
Context Map
- 76 installs
- 325 repo stars
- Updated August 2, 2026
- athola/claude-night-market
context-map is an agent skill that emits a compressed repo map so agents skip redundant file reads.
About
context-map is an agent skill that generates a compressed project context map so solo builders and their assistants avoid expensive Read and Grep discovery on every session. The SKILL.md positions it at session start, before feature work, and when exploring an unfamiliar codebase—exactly when token waste hurts most on Claude Code, Cursor, or Codex. It pre-compiles structure, multi-ecosystem dependencies, entry points, import relationships, blast-radius hot files, HTTP routes, env var usage, and middleware hints into a single map developers can skim before touching code. That turns vague “where does auth live?” questions into guided entry points and reduces the chance you refactor a highly imported module by accident. Complexity is intentionally low: no production deploy steps, just exploration hygiene. Pair it with implementation or review skills once the map highlights the files that matter.
- Detects directory layout with file counts and languages across Python, Node, Rust, Go, and Java ecosystems
- Builds an import graph and flags hot files imported by three or more others before you edit
- Surfaces framework hints from dependencies plus API routes for FastAPI, Flask, Express, and Hono
- Lists environment variable references with defaults and common middleware patterns
- Frontmatter estimates ~300 tokens and targets fast models for session-start scans
Context Map by the numbers
- 76 all-time installs (skills.sh)
- Ranked #1,473 of 3,282 Productivity & Planning skills by installs in the Skillselion catalog
- Security screen: MEDIUM risk (skills.sh audit)
- Data as of Aug 5, 2026 (Skillselion catalog sync)
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| Installs | 76 |
|---|---|
| repo stars | ★ 325 |
| Security audit | 2 / 3 scanners passed |
| Last updated | August 2, 2026 |
| Repository | athola/claude-night-market ↗ |
What it does
Build a one-screen structural map of an unfamiliar repo so your agent stops burning tokens on blind Read and Grep loops.
Who is it for?
Best when you're jumping into monorepos or client codebases and want a fast structural briefing before the first real edit.
Skip if: Skip if you already maintain up-to-date architecture docs and do not need automated rescans each session.
When should I use this skill?
At session start or before implementing features in an unfamiliar codebase, per SKILL.md When to Use.
What you get
You get a structural map with import graph, hot files, routes, and env references so the next implementation or review step targets the right entry points.
- Compressed context map covering structure, dependencies, entry points, import graph, routes, and env references
- Hot-file list highlighting high blast-radius modules
By the numbers
- Estimated ~300 tokens in skill frontmatter for the map workflow
- Hot files defined as those imported by 3+ other files
Files
Context Map
Generate a compressed context map for the current project. The map pre-compiles structural knowledge that AI assistants would otherwise discover through expensive Read/Grep calls, saving thousands of tokens per session.
When to Use
- At the start of a session to understand project layout
- Before implementing features to identify entry points
- When exploring an unfamiliar codebase
- To reduce token waste from Read calls
- To identify hot files (high blast radius) before changes
What It Detects
| Category | Description |
|---|---|
| Structure | Directory layout with file counts and languages |
| Dependencies | Multi-ecosystem: Python, Node, Rust, Go, Java |
| Frameworks | Framework detection from dependency analysis |
| Entry Points | main.py, index.ts, CLI scripts, etc. |
| Import Graph | File-to-file import relationships |
| Hot Files | Files imported by 3+ others (high blast radius) |
| Routes | FastAPI, Flask, Express, Hono API endpoints |
| Env Vars | Environment variable references with defaults |
| Middleware | Auth, CORS, rate-limit, logging patterns |
| Models/Schemas | SQLAlchemy, Django, Pydantic, Prisma definitions |
| Token Savings | Estimated tokens saved vs manual exploration |
Procedure
1. Run the scanner on the project root:
PYTHONPATH="$(find . -path '*/conserve/scripts' -type d \
-print -quit 2>/dev/null || \
echo 'plugins/conserve/scripts')" \
python3 -m context_scanner .2. Present the output to the user as the project overview.
3. Use the context map to guide subsequent file reads. Prioritize hot files and entry points first.
Options
Output
--format jsonfor structured output--max-tokens Nto adjust output size (default: 5000)--output FILEto save to a file
Modes
--blast FILEto show blast radius for a specific file--section NAMEto output a single section
(routes, deps, env, hot-files, models, structure, middleware, frameworks)
--wiki-onlyto generate wiki articles without stdout
Opt-out
--no-cacheto force a fresh scan--no-wikito skip wiki article generation
Wiki Articles
The scanner generates per-topic knowledge articles in .codesight/ for selective context loading:
python3 scanner.py .
# Creates .codesight/INDEX.md, auth.md, database.md, etc.Load only what you need per session instead of the full map:
python3 scanner.py --section routes .
# ~200 tokens vs ~5,000 for the full mapExample Output
# Context Map: myproject
Files: 127
## Structure
src 42 files (Python)
tests 18 files (Python)
docs 5 files (Markdown)
## Dependencies (Python)
Package manager: uv
- fastapi 0.104.0
- pydantic 2.5.0
- sqlalchemy 2.0.0
...12 more
## Frameworks Detected
- FastAPI
- SQLAlchemy
- Pytest
## Routes
GET /users (src/routes/users.py)
POST /users (src/routes/users.py)
GET /users/{id} (src/routes/users.py)
## Hot Files (high blast radius)
- src/models/base.py (12 importers)
- src/utils/auth.py (8 importers)
## Environment Variables
- DATABASE_URL (required)
- SECRET_KEY (has default)
## Token Savings: ~12,600 tokens saved
Routes: ~1,200
Hot files: ~300
Env vars: ~200
File scanning: ~10,200Exit Criteria
- [ ] Scanner produces output covering at minimum: file count,
directory structure, detected frameworks, and hot files (imported by 3+ others); output appears in the session before any feature implementation reads begin
- [ ] "Token Savings" line is present in the output with a numeric
estimate (e.g., ~12,600 tokens saved)
- [ ] If
--blast FILEis used, blast-radius output names the
specific file and lists its importers by count
- [ ] Context map guides subsequent reads: hot files and entry points
are consulted before any other file read in the session
Related skills
How it compares
Token-saving exploration generator, not a deep static-analysis security audit or test runner.
FAQ
Who is context-map for?
Developers and agent users who frequently start cold sessions in unfamiliar or large repositories and need layout without a manual tour.
When should I use context-map?
Use it at Build (agent-tooling) session start, at Idea (discover) when surveying a new repo, and at Ship (review) before editing files the import graph marks as hot.
Is context-map safe to install?
Check the Security Audits panel on this Prism page; the skill scans project structure locally and you should confirm it matches your org’s rules for repository introspection.