This is a cross-post — the original (and any updates) live at is a prompt you trigger by typing
/name; a skill is a procedure Claude triggers when the context matches. Same reusable-instructions idea, opposite trigger.
Where the file goes
Two locations register, exactly like commands and : be explicit about when, not just what.
Bundling scripts, references, and templates
The reason a skill beats a slash command for real workflows is that the folder can hold more than instructions. Anything you drop in the skill directory is available to Claude when the skill runs:
CODE.claude/skills/release-notes/
├── SKILL.md
├── template.md # the format to fill in
└── changelog-parse.py # a helper the skill runs
Reference them from
SKILL.mdby relative path — "fill intemplate.md", "runchangelog-parse.pyon the git log" — and Claude reads or executes them as part of following the skill. That's how a skill packages an entire procedure (a format + a script + the rules for using them), not just a paragraph of prompt. If the script needs a tool that prompts for permission, the same ). The cost is context: everything in it is paid for on every turn.
Slash command — you-triggered, on demand. Use it when you decide the moment (/review,/deploy).
Skill — model-triggered, on demand. Use it when you want Claude to notice the situation and reach for the procedure itself.
The practical rule: standing context goes in CLAUDE.md; a procedure you invoke yourself is a slash command; a procedure Claude should invoke when it sees the trigger is a skill. Getting that split right is what keeps your everyday context lean while still having deep procedures on tap.
The honest workflow
Build the skill small, then watch whether it fires. Ask something that should trigger it and see if Claude reaches for it — if it doesn't, tighten the description and try again. That loop takes a couple of minutes and is the only real test that matters, because a skill that never gets invoked is just a Markdown file nobody reads.
This site runs its own automation on Claude Code and free-tier AI. If you're wiring up cheap models to do real work, we run everything on GLM's free tier through the is the referral that funds our compute (disclosed affiliate).
↗ Original-Artikel auf dev.to lesenVollständiger Original-BerichtAusführliche Details, Code-Beispiele & Hersteller-Stellungnahme auf dev.to.
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