agent-skills
CLAUDE.md8 starsChanged 8 days agoMITView on GitHub
Reusable Claude Code skills for software engineering agents. Each skill lives in its own directory with a SKILL.md (practice guide) and supporting tools. ~/.claude/skills/lazy/ and ~/.codex/skills/lazy/ are symlinks into .claude/skills/lazy/, so this repo is the only copy. Edit it here, open a PR, and after merge publish it so teammates get the same version: Editing ~/.claude/skills/lazy/ directly writes through the symlink into an unreviewed working copy of this repo. Commit it. Three kinds: 1. Unit tests (tests/test_event_model.py) — the Python…
- Installs packages
In this repository2 other files it gives its agents.
- lazySkill
- event-modelingSkill
The file
We split this CLAUDE.md into the rules it gives an agent
1 rule. About 0 are common, 1 is distinctive, and 0 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈1
Distinctive · estimate
This author's own choices. Worth a look.
0
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 66
No coauthor signatures in commits
≈ “Common” is an estimate: at least 1 in 5 of the 26,980 CLAUDE.md files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Agent Skills
Reusable Claude Code skills for software engineering agents.
Structure
Each skill lives in its own directory with a SKILL.md (practice guide) and supporting tools.
event-modeling/— event modeling skill with Pydantic schema, validation, and SVG renderingevent-modeling/ts/— the model as typed TypeScript; assembles to the JSON, generates the protobuf,emCLIevent-modeling/ts/viewer/— the live diagramem viewserves; Vue over the assembled JSON, built by Vite intoviewer/dist.claude/skills/lazy/— response contract skill plus itsStophook, installed active for this repo
The lazy skill is edited here, nowhere else
~/.claude/skills/lazy/ and ~/.codex/skills/lazy/ are symlinks into
.claude/skills/lazy/, so this repo is the only copy. Edit it here, open a PR,
and after merge publish it so teammates get the same version:
gns skills publish .claude/skills/lazy -m "<what changed>" --team architecture --public --force
gns skills repair --key user.noah.skills.lazyEditing ~/.claude/skills/lazy/ directly writes through the symlink into an
unreviewed working copy of this repo. Commit it.
Dependencies
pip install pydantic pytestRunning Tests
pytest event-modeling/tests/ -v
pytest tests/ -v # lazy-check.py
cd event-modeling/ts && npm test # tsc, biome, vite build, node --test, buf lintTest Harness
Three kinds:
- Unit tests (
tests/test_event_model.py) — the Python tool's parsing, validation and rendering - TypeScript tests (
ts/test/) —typecheck.tsholds one@ts-expect-errorper compiler check, sotscfails if a check stops firing; the rest cover assembly, the proto generator, the viewer's layout (pure, no browser) and the CLI, including theviewserver. Biome does not formattypecheck.ts: the directive binds to the next line, so reformatting a chain moves the error off it and silently disarms the check - Brief coverage (
ts/test/brief-coverage.test.ts) — whether the model answers the product brief, which is the only thing left that no type system can decide
Test Fixtures
- Product brief (
tests/fixtures/todo_app_brief.md) — a plain-text product description, the real input an agent works from - The model (
ts/examples/todo-app/) — the model built from that brief.ts/test/todo-app.jsonis what it assembles to, andevent_model.py validatereports zero warnings on it - Golden JSON (
tests/fixtures/todo_app_model.json) — a hand-written model of the same brief, for the Python tests
Conventions
- Skills use
SKILL.mdfrontmatter withnameanddescription - Tool scripts are self-contained Python with minimal dependencies
- No coauthor signatures in commits
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

