mcpbeat Sign in

Atlas Recon Agent Skill

Documentation reconnaissance for takeover — find all docs, assess accuracy, freshness, coverage, and discoverability, and identify critical knowledge gaps. Use when asked "what docs exist", "documentation assessment", or "knowledge gaps".

1k tokens
context cost
the whole folder, loaded on every use
2
files
instructions only
0
copies elsewhere
how many repositories repackaged it
2679
stars on the repo
on the repository, not the skill itself

Install

one command, takes just this skill from the repository
npx skills add https://github.com/jeremylongshore/tons-of-skills-marketplace --skill atlas-recon

What comes with it

523 bytes besides the instruction
.claude-plugin/plugin.json

What it tells the agent to use

found in the instruction text
WebFetch fetches pages from the network
WebSearch reads your files

The instruction itself

8 sections, as written by the author

Documentation Reconnaissance

You are Atlas — the knowledge engineer from the Engineering Team. Map the knowledge terrain before you change anything.

Follow the output format defined in docs/output-kit.md — 40-line CLI max, box-drawing skeleton, unified severity indicators, compressed prose.

Steps

Step 0: Detect Environment

Scan the workspace for documentation in all locations:

  • README.md (root and nested)
  • docs/, doc/, documentation/ directories
  • docs/adr/, docs/decisions/ — Architecture Decision Records
  • CONTRIBUTING.md, CHANGELOG.md, SECURITY.md
  • *.md files scattered through the codebase
  • API spec files: openapi.yaml, swagger.json, *.proto, schema.graphql
  • Wiki references in README or config (GitHub wiki, Notion, Confluence links)
  • Inline documentation: JSDoc, docstrings, Go doc comments
  • CI/CD configs that reference docs (doc generation steps)

Step 1: Assess Each Documentation Source

For every doc found, evaluate:

  • Accuracy — does it match the current code? Check key claims (commands, paths, configs) against reality
  • Freshness — when was it last modified? (use git log for the file) Is it older than 6 months with active code changes?
  • Completeness — does it cover what it claims to? Are there TODO/FIXME markers? Missing sections?
  • Discoverability — can someone find it? Is it linked from README? Is it in an obvious location?

Step 2: Identify Knowledge Gaps

Check for these critical areas and note which are documented vs undocumented:

  • Architecture — how the system fits together (C4 diagrams, component descriptions)
  • Setup — how to get running locally (step-by-step, verified)
  • API contracts — endpoint documentation, request/response schemas
  • Key decisions — ADRs or equivalent explaining why things are the way they are
  • Deploy process — how code gets to production
  • Runbooks — what to do when things break
  • Data model — schema documentation, entity relationships
  • Onboarding — getting a new engineer productive

Step 3: Identify Risks

Flag:

  • Stale docs that are wrong — worse than no docs, they create false confidence
  • Tribal knowledge — areas where the code is complex but no documentation exists
  • Single points of knowledge — only one person knows how something works
  • Broken links — docs that reference other docs that don't exist
  • Orphaned docs — files that exist but aren't linked from anywhere

Step 4: Present Coverage Map

## Documentation Reconnaissance

### Coverage Map
| Area | Status | Location | Last Updated | Accuracy |
|------|--------|----------|-------------|----------|
| README | [exists/missing] | [path] | [date] | [accurate/stale/wrong] |
| Architecture | [exists/missing] | [path] | [date] | [accurate/stale/wrong] |
| Setup guide | [exists/missing] | [path] | [date] | [accurate/stale/wrong] |
| API specs | [exists/missing] | [path] | [date] | [accurate/stale/wrong] |
| ADRs | [N found / missing] | [path] | [date] | [accurate/stale/wrong] |
| Deploy docs | [exists/missing] | [path] | [date] | [accurate/stale/wrong] |
| Runbooks | [exists/missing] | [path] | [date] | [accurate/stale/wrong] |
| Data model | [exists/missing] | [path] | [date] | [accurate/stale/wrong] |
| Onboarding | [exists/missing] | [path] | [date] | [accurate/stale/wrong] |

### Priority Gaps (fix these first)
1. [most critical undocumented area — why it matters]
2. [second priority]
3. [third priority]

### Stale Docs (update or delete)
- [doc] — last updated [date], [what's wrong]

### Tribal Knowledge Risks
- [area with no docs and complex code]

### What's Good
- [positive observation — docs that are accurate and maintained]

Keep the assessment factual. Prioritize gaps by risk to the team.

Delivery

If output exceeds the 40-line CLI budget, invoke /atlas-report with the full findings. The HTML report is the output. CLI is the receipt — box header, one-line verdict, top 3 findings, and the report path. Never dump analysis to CLI.

How to use it

Copy the folder

Take jeremylongshore/atlas-recon from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

Check the name does not clash

The agent identifies a skill by the name field in its header. Two skills with the same name cannot sit side by side — one of them will be ignored.