| name | skillit-bootstrap |
| description | 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. |
| version | 0.1.0 |
| skillit | {"managed":"bundled-orchestrator"} |
skillit-bootstrap
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.
The one hard rule
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.
When to use
- A
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.
- Run after the project is set up with the right
@skillit/* package (see
step 1).
- Third-party MCP servers you cannot edit are out of scope here: with no
editable source, the skill is produced from an overlay ("runtime mode") via
skillit refine. This loop targets the build-mode (own-source) path. See
references/surface-routing.md.
Inputs
/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.
The loop
- Set up once. Determine the source kind (honor
--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).
- Generate. Run
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.)
- Audit. Run
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.
- Enrich the source. For each addressable finding, open the cited source
file and write the missing content on the named symbol/section/key, choosing
the surface the suggestion names. The surface → audit-code map and the
edit-vs-create guidance are in
references/surface-routing.md. Before writing
any runtime-behavior pitfall, read the relevant implementation (--ground
globs) — do not invent semantics from a type signature.
- Prefer the
upsertJsDocTag / upsertPropertyJsDocTag helpers (exported
from @skillit/core) for JSDoc-tag writeback rather than free-hand
splicing — they handle */ escaping and multi-line prefixing.
- You may also create a new parseable artifact when that is the better
home (a
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.
- Regenerate + re-audit. Re-run step 2 then step 3. Compare the new
estimate to the previous pass.
- Decide convergence (your judgment, using these signals):
- 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.
- Plateau — the score did not rise AND every remaining finding targets a
symbol that genuinely has nothing more to truthfully say. You can see the
source, so distinguish "legitimately complete" from "stuck re-drafting" —
stop on the former.
- Cap — never exceed
--max-iterations (default 5).
- Report. Print the final grade, the D1–D8 breakdown, the list of source
files you enriched, and any remaining findings you judged un-addressable with
a one-line rationale each. This is the human review surface; the user commits
the result.
After convergence
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.