agentleFS
LL4nc33LL4nc33/code-workspace-engine/skills/project-docs/SKILL.md

project-docs

Skill0 starsChanged 7 months agoMITView on GitHub

Use when docs need updating: README generation, docs freshness checks, tech stack badge detection, architecture diagram updates. Triggered by researcher (docs update|check) or devops (release).

22 other projects use a version of this.

Adopted by

Most recently taken up by

Used with

Projects with it also use test-audit, to-issues and 3 more.

Other files people use alongside this one.

Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
  • BlockSkill

    test-audit

    Invoke whenever writing, changing, reviewing, or sweeping tests in buzz-app. Authoring gate for new tests plus audit workflow for low-value, implementation-coupled, or duplicative tests and the test-only production seams they demand.

    Also in 3 projects that use this

  • GoogleSkill

    to-issues

    Break a plan, spec, or PRD into independently-grabbable issues on the project issue tracker using tracer-bullet vertical slices.

    Also in 3 projects that use this

  • GoogleSkill

    to-prd

    Turn the current conversation into a PRD and publish it to the project issue tracker — no interview, just synthesis of what you've already discussed.

    Also in 3 projects that use this

  • Google CloudSkill

    triage

    Gather context on a change or bug and plan the implementation.

    Also in 3 projects that use this

  • BlockSkill

    frontend-design

    Create distinctive, production-grade frontend interfaces with high design quality. Use this skill when the user asks to build web components, pages, or applications. Generates creative, polished code that avoids generic AI aesthetics.

    Also in 3 projects that use this

The file

We split this skill into the rules it gives an agent

8 rules. 0 are common, 5 are distinctive, and 3 are very specific to this project.

  • 0

    Common

    Most of the 18 edited versions we read keep these.

  • 5

    Distinctive

    This author's own choices. Worth a look.

  • 3

    Very specific

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

  • Common
  • Distinctive
  • Very specific
  1. Very specific:

    After /cwe:init — generate initial docs from mission.md

    line 16
  2. Distinctive:

    After spec completion — update docs to reflect new features

    line 17
  3. Distinctive:

    After release — update VERSION references, CHANGELOG

    line 18
  4. Distinctive:

    Read these files (if they exist):

    line 26
  5. Very specific:

    Use template from ${CLAUDE_PLUGIN_ROOT}/templates/docs/README.md.

    line 51
  6. Very specific:

    If docs/ARCHITECTURE.md exists, check if the Mermaid diagram matches current structure.

    line 56
  7. Distinctive:

    If not, suggest updates based on actual file structure.

    line 57
  8. Distinctive:

    When VERSION changes, update these files:

    line 82

“Common” is measured: kept by at least 6 in 10 of the 18 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

Project Documentation Skill

Generate and maintain project documentation from source truth.

When to Use

  • After /cwe:init — generate initial docs from mission.md
  • After spec completion — update docs to reflect new features
  • After release — update VERSION references, CHANGELOG
  • On docs update — full refresh
  • On docs check — validate freshness

README Generation

Step 1: Gather Project Metadata

Read these files (if they exist):

  • VERSION — current version
  • workflow/product/mission.md — vision, goals
  • workflow/config.yml — project config
  • package.json / Cargo.toml / go.mod / pyproject.toml — tech stack
  • Dockerfile — containerization
  • .github/workflows/ — CI/CD

Step 2: Auto-Detect Tech Stack

Scan project root for indicators:

FileTechnologyBadge
package.jsonNode.jsnode, npm/yarn/pnpm
tsconfig.jsonTypeScripttypescript
Cargo.tomlRustrust
go.modGogo
pyproject.toml / requirements.txtPythonpython
DockerfileDockerdocker
.github/workflows/GitHub Actionsactions
terraform/Terraformterraform

Step 3: Generate docs/README.md

Use template from ${CLAUDE_PLUGIN_ROOT}/templates/docs/README.md. Replace placeholders with detected values.

Step 4: Architecture Diagram

If docs/ARCHITECTURE.md exists, check if the Mermaid diagram matches current structure. If not, suggest updates based on actual file structure.

Docs Freshness Check

Compare docs against codebase:

CheckMethod
VERSION matchesCompare VERSION file with docs references
API docs currentCompare API.md endpoints with actual route files
SETUP accurateVerify install/dev commands still work
ARCHITECTURE currentCheck if documented components still exist

Output a report:

Docs Freshness Report:
  docs/README.md      — current (VERSION matches)
  docs/API.md         — STALE (3 endpoints missing)
  docs/SETUP.md       — current
  docs/ARCHITECTURE.md — STALE (new module not documented)

VERSION Cascade

When VERSION changes, update these files:

  1. docs/README.md — version reference
  2. CHANGELOG.md — new version section header
  3. .claude-plugin/plugin.json — version field (if CWE plugin project)
  4. package.json — version field (if exists)
  5. Any other files containing the old version string

Rules

  1. Never invent content — only generate from actual project data
  2. Preserve custom edits — detect <!-- custom --> markers and keep them
  3. Template-first — always start from templates, never from scratch
  4. Idempotent — running twice produces the same result

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.

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.