Generate project documentation from codebase analysis — ARCHITECTURE.md, API_ENDPOINTS.md, DATABASE_SCHEMA.md. Reads source code, schema files, routes, and config to produce accurate, structured docs. Use when starting a project, onboarding contributors, or when docs are missing or stale. Triggers: 'generate docs', 'document architecture', 'create api docs', 'document schema', 'project documentation', 'write architecture doc'.
npx skills add https://github.com/jezweb/claude-skills --skill project-docs
Generate structured project documentation by analysing the codebase. Produces docs that reflect the actual code, not aspirational architecture.
Scan the project root to determine what kind of project this is:
| Indicator | Project Type |
|-----------|-------------|
| wrangler.jsonc / wrangler.toml | Cloudflare Worker |
| vite.config.ts + src/App.tsx | React SPA |
| astro.config.mjs | Astro site |
| next.config.js | Next.js app |
| package.json with hono | Hono API |
| src/index.ts with Hono | API server |
| drizzle.config.ts | Has database layer |
| schema.ts or schema/ | Has database schema |
| pyproject.toml / setup.py | Python project |
| Cargo.toml | Rust project |
Which docs should I generate?
1. ARCHITECTURE.md — system overview, stack, directory structure, key flows
2. API_ENDPOINTS.md — routes, methods, params, response shapes, auth
3. DATABASE_SCHEMA.md — tables, relationships, migrations, indexes
4. All of the above
Only offer docs that match the project. Don't offer API_ENDPOINTS.md for a static site. Don't offer DATABASE_SCHEMA.md if there's no database.
For each requested doc, read the relevant source files:
ARCHITECTURE.md — scan:
package.json / pyproject.toml (stack, dependencies)src/index.ts, src/main.tsx, src/App.tsx)wrangler.jsonc, vite.config.ts, tsconfig.json)API_ENDPOINTS.md — scan:
src/routes/, src/api/, or inline in index)DATABASE_SCHEMA.md — scan:
src/db/schema.ts, src/schema/)drizzle/, migrations/)Write each doc to docs/ (create the directory if it doesn't exist). If the project already has docs there, offer to update rather than overwrite.
For small projects with no docs/ directory, write to the project root instead.
# Architecture
## Overview
[One paragraph: what this project does and how it's structured]
## Stack
| Layer | Technology | Version |
|-------|-----------|---------|
| Runtime | [e.g. Cloudflare Workers] | — |
| Framework | [e.g. Hono] | [version] |
| Database | [e.g. D1 (SQLite)] | — |
| ORM | [e.g. Drizzle] | [version] |
| Frontend | [e.g. React 19] | [version] |
| Styling | [e.g. Tailwind v4] | [version] |
## Directory Structure
[Annotated tree — top 2 levels with purpose comments]
## Key Flows
### [Flow 1: e.g. "User Authentication"]
[Step-by-step: request → middleware → handler → database → response]
### [Flow 2: e.g. "Data Processing Pipeline"]
[Step-by-step through the system]
## Configuration
[Key config files and what they control]
## Deployment
[How to deploy, environment variables needed, build commands]
# API Endpoints
## Base URL
[e.g. `https://api.example.com` or relative `/api`]
## Authentication
[Method: Bearer token, session cookie, API key, none]
[Where tokens come from, how to obtain]
## Endpoints
### [Group: e.g. Users]
#### `GET /api/users`
- **Auth**: Required
- **Params**: `?page=1&limit=20`
- **Response**: `{ users: User[], total: number }`
#### `POST /api/users`
- **Auth**: Required (admin)
- **Body**: `{ name: string, email: string }`
- **Response**: `{ user: User }` (201)
- **Errors**: 400 (validation), 409 (duplicate email)
[Repeat for each endpoint]
## Error Format
[Standard error response shape]
## Rate Limits
[If applicable]
# Database Schema
## Engine
[e.g. Cloudflare D1 (SQLite), PostgreSQL, MySQL]
## Tables
### `users`
| Column | Type | Constraints | Description |
|--------|------|-------------|-------------|
| id | TEXT | PK | UUID |
| email | TEXT | UNIQUE, NOT NULL | User email |
| name | TEXT | NOT NULL | Display name |
| created_at | TEXT | NOT NULL, DEFAULT now | ISO timestamp |
### `posts`
[Same format]
## Relationships
[Foreign keys, join patterns, cascading rules]
## Indexes
[Non-primary indexes and why they exist]
## Migrations
- Generate: `npx drizzle-kit generate`
- Apply local: `npx wrangler d1 migrations apply DB --local`
- Apply remote: `npx wrangler d1 migrations apply DB --remote`
## Seed Data
[Reference to seed script if one exists]
<!-- TODO: document purpose -->If docs already exist:
Never silently overwrite custom content the user has added to their docs.
Unified Python interface to 40+ bioinformatics services. Use when querying multiple databases (UniProt, KEGG, ChEMBL, Reactome) in a single workflow with consistent API. Best for cross-database analysis, ID mapping across services. For quick single-database lookups use gget; for sequence/file manipulation use biopython.
Python library for working with geospatial vector data including shapefiles, GeoJSON, and GeoPackage files. Use when working with geographic data for spatial analysis, geometric operations, coordinate transformations, spatial joins, overlay operations, choropleth mapping, or any task involving reading/writing/analyzing vector geographic data. Supports PostGIS databases, interactive maps, and integration with matplotlib/folium/cartopy. Use for tasks like buffer analysis, spatial joins between datasets, dissolving boundaries, clipping data, calculating areas/distances, reprojecting coordinate systems, creating maps, or converting between spatial file formats.
Fast CLI/Python queries to 20+ bioinformatics databases. Use for quick lookups: gene info, BLAST searches, AlphaFold structures, enrichment analysis. Best for interactive exploration, simple queries. For batch processing or advanced BLAST use biopython; for multi-database Python workflows use bioservices.
Direct REST API access to UniProt. Protein searches, FASTA retrieval, ID mapping, Swiss-Prot/TrEMBL. For Python workflows with multiple databases, prefer bioservices (unified interface to 40+ services). Use this for direct HTTP/REST work or UniProt-specific control.
Direct REST API access to UniProt. Protein searches, FASTA retrieval, ID mapping, Swiss-Prot/TrEMBL. For Python workflows with multiple databases, prefer bioservices (unified interface to 40+ services). Use this for direct HTTP/REST work or UniProt-specific control.
BullMQ expert for Redis-backed job queues, background processing, and reliable async execution in Node.js/TypeScript applications. Use when: bullmq, bull queue, redis queue, background job, job queue.
Create custom external web service APIs for Moodle LMS. Use when implementing web services for course management, user tracking, quiz operations, or custom plugin functionality. Covers parameter validation, database operations, error handling, service registration, and Moodle coding standards.
Python library for working with geospatial vector data including shapefiles, GeoJSON, and GeoPackage files. Use when working with geographic data for spatial analysis, geometric operations, coordinate transformations, spatial joins, overlay operations, choropleth mapping, or any task involving reading/writing/analyzing vector geographic data. Supports PostGIS databases, interactive maps, and integration with matplotlib/folium/cartopy. Use for tasks like buffer analysis, spatial joins between datasets, dissolving boundaries, clipping data, calculating areas/distances, reprojecting coordinate systems, creating maps, or converting between spatial file formats.
Take jezweb/project-docs from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
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.
The instructions reference npx.
Without those the skill loads but fails at the first command.