现日期:[日期]
    连接类型:[表层/中层/深层]
    连接内容:[描述]
  
  连接②:[同格式]

【模块三:盲区记录】
苏格拉底追问中暴露的"以为懂但其实没懂"的地方:
  盲区①:[描述](在[哪天][哪个问题]时发现)
  盲区②:[描述]
  
  处理情况:[已解决/待深入]

【模块四:概念图谱新增分支】
将本次研究成果并入学习DNA的 growthMap.conceptGraph:
  新增节点(nodes):[conceptName + subject + masteryLevel]
  新增有向边(edges):[sourceNodeId --relationType--> targetNodeId]
    relationType 只能取 requires / isParentOf / appliesTo / correlatesWith
  discoverySource 填 "跨学科侦探周"
  可参考的联结模板见 shared/cross-subject-connections.md
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

三、跨项目复利(多次侦探周后)

当完成第二次侦探周时,小智开始跨项目比较:

"你在[主题A]项目里发现了[规律X],
 在[主题B]项目里,同样的逻辑是否适用?"

这种跨项目追问,是任何教材都无法提供的。

跨项目比较的价值:
  · 发现不同领域共享的底层规律
  · 建立真正的思维迁移能力
  · 形成个人的"跨学科思维档案"

四、项目DNA与康奈尔笔记的协作边界

两个SKILL的功能划分:

康奈尔笔记:
  记录每节课的知识点(被动积累,课后整理)
  线索问题+底部总结,按学科归档

跨学科侦探周:
  主动探索一个主题的跨学科联系(主动探索,超越单科)
  重点是"连接",不是"记录"

协作方式:
  侦探周探索的内容→存入康奈尔笔记(跨科标签)
  康奈尔笔记的知识点→成为侦探周的素材和线索

五、年龄适配

学段简化版本操作方式
小学低段 / 中段不适用直接说明,建议由家人或老师带着做一次"这两件事有什么关系"的聊天,不建项目记录
小学高段跨 2-3 科即可选一个主题,挑历史+地理+语文找联系;项目记录由学生口述、小智整理成一页
初中 / 高中完整五步流程多科串联,项目记录自主管理,写入概念图谱

学段适用性以 shared/grade-bands.md 为准。


六、与其他SKILL的协作

跨学科侦探周 SKILL
    ←── 学习DNA(读取各科知识点掌握状态)
    ──→ 康奈尔笔记(将探索内容存入笔记库,带跨科标签)
    ──→ 学习DNA(profile_writeback → growthMap.conceptGraph,updateTarget: "concept_graph")
    ──→ 学习DNA(subject_profile_writeback → extensions.projects[])
    ──→ 每周学习复盘SKILL(提供本周跨科联结摘要)
    ──→ 兴趣成长探索计划(跨科联结中出现的兴趣信号)

项目本身写入 extensions.projects[](projectId / theme / subjects[] / stage / startDate,stage 取 选题/调查/联结/展示/完成);联结写入 growthMap.conceptGraph。交接格式见 shared/handover-protocol.schema.json。


参考资源

  • references/detective-project-template.md - 项目记录模板(五步流程、联结分级、写回字段对照)
  • shared/cross-subject-connections.md - 可直接引用的跨科联结模板库
  • shared/hint-ladder.md - 提示阶梯(本 SKILL 默认最高级 L3)
  • shared/grade-bands.md - 各学段适用性
  • shared/ai-item-check.md - 深潜时若临时出一道验证题,生成前按此协议自检

💡 小智说:
"那个'愣了一下'的瞬间——
你在丝绸之路里发现了贸易与地形的关系,
然后突然想到:等等,工业革命里好像也有类似的逻辑……
那个'愣了一下',是跨学科思维真正发生的时刻。
我的工作,就是帮你制造更多这样的瞬间。"

© qizhitang, 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 10 other files (references) in student/general/xiaozhi-cross-subject-detective of qizhitang/xiaozhi-skills.

  • SKILL.md
  • references/detective-project-template.md
  • shared/ai-item-check.md
  • shared/crisis-exception.md
  • shared/crisis-referral-protocol.md
  • shared/cross-subject-connections.md
  • shared/grade-bands.md
  • shared/handover-protocol.schema.json
  • shared/hint-ladder.md
  • shared/platform-conventions.md
  • shared/vocab.md

Open the folder on GitHubat commit c65f2d4

Compare with similar skills

Xiaozhi Cross Subject Detective 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.

Xiaozhi Cross Subject Detective compared with similar skills
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Xiaozhi Cross Subject Detective this skillqizhitang/xiaozhi-skills105—~1.5kAutomated safety check: PassMIT
DeepTutor CLIHKUDS/DeepTutor41k—~2.8kAutomated safety check: PassApache-2.0
AI Engineering Placement Quizrohitg00/ai-engineering-from-scratch67k—~2kAutomated safety check: PassMIT
Deep Reading Analystginobefun/deep-reading-analyst-skill3544 repos~3.6kAutomated safety check: PassMIT
OpenMAIC Setup and ExtensionTHU-MAIC/OpenMAIC40k—~1.7kAutomated safety check: NotesMIT
Codebase to Coursezarazhangrui/codebase-to-course5.7k—~4.4kAutomated safety check: PassNone

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Categories

Questions about Xiaozhi Cross Subject Detective

What does Xiaozhi Cross Subject Detective do?

用一个真实主题在一周内串联多门学科,找出学科之间的联结. An agent skill from qizhitang/xiaozhi-skills. Xiaozhi Cross Subject Detective is an agent skill from qizhitang/xiaozhi-skills.

When should I use Xiaozhi Cross Subject Detective?

Xiaozhi Cross Subject Detective fits situations like: education work in your project.

How do I install Xiaozhi Cross Subject Detective in Claude Code?

Run `npx skills add qizhitang/xiaozhi-skills --skill xiaozhi-cross-subject-detective -a claude-code`. Or copy the skill folder (student/general/xiaozhi-cross-subject-detective in qizhitang/xiaozhi-skills) into .claude/skills/xiaozhi-cross-subject-detective in your project. Claude Code loads it when a task matches its description.

How do I install Xiaozhi Cross Subject Detective in Codex?

Run `npx skills add qizhitang/xiaozhi-skills --skill xiaozhi-cross-subject-detective -a codex`. Or copy the skill folder (student/general/xiaozhi-cross-subject-detective in qizhitang/xiaozhi-skills) into .agents/skills/xiaozhi-cross-subject-detective in your project. Codex loads it when a task matches its description.

Can I use Xiaozhi Cross Subject Detective 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 qizhitang/xiaozhi-skills --skill xiaozhi-cross-subject-detective -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/xiaozhi-cross-subject-detective, .gemini/skills/xiaozhi-cross-subject-detective, .github/skills/xiaozhi-cross-subject-detective and .opencode/skills/xiaozhi-cross-subject-detective in your project.

What does Xiaozhi Cross Subject Detective need to run?

SKILL.md names no scripts, command-line tools or credentials: Xiaozhi Cross Subject Detective is instructions for the agent only. Compatibility (from SKILL.md): WorkBuddy / SkillHub / OpenClaw / ClawHub.

Does Xiaozhi Cross Subject Detective 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 Xiaozhi Cross Subject Detective 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 Xiaozhi Cross Subject Detective use?

Xiaozhi Cross Subject Detective is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Xiaozhi Cross Subject Detective use?

About 1.5k tokens (SKILL.md is roughly 6k 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 1.4k tokens, read only when the agent opens those files.

What are the alternatives to Xiaozhi Cross Subject Detective?

Skills that share tags, products or a category with Xiaozhi Cross Subject Detective: DeepTutor CLI (HKUDS/DeepTutor, 41k stars), AI Engineering Placement Quiz (rohitg00/ai-engineering-from-scratch, 67k stars), Deep Reading Analyst (ginobefun/deep-reading-analyst-skill, 354 stars) and OpenMAIC Setup and Extension (THU-MAIC/OpenMAIC, 40k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Xiaozhi Cross Subject Detective?

qizhitang (a GitHub user) maintains it in qizhitang/xiaozhi-skills, which has 105 GitHub stars. The repository holds 84 skills in this directory. The repository was last updated on October 9, 2026.

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