agentleFS
ulpi-ioulpi-io/autonomous-engineering/auto-map/SKILL.md

auto-map

Skill2 starsChanged 4 months agoNo licenceView on GitHub

Generate and refresh the project's CONTEXT ARCHITECTURE — a disclosure-tiered map so the agent starts every session knowing the repo without paying for what it doesn't need. Platform-aware by explicit contract (claude|codex|dual): for Claude a lean root CLAUDE.md (loads always), path-scoped .claude/rules/*.md (load only when touching matching files), nested CLAUDE.md throughout the tree (loaded on demand — zero cost until then); for Codex the root + nested AGENTS.md tree instead — never inventing a memory location the platform lacks, never touching private agent memory. Deep references are LINKED, never imported. Every claim is VERIFIED against the real repo before it ships (commands actually run; paths actually exist) — the map cannot lie. Use to initialize project context, refresh it after meaningful changes, or as the pipeline's final phase so the map reflects what just shipped.

The file

Show its rules and text

We split this skill into the rules it gives an agent

13 rules. About 0 are common, 7 are distinctive, and 6 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈7

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 6

    Very specific

    Tied to their project's names, files or tools. Probably skip.

No licence file, so all rights are reserved — read it at the source. We count its rules but don't quote them. Read them on GitHub.

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.