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scaffold-exercises

Create exercise directory structures with sections, problems, solutions, and explainers that pass linting

Install / Use

npx skills add mattpocock/skills --skill scaffold-exercises

Installs into whichever agent you are using.

About this skill
📄

SKILL.md

Installable skill definition

Quality Score

87/100

Supported Platforms

Universal

Our assessment of scaffold-exercises

scaffold-exercises scores 87/100 on our quality scale, 368th of 1,751 Development & Engineering skills we index (top 22%).

Its SKILL.md is 3.5 KB long, well organised into 9 sections with 5 code examples: a solid amount of guidance for an agent.

With 268,790 GitHub stars, it is one of the more widely adopted skills in the catalogue.

Substance
26/30
Structure
20/20
Description
12/15
Adoption
20/20
Freshness
15/15

Maintenance, license and trust

  • The repository was last updated yesterday, so scaffold-exercises is actively maintained.
  • It is released under the MIT license, a permissive license that allows use, modification and commercial use with attribution.
  • Its trust signals score 100/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.

scaffold-exercises compared with similar skills

All 4 of these similar skills score higher than scaffold-exercises; compare them before choosing.

SkillScoreStarsUpdatedFormat
scaffold-exercises (this skill)by mattpocock87268.8k1d agoSKILL.md
Agent-Reachby Panniantong10085.4k9d agoCLAUDE.md
ai-job-searchby MadsLorentzen10043.9k4d agoCLAUDE.md
claude-howtoby luongnv8910041.7k5d agoCLAUDE.md
algorithmic-artby anthropics100177.9k2d agoSKILL.md

Frequently asked questions

How do I install scaffold-exercises?
Run npx skills add mattpocock/skills --skill scaffold-exercises. The install tabs above show the steps for each supported agent.
Which AI agents does scaffold-exercises work with?
It is written for Universal, as a SKILL.md file. Other agents that read the same format can often use it too.
Is scaffold-exercises safe to use?
It is MIT-licensed and scores 100/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
Is scaffold-exercises still maintained?
The repository was last updated yesterday, so scaffold-exercises is actively maintained.

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

  1. Parse the plan - extract section names, exercise names, and variant types
  2. Create directories - mkdir -p for each path
  3. Create stub readmes - one readme.md per variant folder with a title
  4. Run lint - pnpm ai-hero-cli internal lint to validate
  5. 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:

  1. Use git mv (not mv) to rename directories - preserves git history
  2. Update the numeric prefix to maintain order
  3. 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"

Related Skills

View on GitHub
GitHub Stars268.8k
CategoryDevelopment
Updated1d ago
Forks22.7k

Languages

Shell

Trust signals

100/100

From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.

No cautions