Awesome-omni-skill repo-atlas

Build a self-contained persistent context system (atlas) for any repository. Use when asked to create a repo map, generate codebase documentation for LLM agents, set up an atlas, or create onboarding docs for a codebase. Also use when asked to "map this repo", "document this codebase", or "create context docs".

install
source · Clone the upstream repo
git clone https://github.com/diegosouzapw/awesome-omni-skill
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/diegosouzapw/awesome-omni-skill "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/data-ai/repo-atlas" ~/.claude/skills/diegosouzapw-awesome-omni-skill-repo-atlas && rm -rf "$T"
manifest: skills/data-ai/repo-atlas/SKILL.md
source content

Repo Atlas

Build an in-repo persistent context system so engineers and LLM agents can understand any codebase quickly with minimal searching.

Hard Constraints

  • Do NOT change product/runtime behavior
  • No paid/hosted tooling — everything lives in the repo
  • Zero or minimal dependencies (Python 3 standard library only)
  • All generated content must reflect real repo specifics, not generic filler

Workflow

Phase 1: Reconnaissance

Before writing anything, understand the repo:

  1. Read the top-level directory structure
  2. Identify the repo type:
    • App (web, mobile, desktop) — has screens/views, state managers, routes
    • Backend/API — has controllers, routes, middleware, models
    • Library — has public exports, module structure, build config
    • Monorepo — multiple packages/services
    • CLI tool — has command handlers, argument parsing
    • Infrastructure — has deployment configs, IaC files
  3. Identify the primary language(s) and framework(s)
  4. Find entrypoints, build configs, CI files
  5. Read 5-10 key files to understand architecture patterns

Phase 2: Run the Generator Script

Copy

scripts/generate_atlas.py
(bundled with this skill) to the repo at
scripts/atlas/generate_atlas.py
. Then customize and run it:

  1. Copy the script to the target repo
  2. Review and adjust the configuration section at the top:
    • IGNORE_NAMES
      — add repo-specific directory names to ignore (exact segment match)
    • TREE_ANNOTATIONS
      — add short descriptions for key directories
    • ENTRYPOINT_NAMES
      — add framework-specific entry filenames
    • ENTRYPOINT_PATH_PATTERNS
      — add path-based patterns (fnmatch style, e.g.,
      cmd/*/main.go
      )
    • ENTRYPOINT_CONTENT_MARKERS
      — add code markers that identify entry points
    • CONVENTIONAL_COMMITS
      — adjust if repo uses different commit conventions
    • CHANGELOG_DAYS
      — change the changelog lookback window (default: 14)
  3. Run:
    python3 scripts/atlas/generate_atlas.py --write

This auto-generates:

  • docs/atlas/repo-map.md
    — directory tree + entrypoints + file stats
  • docs/atlas/08_CHANGELOG_LAST_14_DAYS.md
    — categorized recent commits

Phase 3: Enhance repo-map.md

After the script generates the skeleton, manually add these sections to

repo-map.md
:

Router Table — "Where to look for X" (10-15 rows):

## Where to Look for X

| Task | Start Here |
|------|-----------|
| Fix [domain concept] | `path/to/file.ext` |

Map the top 10-15 tasks someone would do in this repo to specific files.

Danger Zones — fragile files/areas:

## Danger Zones

| File/Area | Why It's Fragile |
|-----------|-----------------|
| `path/to/file` | Reason |

Phase 4: Write Manual Atlas Docs

Create

docs/atlas/
with these files. See
references/atlas-templates.md
for structure guidance on each.

FileContent Source
00_README.md
How to use the atlas + agent workflow conventions
01_ARCHITECTURE.md
Read entrypoints, DI setup, module boundaries
02_DOMAIN_MODEL.md
Read models/types, identify state machines
03_CRITICAL_FLOWS.md
Trace top 3-5 user flows through the code
04_STATE_SOURCES_OF_TRUTH.md
Identify all state stores (DB, cache, files, memory)
05_EXTERNAL_DEPENDENCIES.md
Read package manifests + integration code
06_GOTCHAS.md
Look for race conditions, init ordering, fragile patterns
07_TEST_MATRIX.md
Read test configs, describe how to run tests

Each doc should be 50-150 lines with real paths, real code references, and real gotchas from the codebase. Not generic advice.

Phase 5: Add Agent On-Ramp

Add an atlas section to the repo's

CLAUDE.md
(or create one). Include:

## Atlas — Persistent Context System

The `docs/atlas/` folder contains structured documentation for fast codebase onboarding.

### Agent Workflow

**Agent A (Plan + Execute)**:
1. Load `docs/atlas/repo-map.md` for orientation
2. Load the domain-specific atlas doc for your task
3. Read source files only after the atlas narrows your search
4. Implement changes following the patterns in the atlas

**Agent B (Verify)**:
1. Review diffs against `docs/atlas/06_GOTCHAS.md`
2. Verify changes match the flow described in `03_CRITICAL_FLOWS.md`
3. Confirm tests pass per `07_TEST_MATRIX.md`
4. Check state consistency against `04_STATE_SOURCES_OF_TRUTH.md`

### Working Rules
- **Analysis first**: Read the relevant atlas docs before writing code
- **Verify behavior**: After changes, confirm critical flows still work
- **No test-cheating**: Tests must pass because the code is correct
- **Update atlas**: If changes alter architecture/flows/state, update the relevant doc
- **Regenerate**: Run `make atlas-generate` after structural changes

Phase 6: Add Build Targets

Add to

Makefile
(create if needed):

atlas-generate:
	python3 scripts/atlas/generate_atlas.py --write

atlas-check:
	python3 scripts/atlas/generate_atlas.py --check

If the repo uses

package.json
, also add to scripts:

"atlas:generate": "python3 scripts/atlas/generate_atlas.py --write",
"atlas:check": "python3 scripts/atlas/generate_atlas.py --check"

Phase 7: Verify

  1. Run
    atlas-generate
    — must complete without errors
  2. Run
    atlas-check
    — must exit 0 immediately after generation
  3. Confirm every atlas doc has real file paths and repo-specific content
  4. Confirm no runtime/product code was changed

Output Summary

After completing all phases, report:

  • List of created files
  • How to run atlas generation/check
  • 10-line "How an agent should use this atlas" quick reference

Resources

  • Generator script: See
    scripts/generate_atlas.py
    — copy to target repo and customize
  • Doc templates: See
    references/atlas-templates.md
    for structure guidance on each manual doc