ii23-skills
CLAUDE.md11 starsChanged 49 days agoMITView on GitHub
Each skill lives at skills/<name>/ with a SKILL.md and, where it needs them, a scripts/ folder. Scripts are stdlib-only Python so a skill installs by copying a folder. Adding, renaming, or removing a skill means updating three places, or the repo starts lying about itself: 1. README.md — a problem-and-fix section under "Why these exist", plus a row in the Skills table. Every mention links to the skill's SKILL.md. 2. skills.sh.json — the skill's name in a grouping's skills array.…
In this repository2 other files it gives its agents.
- image-gen-routerSkill
- video-understandSkill
The file
Files
Each skill lives at skills/<name>/ with a SKILL.md and, where it needs them,
a scripts/ folder. Scripts are stdlib-only Python so a skill installs by
copying a folder.
Adding, renaming, or removing a skill means updating three places, or the repo starts lying about itself:
README.md— a problem-and-fix section under "Why these exist", plus a row in the Skills table. Every mention links to the skill'sSKILL.md.skills.sh.json— the skill's name in a grouping'sskillsarray.docs/<name>.md— the human-facing page. Follow .agents/writing-docs.md; a rename moves the file.
SKILL.md is the agent contract: what to run, in what order, and the traps to
avoid while doing it. It is not the place for the reasoning behind a decision.
That goes in .agents/adr/, and a rejected approach goes in .out-of-scope/
with the measurement that killed it — so nobody re-proposes it and no agent
burns a session rediscovering it.
Numbers in any document are measured, never estimated. Every performance claim in this repo came from a real run on a real file; if you change a claim, re-run the measurement first and say what you ran it on.
Validate a skill after editing it:
python3 ~/.agents/skills/skill-creator/scripts/quick_validate.py skills/<name>Frontmatter limits it enforces: name <= 64 chars, description <= 1024. The
description is what makes a skill trigger, so it carries the trigger phrases
(including Thai ones) and an explicit "do NOT use for ..." boundary.
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.

