学习教育
#ai
scaffold-exercises
Create exercise directory structures with sections, problems, solutions, and explainers that pass linting. Use when user wants to scaffold exercises, create exercise stubs, or set up a new course section.
DeepseekModel
官方收录技能
质量 优秀 · 90
v1.0.0
获取
https://deepseekmodel.com/api/download.php?id=mattpocock-skills-skills-misc-scaffold-exercises-skill-md&format=skill
下载 .skill
标准格式,含 system_prompt 与 model_config,导入任意 Agent 框架即可使用
.skill 文件中 system_prompt 字段的实际内容。
name scaffold-exercises description Create exercise directory structures with sections, problems, solutions, and explainers that pass linting. Use when user wants to scaffold exercises, create exercise stubs, or set up a new course section. Scaffold Exercises Create exercise directory structures that pass pnpm ai-hero-cli internal lint , then commit with git commit . Directory naming Sections : XX-section-name/ inside exercises/ (e.g., 01-retrieval-skill-building ) Exercises : XX.YY-exercise-name/ inside a section (e.g., 01.03-retrieval-with-bm25 ) Section number = XX , exercise number = XX.YY Names are dash-case (lowercase, hyphens) Exercise variants Each exercise needs at least one of these subfolders: problem/ - student workspace with TODOs solution/ - reference implementation explainer/ - conceptual material, no TODOs When stubbing, default to explainer/ unless the plan specifies otherwise. Required files Each subfolder ( problem/ , solution/ , explainer/ ) needs a readme.md that: Is not empty (must have real content, even a single title line works) Has no broken links When stubbing, create a minimal readme with a title and a description: # Exercise Title Description here If the subfolder has code, it also needs a main.ts (>1 line). But for stubs, a readme-only exercise is fine. Workflow Parse the plan - extract section names, exercise names, and variant types Create directories - mkdir -p for each path Create stub readmes - one readme.md per variant folder with a title Run lint - pnpm ai-hero-cli internal lint to validate Fix any errors - iterate until lint passes Lint rules summary The linter ( pnpm ai-hero-cli internal lint ) checks: Each exercise has subfolders ( problem/ , solution/ , explainer/ ) At least one of problem/ , explainer/ , or explainer.1/ exists readme.md exists and is non-empty in the primary subfolder No .gitkeep files No speaker-notes.md files No broken links in readmes No pnpm run exercise commands in readmes main.ts required per subfolder unless it's readme-only Moving/renaming exercises When renumbering or moving exercises: Use git mv (not mv ) to rename directories - preserves git history Update the numeric prefix to maintain order Re-run lint after moves Example: git mv exercises/01-retrieval/01.03-embeddings exercises/01-retrieval/01.04-embeddings Example: stubbing from a plan Given a plan like: Section 05: Memory Skill Building - 05.01 Introduction to Memory - 05.02 Short-term Memory (explainer + problem + solution) - 05.03 Long-term Memory Create: 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 Then create readme stubs: 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"
Agent 识别该技能的关键词,点击任意一个即可复制。
该技能未提供触发词。
下载的 .skill 包内含以下字段。
| 字段 | 说明 |
|---|---|
| format | 格式标识(skill/v1) |
| skill_id | 技能唯一 ID |
| name | 技能名称 |
| version | 版本号 |
| description | 技能描述 |
| category | 所属分类(数组) |
| trigger_words | 触发词列表 |
| tags | 标签列表 |
| source | 来源标识 |
| source_url | 来源链接(本页地址) |
| exported_at | 导出时间(每次下载生成) |
| system_prompt | 系统提示词正文 |
| model_config | 模型参数:provider / model / temperature / max_tokens / top_p |
| examples | 示例 |
| install_guide | 各平台导入说明(Coze / Dify / Claude / 自定义框架) |