/llmdoc

SkillWeb & browsing

Default V3 operating skill for llmdoc-enabled projects. Route discovery — exploring the codebase, locating a concept or contract, judging the blast radius of a change — through the llmdoc CLI instead of broad file crawling.

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the /llmdoc skill

What this skill tells your AI

The instructions your AI receives, as published by tokenrollai/llmdoc in skills/llmdoc/SKILL.md and read by ahel’s review.

Use the CLI to retrieve durable architecture, constraints, and working agreements from V3 llmdoc/ projects. Run commands as npx -y @tokenroll/llmdoc <cmd>.

Retrieval Gate

Apply this gate before the first discovery action of a task, and again whenever investigation crosses into a new subsystem. Choose the one entry point that matches the intent:

IntentEntry point
Concept, contract, term, "where is X?"search <query>
Background or blast radius of concrete source filescontext --files <path...>
Cold start, unclear scopetree
Known topic or document kindindex --topic <topic> / --kind <kind>
Bodies of documents already identifiedshow <path...>

The gate guards broad native discovery: recursive or cross-directory exploration with Read, Grep, Glob, or shell outside a working set llmdoc has already narrowed.

Once llmdoc has narrowed that working set, native tools own the exact facts — source text, line numbers, test behavior, counts, git state. The knowledge surface deliberately does not duplicate those.

These entry points are alternatives, not a sequence. Stop as soon as the task has enough context; that permission applies after choosing an entry point, never instead of choosing one.

status and delta are not retrieval. Use them to assess staleness or to prepare /llmdoc:update, where delta decides light vs deep.

CLI Invocation

@tokenroll/llmdoc is external tooling, not a project dependency. -y lets a missing package resolve into the npm cache without a prompt.

  • Never add it to the served project's package.json or lockfile.
  • Pin in the package spec when reproducibility matters: npx -y @tokenroll/llmdoc@<version> <cmd>.
  • Never call a bare npx llmdoc; that name resolves to an unrelated package.
  • If the CLI stays unavailable, report the degraded path, then continue with narrowly scoped native tools.

Operating Rules

  • Preserve and reuse LLMDOC_STATE across continuation; do not replay prior reads unless evidence changed or the task moved.
  • Temporary investigation notes belong in .llmdoc-tmp/, not in stable docs.
  • Stable llmdoc/ writes belong to recorder; llmdoc/meta.json changes go through the CLI only (new, adopt, mv, fingerprint, commit). A valid .mdx that already exists on disk gets its ledger entry via adopt <path...> — never the delete-and-recreate dance through new.
  • Before non-trivial edits, align with the user.
  • If llmdoc/ does not exist, suggest /llmdoc:init; do not fabricate the knowledge surface ad hoc.
  • When a task produces durable knowledge changes, suggest /llmdoc:update at the end.
  • For topology or routing work, read Knowledge Topology.
  • For SessionStart reminders or document preload, read Startup Configuration.
  • Never suggest /llmdoc:upgrade; it runs only when the user asks for it by name.

Reflection Gate

Strong reflection signals expose a reusable project or workflow lesson:

  • the user corrects an assistant assumption or action
  • verification proves the chosen approach wrong
  • substantial rework, rollback, or an instruction violation occurs
  • a missing project signal would likely prevent recurrence

Skip transient tool failures, trivial typos, speculation, and one-task preferences unless marked durable.

On a strong signal, continue the task and give reflector compact evidence while context is fresh. It writes a privacy-safe candidate under .llmdoc-tmp/reflections/pending/, never the transcript or tracked knowledge. A pending candidate triggers update review even with no source delta. At task end, name the lesson and ask once to run /llmdoc:update --reflection <path>; wait for authorization.

Continuation State

On compact or resume, keep LLMDOC_STATE small and practical:

  • active goal
  • documents already read
  • key conclusions and invariants
  • user decisions and constraints
  • next action
  • open risks or unknowns
  • pending lesson candidates, if any

If that state is still sufficient, continue without re-running tree, index, or prior show reads.

Roles

  • investigator: current-state research, scoped evidence gathering, scratch reports under .llmdoc-tmp/
  • reflector: turns strong corrections, verified mistakes, and major rework into structured candidates under .llmdoc-tmp/reflections/pending/
  • recorder: the only writer of tracked llmdoc/ knowledge

Signals

GitHub stars
477
Forks
52
Last commit
Sep 2026
Advanced
Catalog kind
skill
Gateway key
llmdoc
Source
github.com/tokenrollai/llmdoc