Loading
Use when the user wants to create, author, write, or design a new Agent Skill (a SKILL.md) — for OpenKnowledge or for their editors — including requests like 'help me write a skill', 'make a skill tha
The skill file stays in the publisher's repository.
Paste the copied command in a terminal. It installs this SKILL.md into that agent.
npx skills add inkeep/open-knowledge --skill write-skill -a cursor -y
Use when the user wants to create, author, write, or design a new Agent Skill (a SKILL.md) — for OpenKnowledge or for their editors — including requests like 'help me write a skill', 'make a skill that…', 'turn this workflow into a skill', or improving an existing skill's triggering and discipline. Also use when capturing reusable agent guidance that should live as an installable skill rather than a one-off prompt. Covers choosing scope (project vs global), authoring inside a plugin or skills-distribution repo (write in the repo's own layout, never install), the SKILL.md frontmatter contract, progressive-disclosure structure, evaluating the skill, and installing it into the user's editors.
Use when the user wants to create, author, write, or design a new Agent Skill (a SKILL.md) — for OpenKnowledge or for their editors — including requests like 'help me write a skill', 'make a skill that…', 'turn this workflow into a skill', or improving an existing skill's triggering and discipline. Also use when capturing reusable agent guidance that should live as an installable skill rather than a one-off prompt. Covers choosing scope (project vs global), authoring inside a plugin or skills-distribution repo (write in the repo's own layout, never install), the SKILL.md frontmatter contract, progressive-disclosure structure, evaluating the skill, and installing it into the user's editors.
write / edit / install MCP verbs). Authoring + validation are pure file ops; live preview + eval want a running server (ok start, or ok-beta start for Beta)."
metadata:
author: "Inkeep"
repository: "https://github.com/inkeep/open-knowledge-skills"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.
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.
Ask only what you can't infer:
scripts/ command — when any deviation breaks the result). Don't
over-specify a judgment task or under-specify a fragile one.Scope determines where the skill lives and where install fans it. This is
the user's decision and has different blast radius — make it explicit.
| Scope | Lives in | install fans it to |
|---|---|---|
| Global | a real folder under your home's skill roots (e.g. ~/.claude/skills/<name>/) | your editors, in every project |
| Project | a real folder in this repo's skill roots (e.g. .claude/skills/<name>/ or the .agents/skills/ hub — shared via git) | this project's editors; teammates get it on git pull |
Default heuristic: inside an OK project and the task is specific to it → project; "for all my work / globally" → global; otherwise ask one question. State the choice and its consequence before writing.
Developing a skills repo or plugin? Then NEITHER scope applies. If the repo
you are working in is itself a skill distribution — a plugin (e.g. a
.claude-plugin/ manifest or marketplace listing) or a catalog repo that
shelves skills as skills/<name>/ for others to import — the skill you are
authoring is a product of that repo, not an installation into it. Write it
in the repo's own layout, beside its sibling skills, following the format the
repo already uses. Do not place it under .claude/skills/ or
.agents/skills/ here, and do not install it: consumers get it by
installing the plugin or importing from the repo, and the plugin's own repo
loads nothing from itself. install is only for skills the current project
or user should load. If you are unsure whether the repo is a distribution or a
consumer, ask — writing to the wrong place ships a skill nobody can find.
references/<topic>.md (loaded only when
needed) and point at it from the body. For a project skill the reference
auto-connects in the graph either way, so a backticked `references/<topic>.md`
path is fine; use a [[references/<topic>]] wiki-link only when you want the
mention to be a clickable inline link. For a global skill use a plain
backtick path — global references aren't graph docs, so a wiki-link there
dangles. Keep references one level deep.Before writing the skill, run the scenario WITHOUT it and capture what the agent does wrong — verbatim, including its rationalizations ("the test is trivial so I skipped it"). Those rationalizations are the exact loopholes the skill body must close. Run the scenario in a fresh agent session with the skill absent — a new chat, a sub-agent, or a second terminal — and keep the transcript; if you have no way to run it clean, reason through the baseline with the user instead. Skip this stage for plain reference skills.
Author the source with the skill verb (fs-direct; a live preview updates if a server is running):
write({ skill: { name: "<lowercase-hyphen-name>", description: "<triggers>", body: "<markdown>", scope: "project" } })
Frontmatter contract (validated on write — get it right):
name — lowercase letters, digits, hyphens; ≤64; equals the directory.description — ≤1024 chars, no XML tags, no version field. See Stage 7..ok/.Write the body as direct instructions to the agent (imperative, second person), concrete over abstract.
Add depth files — references/*.md (loaded on demand) and scripts/* (shown as
text, never executed by OK) — through the skill verbs, never native Write/cat:
# write one or more bundle files (independent of body — no need to resend SKILL.md)
write({ skill: { name: "<name>", files: [{ path: "references/tiers.md", content: "..." }] } })
# surgical edit inside one bundle file (mirrors edit({ document }))
edit({ skill: { name: "<name>", file: "references/tiers.md", find: "...", replace: "..." } })
# list the bundle, then read one file (no native cat)
skills({ name: "<name>" }) # → files: [{ path, kind }]
skills({ name: "<name>", file: "references/tiers.md" }) # → { path, kind, text }
# delete specific bundle files (omit `files` to delete the whole skill)
delete({ skill: { name: "<name>", files: ["references/tiers.md"] } })
Paths are skill-relative and must stay inside the skill dir (no ../, no
absolute paths). references/ and scripts/ are the conventional homes and the
ones to reach for; other roots (assets/, a per-harness dir) are accepted
because published skills ship them and an import preserves them verbatim. Keep
references one level deep. A project .md reference becomes a live content doc that
auto-connects to its SKILL in the graph regardless of how the body mentions it —
a backticked `references/<name>.md` path joins the graph just like a
[[references/<name>]] wiki-link. Reach for a wiki-link (or
[label](references/<name>.md)) only when you want a clickable inline link.
Global skills are different: their references aren't graph docs, so use a plain
backtick path there — a wiki-link would dangle.
Re-run the scenario WITH the skill. For a discipline skill, pressure-test:
combine 2–3 pressures (time, authority, sunk cost) and confirm the agent still
follows the rule — then patch any loophole and re-test (references/pressure-testing.md).
For a reference skill, confirm the agent now does the task correctly and the body
isn't longer than it needs to be. Cut anything the agent already knows.
The description is the only thing the agent sees when deciding whether to
load the skill. Get it right (references/description-optimization.md):
The skill is already live for whichever agent reads the folder it was created
in — its own folder IS the skill (there is no draft state). install manages
WHERE ELSE it is available, additively:
install({ name: "<name>", add: ["codex", "opencode"] }) // add locations
install({ name: "<name>", remove: ["codex"] }) // remove locations
install({ name: "<name>", add: ["codex"], mode: "link" }) // ...as a symlink
install({ name: "<name>", convert: ["codex"], mode: "copy" }) // change one location's form
install({ name: "<name>", source: ".team/skills" }) // move the real folder (run alone)
Location ids are editor host ids (claude … pi), agents (the
vendor-neutral hub), or a custom root path like .team/skills.
Which form a location takes. mode applies only to the locations the call
names — those in add, or those in convert — and to nothing else. Omit it on
add and the new location takes the form the skill already uses. There is no
skill-wide mode: installing never rewrites a location you did not name.
Changing an existing location is convert, which leaves membership alone; pass
every location to make them uniform.
What each form means. A symlink points at the source, so it cannot drift. A copy is its own folder. A recorded, unedited copy refreshes from the source when the skill watcher runs or the server starts, so it may briefly lag a source edit. A hand edit forks the copy and prevents further automatic overwrites.
Lifecycle. Edit with edit({ skill }); it routes to the source and versions
in place. There is no "uninstall everywhere" — removing every other location
still leaves the source folder loading for its agent, and a skill stops existing
only via delete({ skill }), which removes the source and every location. Roll
a project skill back with history({ skill }) → restore_version({ skill, version }); global skills are unversioned in this build. For a project skill,
commit the skill folders — they are ordinary files in git, so teammates get them
on pull.
write({ skill }) — it lands as a real folder at the project's default skill home with attribution and versioning — and fan it out with install; don't hand-scatter copies across editor dirs, because install owns fan-out; recorded, unedited copies refresh on watcher/startup sync (a hand-edited copy forks and stops refreshing). If you load this flow, author through it.scripts/ is projected verbatim into another
agent's trust domain — only include scripts the user has reviewed.