AI Skills: One Folder, Any Model
TL;DR A Claude Code skill is just a folder with a SKILL.md file - YAML frontmatter plus natural-language instructions - and the same folder works across Cursor, Gemini CLI, Codex, and a dozen other tools The format is model-agnostic because it contains no provider-specific syntax; any instruction-following model can read it, and any harness that loads markdown can execute it Progressive disclosure keeps large skill libraries cheap: only names and descriptions load at session start, with full instructions loading only when a skill is activated The portability is practically valuable - version-controlled runbooks that survive tool switches, model upgrades, and team growth without being rewritten Core skills are genuinely portable; advanced frontmatter extensions (like allowed-tools or context: fork) are tool-specific and may need tuning across harnesses Most of the tooling I have written about over the last year has been provider-specific. A particular model, a particular harness, a particular set of features. The thing I find interesting about agent skills is that they are not. ...