open-knowledge-write-skill

Writing an OpenKnowledge skill

You are helping the user author an Agent Skill — a SKILL.md file (plus optional references/ and scripts/) that teaches an AI agent how to do a recurring task. In OpenKnowledge a skill is a first-class, versioned, installable artifact: you author it with the write / edit skill verbs, then install it into the user's editors.

Skills earn their keep by being recognized at the right moment and followed faithfully. Most of the craft is in two places: a description that triggers reliably, and a body short and concrete enough that the agent actually does what it says. Work the stages below in order, but jump to where the user already is.

Stage 1 — Capture intent and classify the skill

Gate — does this already exist? Check BEFORE you build. First list managed skills with skills({}), then read any likely match with skills({ name }); these are the Project/Global skills OpenKnowledge already manages. Also search the public marketplace with skills({ query: "<2-4 trigger words>" }) before drafting when the task sounds reusable beyond this project. Each marketplace row returns name, source, and description; inspect the strongest descriptions, then import a chosen candidate with import({ source, skill: name, add: [...] }) and adapt it only if reuse is the right call. Use the Vercel find-skills skill, npx skills find <query>, or manual skills.sh search only when the OK MCP skills({ query }) path is unavailable. If the user already has a skills.sh page open, pass the full skill-page URL as source, e.g. import({ source: "https://www.skills.sh/<owner>/<repo>/<skill>", add: [...] }) — the middle segment is the REPO, not a literal skills. Do not run npx skills add as the default install path in this flow: import through OpenKnowledge (import({ source, skill, add })) so the skill lands as a real folder with provenance, versioning, and managed fan-out; add says where it goes, and install afterwards changes where it lives. Use 2-4 concrete trigger phrases from the user's request plus the domain or tool name, then open/read the strongest candidates' descriptions before judging. If an existing or public skill covers most of it, STOP and recommend reuse — a near-duplicate with overlapping triggers mis-fires and dilutes both. If a public skill is close but not exact, decide WITH the user whether to import/adapt it into OpenKnowledge, install it outside OK with the Skills CLI, or write a narrower companion whose description explicitly hands off to it. Build a new skill only when it is genuinely distinct. Surface the overlap and the installed-skill plus marketplace search outcome before drafting or writing anything. This is a disclosure gate: tell the user what you checked, what matched, and why reuse/import/adapt/new-skill is the right next step. Never discover overlap after the skill is written. If skills({ query }) / skills.sh is unreachable, say so plainly and continue with the installed-skill check.