Agent skill · writing content · jeremylongshore
atlas-recon
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".
Why this skill is useful
Provides a structured approach to documentation assessment that the AI wouldn't reliably generate on its own.
What it needs
About 3k tokens when loaded. Last updated 2026-08-07. 2,604 stars on the source repository.
What this skill does
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 cre …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills jeremylongshore/atlas-recon