skillit
무료Generate structured AI agent skills (SKILL.md) and llms.txt from your TypeScript API documentation
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Bootstrap an AI-agent skill from a TypeScript codebase by running the deterministic skillit generate/audit loop and enriching repo source (JSDoc, README, config-type properties, MCP tool annotations, examples, package.json) until the skill reaches its grade target. Use for cli, typedoc, config, or mcp (build-mode) projects; never edit SKILL.md/references directly.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
설치 방법 보기설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.
Bootstrap a high-quality AI-agent skill from a TypeScript codebase. You run the deterministic skillit pipeline, read its machine-readable findings, and enrich the repo source (JSDoc, README, examples, package.json) until the generated skill reaches its grade target. skillit owns the skill output; you own the inputs.
Never create or edit any SKILL.md or references/*.md for the target
project. Those are pure outputs of skillit gen — regenerated every pass. You
edit only repo source surfaces. If you find yourself about to write a
SKILL.md, stop: the fix belongs in the source the skill is generated from.
cli (Commander), typedoc (TypeScript library), config (a TypeScript
config type), or mcp (an MCP server whose TS source you own — "build mode")
project that needs a generated agent skill, or whose skill scores below its
grade target.@skillit/* package (see
step 1).skillit refine. This loop targets the build-mode (own-source) path. See
references/surface-routing.md./skillit-bootstrap [--source cli|typedoc|config|mcp] [--program <file#export>]
[--config-type <file#export>] [--mcp <path>] [--server <name>]
[--out <dir>] [--grade A|B|C] [--max-iterations <n>]
[--ground <glob>...]
--source — override detection (cli, typedoc, config, or mcp).--program — Commander program entry for the cli source (./dist/cli.js#program).--config-type — config type entry for the config source (./src/config.ts#MyConfig).--mcp — path to mcp.json / MCP config file (mcp source).--server — MCP server entry to select when the config lists several (mcp source).--out — skill output dir (default skills).--grade — override the kind-aware target (below).--max-iterations — hard cap on enrich/regenerate passes (default 5).--ground <glob> — consumer/implementation code you MUST read before writing
any runtime-behavior pitfall, so your claims reflect real behavior, not guesses.--source, else infer:
commander/yargs dep → cli; @modelcontextprotocol/sdk dep → mcp;
otherwise a TS library → typedoc). config is never auto-detected — select it
explicitly with --config-type <file#export>. Each kind has its own selector:
cli → --program, config → --config-type, mcp → --mcp (+ optional
--server); typedoc needs none. If the project has no @skillit/* package
installed yet, run skillit init --source <kind> once (it installs + wires
only; it does not generate).skillit gen --source <kind> <selector> [--out …] (the
selector is the kind's from step 1). This deterministically produces the skill
from current source. Never hand-edit its output. (For mcp, gen spins up the
server to introspect it, so the source skill is a function of a deterministic
server.)skillit audit --source <kind> <selector> --json and read
the JSON: estimate.grade, estimate.dimensions (D1–D8), and
improvements[]. Each improvement carries suggestion, dimension,
targets: [{file, name, kind}], and (when resolvable) resolvedLocations[]
pointing at the exact file + declaration to edit. These targets are your
work queue.references/surface-routing.md. Before writing
any runtime-behavior pitfall, read the relevant implementation (--ground
globs) — do not invent semantics from a type signature.
upsertJsDocTag / upsertPropertyJsDocTag helpers (exported
from @skillit/core) for JSDoc-tag writeback rather than free-hand
splicing — they handle */ escaping and multi-line prefixing.docs/<guide>.md, an examples/<name>.ts, a missing README
section) — but only of a type an existing parser already consumes, and
never a SKILL.md.estimate to the previous pass.estimate.grade ≥ the target. Default target is kind-aware:
typedoc/library → A (every export is introspectable); cli adapter-model
→ B, config → B, mcp → B — these surfaces structurally cap below
A (a cli command tree isn't enumerated per-symbol; a config type has no
functions/params, so per-option routing + one example file is its ceiling;
mcp reaches A only if every tool handler carries full JSDoc). --grade
overrides.--max-iterations (default 5).Tell the user to review the enriched source diffs and the regenerated skill,
then commit. Remind them the skill is reproducible: skillit gen on the same
source yields byte-identical output, so the source diff is the real change.
아직 리뷰가 없습니다. 사용해 본 소감을 남겨 주세요.
로그인 없이 쓸 수 있습니다. 사용 후기, 질문, 작동하지 않은 환경 등을 편하게 남겨 주세요.
아직 댓글이 없습니다. 첫 댓글을 남겨 보세요.
Generate structured AI agent skills (SKILL.md) and llms.txt from your TypeScript API documentation
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Extract CLI command structure from commander/yargs for AI agent skill generation Use when working with agent-skills, cli, commander, documentation, skill-generation, yargs.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
CLI documentation conventions for generated skills. Use when improving Commander descriptions, help text, positional argument docs, and config-surface correlation.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Shared types, SKILL.md renderer, and token budgeting for skillit plugins
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Documentation conventions for generating high-quality AI agent skills from TypeScript source. Use when preparing a library for skill generation, auditing JSDoc quality, fixing audit warnings, writing @useWhen/@avoidWhen/@never tags, or asking about documentation conventions for skills.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Generate AI agent skills from TypeScript documentation
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.