Skip to content
Agentmart
Submit a tool

scaffold-exercises

创建包含章节、习题、解答和讲解的练习目录结构,并能通过 lint 检查。当用户想搭建练习脚手架、创建练习存根,或新建一个课程章节时使用。

Skill by WenWuZhiDao

IndexedMIT★ 29
Write a review

Chalk Labs

Need help deploying scaffold-exercises?

Chalk Labs sets up agents like this inside real teams: connected to your tools, tested on your data, with a human in the loop where it matters.

Book a call

Install

Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.

npx agentmarket install skill/wenwuzhidao-scaffold-exercises

Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.

Get the weekly diff

The weekly diff: one email a week with new agent tools, notable updates and grade changes, plus security alerts for tools you follow. Double opt-in, one-click unsubscribe.

We use your email only for this newsletter. Privacy

About

创建包含章节、习题、解答和讲解的练习目录结构,并能通过 lint 检查。当用户想搭建练习脚手架、创建练习存根,或新建一个课程章节时使用。

No reviews yet. Installed it? Reviews come from verified installers only. How reviews work

Permissions

What this skill can do and what it asks for, from its SKILL.md and code. Checked Oct 26, 2026.

Tools
No tools found
Secrets
None asked for
Install scripts
None found

Network hosts it talks to 1

  • codeload.github.com · found in install command

Files it touches

  • ~/.claude/skills/scaffold-exercises

What's inside

Skill name
scaffold-exercises
Description
创建包含章节、习题、解答和讲解的练习目录结构,并能通过 lint 检查。当用户想搭建练习脚手架、创建练习存根,或新建一个课程章节时使用。
License
MIT
Instructions
103 lines in SKILL.md · view on GitHub

Files (2)

  • SKILL.md
  • openai.yaml · agents/

SKILL.md (first lines)

# 脚手架生成练习

创建能通过 `pnpm ai-hero-cli internal lint` 的练习目录结构,然后用 `git commit` 提交。

## 目录命名

- **章节(Sections)**:`exercises/` 内的 `XX-section-name/`(例如 `01-retrieval-skill-building`)
- **练习(Exercises)**:某章节内的 `XX.YY-exercise-name/`(例如 `01.03-retrieval-with-bm25`)
- 章节编号 = `XX`,练习编号 = `XX.YY`
- 名称采用 dash-case(小写,连字符)

## 练习变体

每个练习需要以下子文件夹中的至少一个:

- `problem/` —— 带 TODO 的学员工作区
- `solution/` —— 参考实现
- `explainer/` —— 概念性材料,无 TODO

生成桩代码时,除非计划另有规定,否则默认使用 `explainer/`。

## 必需文件

每个子文件夹(`problem/`、`solution/`、`explainer/`)都需要一个 `readme.md`,要求:

- **非空**(必须有真实内容,哪怕只有一行标题也行)
- 没有失效链接

生成桩代码时,创建一个带标题和描述的最小 readme:

```md
# Exercise Title

Description here
```

如果子文件夹有代码,还需要一个 `main.ts`(多于 1 行)。但对于桩代码而言,只有 readme 的练习也可以。

## 工作流程

1. **解析计划** —— 提取章节名称、练习名称和变体类型
2. **创建目录** —— 为每个路径执行 `mkdir -p`
3. **创建桩 readme** —— 每个变体文件夹一个带标题的 `readme.md`
4. **运行 lint** —— 用 `pnpm ai-hero-cli internal lint` 验证
5. **修复所有错误** —— 反复迭代直到 lint 通过

## Lint 规则摘要

linter(`pnpm ai-hero-cli internal lint`)会检查:

- 每个练习都有子文件夹(`problem/`、`solution/`、`explainer/`)
- 至少存在 `problem/`、`explainer/` 或 `explainer.1/` 中的一个
- 主子文件夹中存在非空的 `readme.md`
- 没有 `.gitkeep` 文件
- 没有 `speaker-notes.md` 文件
- readme 中没有失效链接
- readme 中没有 `pnpm run exercise` 命令
- 除非只有 readme,否则每个子文件夹都需要 `main.ts`

## 移动/重命名练习

重新编号或移动练习时:

1. 使用 `git mv`(而非 `mv`)重命名目录 —— 保留 git 历史
2. 更新数字前缀以维持顺序
3. 移动后重新运行 lint

示例:

```bash
git mv exercises/01-retrieval/01.03-embeddings exercises/01-retrieval/01.04-embeddings
```

## 示例:从计划生成桩代码

给定这样一个计划:

```
Section 05: Memory Skill Building
- 05.01 Introduction to Memory
- 05.02 Short-term Memory (explainer + problem + solution)
- 05.03 Long-term Memory
```

创建:

```bash
mkdir -p exercises/05-memory-skill-building/05.01-introduction-to-memory/explainer
mkdir -p exercises/05-memory-skill-building/05.02-short-term-memory/{explainer,problem,solution}
mkdir -p exercises/05-memory-skill-building/05.03-long-term-memory/explainer
```

然后创建 readme 桩:

```
exercises/05-memory-skill-building/05.01-introduction-to-memory/explainer/readme.md -> "# Introduction to Memory"
exercises/05-memory-skill-building/05.02-short-term-memory/explainer/readme.md -> "# Short-term Memory"
exercises/05-memory-skill-building/05.02-short-term-memory/problem/readme.md -> "# Short-term Memory"
exercises/05-memory-skill-building/05.02-short-term-memory/solution/readme.md -> "# Short-term Memory"
exercises/05-memory-skill-building/05.03-long-term-memory/explainer/readme.md -> "# Long-term Memory"
```

From WenWuZhiDao/mattpocock-skills-zh, MIT.

More from WenWuZhiDao/mattpocock-skills-zh

Signals

Stars
29
Forks
5
Open issues
0
Last commit (this folder)
Jul 24, 2026 (3 months ago)
Last release
Aug 13, 2026 (2 months ago)

From GitHub (fetched Oct 24, 2026).

Details

License
MIT
First seen
Oct 24, 2026
Last checked
Oct 24, 2026

More from WenWuZhiDao

Done for you

Rather not set it up yourself?

Chalk Labs scopes, builds and runs agents for your team: the task audit, the eval harness, the integrations and the weekly ops report. Fixed scope, priced before we start.

See how we build AI agents →Read the case studies

Chalk Labs is a two-founder AI and growth studio. We build AI agents, CRMs and MVPs for Web3 and AI companies, and have shipped 50+ product and token launches.

launches shipped
50+
launches shipped
media placements
500+
media placements
founders on every account
2
founders on every account

Press we've placed: Forbes · CoinDesk · Decrypt · Cointelegraph · The Block

Rahil Jain, Co-founder, Chalk Labs. Ex-Goldman Sachs engineer. You talk to the person who builds it.

Get scaffold-exercises running in your business

Tell us what you want to automate. A founder replies within one working day with a plan, not a pitch deck.

Goes to the Chalk Labs founders, not the newsletter. Privacy

Need help deploying scaffold-exercises?

CallGet help
Cite this page

scaffold-exercises skill. Agent Mart. https://agentmart.dev/skills/wenwuzhidao-scaffold-exercises (last updated 2026-10-24)