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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 キュレーション済みスキル 品質 優秀 · 90 v1.0.0

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ダウンロード .skill 標準形式。system_prompt と model_config を収録し、任意の Agent で利用可能
.skill ファイルの system_prompt フィールドの実際の内容。
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"
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ダウンロードした .skill に含まれるフィールド。
フィールド 説明
formatフォーマット識別子(skill/v1)
skill_idスキル固有 ID
nameスキル名
versionバージョン
description説明
categoryカテゴリ(配列)
trigger_wordsトリガーワード
tagsタグ
sourceソース
source_urlソース URL(本ページ)
exported_atエクスポート日時(ダウンロード毎)
system_promptシステムプロンプト本文
model_configモデル設定:provider / model / temperature / max_tokens / top_p
examplesサンプル
install_guide各プラットフォームの導入説明(Coze / Dify / Claude / カスタム)
同じスキルを各プラットフォーム形式で出力できます。
.skill 標準形式。system_prompt と model_config を収録し、任意の Agent で利用可能 ダウンロード
.skillpro 拡張形式。scripts / tools / dependencies / hooks を含む ダウンロード
.json 純粋な JSON 出力。system_prompt とモデル設定のみ ダウンロード
Coze frontmatter 付き Markdown。Coze へのインポート用 ダウンロード
Dify Dify DSL。アプリ作成後にそのままインポート ダウンロード

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