agentleFS
cellrishi-codecellrishi-code/claude-skills-atlas/skills/coding/codebase-explorer/SKILL.md

codebase-explorer

Skill6 starsChanged 39 days agoMITView on GitHub

Use when entering an unfamiliar codebase and you need to understand architecture, entry points, dependencies, conventions, and data flow before editing.

9 other projects use a version of this.

Adopted by

Most recently taken up by

The file

We split this skill into the rules it gives an agent

1 rule. 0 are common, 1 is distinctive, and 0 are very specific to this project.

  • 0

    Common

    Most of the 8 edited versions we read keep these.

  • 1

    Distinctive

    This author's own choices. Worth a look.

  • 0

    Very specific

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

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Do not invent architecture that is not supported by the repository.

    line 32

“Common” is measured: kept by at least 6 in 10 of the 8 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Codebase Explorer

Instructions

Build a concise mental model from evidence in the repository.

Inspect, as relevant:

  • README and project documentation
  • package/build configuration
  • application entry points
  • directory structure
  • important modules
  • tests
  • configuration and environment handling

Then report:

  1. Project purpose
  2. Main entry points
  3. Major components
  4. Data/control flow
  5. Important conventions
  6. Relevant files for the requested task
  7. Unknowns that require further inspection

Do not invent architecture that is not supported by the repository.

Download now (ZIP)

Does it work?

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

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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.