aidocs 0.16.0

AI-powered documentation generator for web applications. Install docs commands into your Claude Code project.

aidocs

AI-powered documentation generator for web applications.

▶️ Watch the demo on YouTube

How It Works

aidocs generates comprehensive documentation by combining three sources of truth:

1. Vision Analysis - Playwright captures screenshots, Claude analyzes what users actually see
2. Codebase Analysis - Scans your frontend components, backend routes, validation rules, and models
3. Interactive Exploration - Clicks buttons, fills forms, discovers conditional UI and validation messages

This produces documentation that's accurate to both the code AND the actual user experience.

┌─────────────────┐     ┌──────────────────┐     ┌─────────────────┐
│  📸 Screenshots │  +  │  📄 Code Analysis │  +  │  🖱️ UI Testing   │
│  (what users    │     │  (validation,     │     │  (conditional   │
│   see)          │     │   routes, models) │     │   fields, flows)│
└────────┬────────┘     └────────┬─────────┘     └────────┬────────┘
         │                       │                        │
         └───────────────────────┼────────────────────────┘
                                 ▼
                    ┌────────────────────────┐
                    │  📚 Smart Documentation │
                    │  that stays in sync    │
                    └────────────────────────┘

Quick Start

# 1. Install the CLI
brew install binarcode/aidocs/aidocs

# 2. Add to your project
cd your-project
aidocs init .

# 3. Generate docs (in Claude Code)
/docs:generate https://myapp.com/dashboard

Alternative installation:

# Homebrew (macOS/Linux)
brew install binarcode/aidocs/aidocs

# uv (recommended for Python users)
uv tool install aidocs

# pipx
pipx install aidocs

# From GitHub (latest)
uv tool install aidocs --from git+https://github.com/binarcode/aidocs-cli.git

Updating:

brew upgrade aidocs            # Homebrew
aidocs update                  # PyPI (uv/pipx/pip)
aidocs update --github         # GitHub (latest)
aidocs init . --force          # Reinstall commands in project

Usage Flow

┌──────────────────────────────────────────────────────────────────────────────┐
│                              SETUP (once)                                    │
├──────────────────────────────────────────────────────────────────────────────┤
│                                                                              │
│  $ aidocs init .                    Install commands into project            │
│           │                                                                  │
│           ▼                                                                  │
│  /docs:init                         Configure: name, auth, style, output     │
│                                                                              │
└──────────────────────────────────────────────────────────────────────────────┘
                                      │
                                      ▼
┌──────────────────────────────────────────────────────────────────────────────┐
│                    OPTION A: Document a Single Page                          │
├──────────────────────────────────────────────────────────────────────────────┤
│                                                                              │
│  /docs:generate https://myapp.com/users    ← Give it any URL!                │
│           │                                                                  │
│           ├──→ Takes screenshots with Playwright                             │
│           ├──→ Analyzes codebase for that route                              │
│           ├──→ Documents UI elements and interactions                        │
│           └──→ Creates docs/users/index.md                                   │
│                                                                              │
└──────────────────────────────────────────────────────────────────────────────┘
                                      │
                                      ▼
┌──────────────────────────────────────────────────────────────────────────────┐
│                    OPTION B: Document a Code Flow                            │
├──────────────────────────────────────────────────────────────────────────────┤
│                                                                              │
│  /docs:flow "sync users from discord"    ← Describe the flow in words!       │
│           │                                                                  │
│           ├──→ Searches codebase for relevant files                          │
│           ├──→ Traces execution path and builds call graph                   │
│           ├──→ Generates mermaid sequence diagram                            │
│           ├──→ Captures UI screenshots (if Playwright + route detected)      │
│           └──→ Creates docs/flows/sync-users-from-discord.md                 │
│                                                                              │
└──────────────────────────────────────────────────────────────────────────────┘
                                      │
                                      ▼
┌──────────────────────────────────────────────────────────────────────────────┐
│                    OPTION C: Document Entire Project                         │
├──────────────────────────────────────────────────────────────────────────────┤
│                                                                              │
│  /docs:discover                     Scan codebase, find all modules          │
│           │                                                                  │
│           ▼                                                                  │
│  /docs:plan                         Create ordered documentation plan        │
│           │                         → Outputs docs/plan.yml                 │
│           ▼                                                                  │
│  /docs:execute                      Run through plan, generate all docs      │
│                                     → Resume with --continue if interrupted  │
│                                                                              │
└──────────────────────────────────────────────────────────────────────────────┘
                                      │
                                      ▼
┌──────────────────────────────────────────────────────────────────────────────┐
│                         KEEP DOCS IN SYNC                                    │
├──────────────────────────────────────────────────────────────────────────────┤
│                                                                              │
│  # After implementing a feature:                                             │
│  /docs:update --base main           Detect changes, update affected docs     │
│                                                                              │
└──────────────────────────────────────────────────────────────────────────────┘
                                      │
                                      ▼
┌──────────────────────────────────────────────────────────────────────────────┐
│                      ENABLE SEMANTIC SEARCH (optional)                       │
├──────────────────────────────────────────────────────────────────────────────┤
│                                                                              │
│  # After docs are generated, setup RAG for AI-powered search:                │
│  /docs:rag                          ← One command does it all!               │
│           │                                                                  │
│           ├──→ Chunks your docs into searchable pieces                       │
│           ├──→ Creates database migration (pgvector)                         │
│           ├──→ Generates OpenAI embeddings                                   │
│           └──→ Outputs sync.sql ready to import                              │
│                                                                              │
└──────────────────────────────────────────────────────────────────────────────┘

Quick Commands

# Simple: Generate docs for one page
/docs:generate https://myapp.com/dashboard

# Flow: Document a feature (user-focused by default)
/docs:flow "how to create employees"
/docs:flow "import payments" --technical    # Developer docs

# Batch: Document entire project
/docs:discover && /docs:plan && /docs:execute

# Maintain: Update after code changes
/docs:update --base main

# RAG: Setup semantic search for your docs
/docs:rag

CLI Commands

aidocs init [PROJECT_NAME]

Initialize the docs module in a project.

aidocs init .                  # Current directory
aidocs init my-project         # New directory
aidocs init . --force          # Overwrite existing
aidocs init . --ai cursor      # Use with Cursor

Options:

Option	Description
--ai	AI assistant: claude, cursor, copilot (default: claude)
--force, -f	Overwrite existing files
--no-git	Skip git initialization

aidocs check

Check for required tools and dependencies.

aidocs check

aidocs version

Show version information.

aidocs update

Update aidocs to the latest version.

aidocs update              # Update from PyPI
aidocs update --github     # Update from GitHub (latest)

Options:

Option	Description
--github	Install latest from GitHub instead of PyPI

Automatically detects and uses the appropriate package manager (uv, pipx, or pip).

aidocs rag

Prepare documentation for RAG: chunk files and generate embeddings in one command.

aidocs rag                      # Chunk and generate embeddings
aidocs rag docs/users           # Specific directory
aidocs rag --dry                # Preview only
aidocs rag --force              # Re-process everything
aidocs rag --skip-vectors       # Only chunk, no embeddings

Options:

Option	Description
--force, -f	Re-chunk and re-sync all files
--dry	Preview without making changes
--table, -t	Target table name (default: doc_embeddings)
--skip-vectors	Only chunk files, skip embedding generation

What it does:

1. Chunks markdown files at ## headings (creates .chunks.json files)
2. Generates embeddings via OpenAI API (requires OPENAI_API_KEY)
3. Creates docs/.chunks/sync.sql for database import

Workflow:

# Prepare docs for MCP server
aidocs rag docs/

# Start MCP server
aidocs mcp docs/

Note: If OPENAI_API_KEY is not set, chunking completes but embeddings are skipped. The MCP server works with just chunks (keyword search).

Environment: Reads OPENAI_API_KEY from .env file in current directory or global environment.

aidocs rag-chunks

Chunk markdown files for vector database import.

aidocs rag-chunks                   # Chunk all files in docs/
aidocs rag-chunks docs/users        # Chunk specific directory
aidocs rag-chunks --force           # Re-chunk all files
aidocs rag-chunks --dry             # Preview only

Options:

Option	Description
--force, -f	Re-chunk all files (ignore cache)
--dry	Preview without writing files

What it does:

1. Scans directory for .md files
2. Splits at ## headings into chunks
3. Creates .chunks.json files alongside each .md
4. Maintains docs/.chunks/manifest.json for change tracking

Output structure:

docs/
├── users/
│   ├── lifecycle.md
│   └── lifecycle.chunks.json    # Chunks for this file
├── campaigns/
│   ├── lifecycle.md
│   └── lifecycle.chunks.json
└── .chunks/
    └── manifest.json            # Tracking file

Next step: Run aidocs rag-vectors to generate embeddings

aidocs export-pdf

Export markdown documentation to PDF with auto-generated table of contents.

aidocs export-pdf docs/projects/index.md                    # Export to docs/exports/
aidocs export-pdf docs/flows/sync-users.md -o manual.pdf    # Custom output path

Options:

Option	Description
--output, -o	Output PDF path (default: docs/exports/{name}.pdf)

What it does:

1. Reads the markdown file
2. Extracts H1/H2 headings for table of contents
3. Converts markdown to styled HTML
4. Uses Chrome/Chromium headless to render PDF
5. Saves with proper page breaks and formatting

Output:

╭──────────── Success ────────────╮
│ PDF exported successfully!      │
│                                 │
│ Title: Projects Overview        │
│ TOC entries: 8                  │
│ Size: 245.3 KB                  │
│                                 │
│ Output: docs/exports/index.pdf  │
╰─────────────────────────────────╯

Requirements:

• Chrome or Chromium installed (uses headless mode)

aidocs rag-vectors

Generate embeddings and SQL for vector database import.

aidocs rag-vectors                  # Generate embeddings and SQL
aidocs rag-vectors --dry            # Preview what would be synced
aidocs rag-vectors --force          # Re-sync all files
aidocs rag-vectors --table my_docs  # Custom table name

Options:

Option	Description
--force, -f	Re-sync all files (ignore last sync)
--dry	Preview without generating embeddings
--table, -t	Target table name (default: doc_embeddings)

Requires: OPENAI_API_KEY (from .env file or environment variable)

What it does:

1. Reads chunk files from docs/.chunks/
2. Calls OpenAI API to generate embeddings (text-embedding-3-small)
3. Creates docs/.chunks/sync.sql with INSERT statements
4. Tracks sync state to avoid re-processing unchanged files

Output: docs/.chunks/sync.sql

BEGIN;
INSERT INTO doc_embeddings (file_path, content, chunk_index, title, metadata, embedding)
VALUES ('docs/users/lifecycle.md', '...', 0, 'Overview', '{...}'::jsonb, '[0.001, ...]'::vector);
-- ... more inserts
COMMIT;

Import to database:

psql $DATABASE_URL -f docs/.chunks/sync.sql

aidocs serve

Serve documentation with live reload using MkDocs Material theme.

aidocs serve                    # Serve docs/ on port 8000
aidocs serve --port 3000        # Custom port
aidocs serve docs/users         # Serve specific subdirectory
aidocs serve --build            # Build static site only
aidocs serve --build -o ./site  # Build to custom output
aidocs serve --no-open          # Don't auto-open browser

Options:

Option	Description
--port, -p	Port to serve on (default: 8000)
--host	Host to bind to (default: 127.0.0.1)
--open/--no-open	Open browser automatically (default: --open)
--build, -b	Build static site only, no server
--output, -o	Output directory for built site

Features:

• Auto-generates navigation from folder structure
• Material Design theme with light/dark mode
• Live reload when files change
• Full-text search
• Code syntax highlighting

aidocs mcp

Start a local MCP server to expose documentation via tools. Allows Claude Code and other MCP clients to search and read your docs.

aidocs mcp                      # Serve docs/ directory
aidocs mcp docs/users           # Serve specific subdirectory

MCP Tools exposed:

Tool	Description
list_docs	List all documentation files with chunk counts
search_docs	Search through documentation by keyword
read_doc	Read full content of a file or specific chunk
get_doc_structure	Get heading hierarchy for navigation

Configuration (.mcp.json):

{
  "mcpServers": {
    "aidocs": {
      "command": "aidocs",
      "args": ["mcp", "docs/"]
    }
  }
}

Features:

• Works without pre-chunking (chunks markdown on-the-fly if needed)
• Uses existing .chunks.json files if available (faster)
• Keyword search with weighted scoring (title matches weighted 3x)
• Returns content previews and hierarchy context

Example search result:

{
  "file_path": "users/lifecycle.md",
  "chunk_index": 2,
  "title": "Creating Users",
  "hierarchy": ["Users", "Creating Users"],
  "content_preview": "To create a new user, navigate to...",
  "score": 12
}

Usage Examples in Claude Code:

Once configured, Claude Code can use these tools automatically. You can prompt:

# Search documentation
"Search our docs for authentication setup"
"Find documentation about API rate limits"

# Read specific docs
"Read the user lifecycle documentation"
"Show me the API reference section"

# Explore structure
"What documentation do we have?"
"List all docs about payments"

Best Practices:

1. Prepare docs first - Run aidocs rag docs/ before starting MCP server for faster searches
2. Use descriptive headings - The MCP chunks at ## headings, clear titles improve search
3. Keep docs updated - Re-run aidocs rag --force after major doc changes
4. Project-level config - Add .mcp.json to your repo so the team shares the same setup
5. Combine with code context - Ask Claude to "check our docs for X" while reviewing code

Troubleshooting:

Issue	Solution
MCP not connecting	Restart Claude Code or run /mcp to reload servers
Empty search results	Ensure docs directory has .md files
Slow searches	Run aidocs rag to pre-chunk files

Slash Commands

After running aidocs init, these commands are available in Claude Code:

Command	Description	Requires Playwright
/docs:init	Configure project settings, credentials, output style	No
/docs:generate <url>	Generate docs for a single page with screenshots	Yes
/docs:analyze <route>	Analyze codebase for a route (no browser)	No
/docs:batch	Generate docs for multiple pages	Yes
/docs:update	Update docs based on git diff	Optional
/docs:discover	Scan codebase, discover all modules	No
/docs:plan	Create ordered documentation plan	No
/docs:execute	Execute plan, generate all docs	Yes
/docs:explore <module>	Interactive UI exploration with Playwright	Yes
/docs:flow "<description>"	Document a feature with screenshots (use --technical for dev docs)	Optional
/docs:rag-vectors	Generate embeddings and SQL for vector DB import	No
/docs:rag-init	Generate database migration for vector embeddings	No
/docs:rag	Setup RAG: chunks → migration → embeddings (all-in-one)	No
/docs:export-pdf	Export markdown documentation to PDF with TOC	Yes (Playwright)

/docs:init

Interactive setup wizard that:

• Detects your tech stack (Laravel, Vue, React, Next.js, etc.)
• Asks for project name, audience, and documentation tone
• Configures authentication method (file, env vars, or manual)
• Sets output directory and screenshot preferences

/docs:generate <url>

Generate documentation for a single page:

/docs:generate https://myapp.com/campaigns
/docs:generate /campaigns                      # Uses base URL from config
/docs:generate /settings --auth user:pass      # With authentication

Features:

• Captures full-page screenshots
• Analyzes UI elements visually
• Searches codebase for related code
• Detects forms, buttons, and interactive elements
• Offers to document user flows step-by-step

/docs:update

Update existing documentation based on code changes:

/docs:update                    # Compare against main
/docs:update --base staging     # Compare against staging branch
/docs:update --dry-run          # Preview changes without applying
/docs:update --screenshots      # Also refresh screenshots

What it does:

1. Gets git diff between current branch and base
2. Analyzes changed frontend/backend files
3. Maps code changes to affected features
4. Finds and updates related documentation
5. Optionally refreshes screenshots
6. Offers to stage/commit doc changes

Perfect for: Running before creating a PR to ensure docs stay in sync with code.

/docs:analyze <route>

Analyze codebase without browser automation:

/docs:analyze /campaigns
/docs:analyze /api/users

/docs:batch

Generate documentation for multiple pages:

/docs:batch urls.txt                           # From file
/docs:batch --discover --base-url https://myapp.com  # Auto-discover routes

/docs:discover

Scan your codebase to discover all modules and their structure:

/docs:discover                     # Discover all modules
/docs:discover --dry               # Preview without saving
/docs:discover campaigns           # Analyze only one module

What it analyzes:

• Backend: Models, controllers, routes, validation rules
• Frontend: Pages, components, forms, state management
• Relationships: Foreign keys, ORM relationships, cross-module navigation

Creates docs/.knowledge/ with:

docs/.knowledge/
├── _meta/
│   ├── project.json              # Project-level info
│   └── modules-index.json        # List of discovered modules
├── modules/
│   ├── campaigns/
│   │   ├── entity.json           # Fields, types, relationships
│   │   ├── routes.json           # API endpoints
│   │   ├── components.json       # UI components
│   │   └── validation.json       # Validation rules
│   └── users/
│       └── ...
└── relationships/                # Cross-module relationships

Next step: Run /docs:plan to create documentation plan

/docs:plan

Create an ordered documentation plan based on discovered modules:

/docs:plan                         # Create plan interactively
/docs:plan --auto                  # Auto-generate plan (no prompts)
/docs:plan --show                  # Show existing plan

What it does:

1. Reads discovered modules from docs/.knowledge/
2. Analyzes dependencies and relationships
3. Suggests documentation order (core modules first)
4. Creates docs/plan.yml with the plan

Output: docs/plan.yml

modules:
  - name: users
    priority: 1
    reason: "Core module - other modules depend on it"
    document:
      lifecycle: true
      include_errors: true
    status: pending

  - name: campaigns
    priority: 2
    document:
      lifecycle: true
      flows:
        - "duplicate campaign"
    status: pending

cross_module_flows:
  - name: "user registration to first campaign"
    modules: [users, campaigns]
    status: pending

Next step: Run /docs:execute to generate documentation

/docs:execute

Execute the documentation plan and generate all docs:

/docs:execute                      # Execute full plan
/docs:execute --module campaigns   # Execute only one module
/docs:execute --continue           # Continue from where it stopped
/docs:execute --dry                # Preview what would be generated

What it does:

1. Reads docs/plan.yml
2. For each module in order:
   • Runs explore (if needed)
   • Generates lifecycle documentation
   • Captures screenshots
   • Writes to docs/{module}/
3. Updates plan status as it progresses
4. Generates cross-module flows last

Output structure:

docs/
├── index.md                    # Auto-generated with links
├── users/
│   ├── index.md               # Module overview
│   ├── lifecycle.md           # CRUD documentation
│   ├── user-registration-to-campaign.md  # Cross-module flow (first module)
│   └── images/
└── campaigns/
    ├── index.md
    ├── lifecycle.md
    ├── duplicate-campaign.md  # Custom flow
    └── images/

Resume support: If execution stops, run /docs:execute --continue to resume

/docs:explore <module>

Interactively explore a module's UI with Playwright:

/docs:explore campaigns                    # Explore all campaign pages
/docs:explore users --page /users/create   # Specific page
/docs:explore orders --depth deep          # Thorough exploration

What it discovers:

• Conditional fields (checkbox reveals more inputs)
• Validation messages (tries invalid data)
• UI state changes (what happens when you click)
• Cross-page effects (create here → appears there)

/docs:flow "<description>"

Document a feature with screenshots and step-by-step instructions. By default, creates user-focused documentation. Use --technical for developer documentation.

/docs:flow "how to create employees"              # User guide with screenshots
/docs:flow "import payments from csv"             # User guide with screenshots
/docs:flow "payment processing" --technical       # Developer docs with code
/docs:flow "stripe webhooks" --technical          # Developer docs with code
/docs:flow "user registration" --no-screenshots   # Skip screenshots

Arguments:

• --technical - Generate developer-focused documentation with code snippets
• --no-screenshots - Skip UI screenshot capture

Output modes:

Mode	Audience	Output
Default	End users	Screenshots, plain English, step-by-step guide
--technical	Developers	Code snippets, file paths, mermaid diagrams

Output: docs/flows/{kebab-case-title}.md

Example: User-focused (default)

# How to Import Payments

Import payment records from a CSV file.

## Before You Start
- Prepare a CSV with columns: date, amount, description
- Maximum 10,000 rows per import

## Steps

### Step 1: Go to Payroll
Navigate to **Payroll** from the sidebar.

![Payroll Page](./images/payroll-page.png)

### Step 2: Click Import
Click the **Import Payments** button.

![Import Button](./images/import-button.png)

### Step 3: Upload Your File
Select your CSV file and click **Start Import**.

## What Happens Next
- Import runs in background
- You'll receive an email when complete

Example: Technical (--technical)

# Import Payments Flow

## Architecture
sequenceDiagram: User → Controller → Job → Database

## Entry Points
| Trigger | Route |
|---------|-------|
| UI | POST /payroll/import |
| CLI | php artisan payments:import |

## Execution Flow

**File:** `app/Http/Controllers/PayrollController.php:45`
public function import(Request $request) { ... }

**File:** `app/Jobs/ImportPaymentsJob.php:28`
public function handle() { ... }

Screenshots require:

• Playwright MCP installed
• urls.base configured in docs/config.yml

/docs:rag-vectors

Generate embeddings and SQL for syncing documentation to a PostgreSQL vector database.

/docs:rag-vectors                    # Generate sync SQL (smart)
/docs:rag-vectors --dry              # Preview what would be synced
/docs:rag-vectors --force            # Re-sync all files

Prerequisites:

• Run aidocs rag-chunks first to create chunk files
• Set OPENAI_API_KEY environment variable

What it does:

1. Reads chunk files from docs/.chunks/manifest.json
2. Compares against last sync to find changes
3. Generates embeddings via OpenAI API (only for new/changed chunks)
4. Creates docs/.chunks/sync.sql with INSERT statements

Smart sync:

• Unchanged files → Skip (no API calls)
• Changed files → Re-generate embeddings
• New files → Generate embeddings
• Deleted files → Add DELETE statements

Output:

📊 Sync Summary:
   Unchanged: 12 files (skipped)
   Changed: 2 files (8 chunks)
   New: 1 file (3 chunks)

📄 Generated: docs/.chunks/sync.sql

Run with:
   psql $DATABASE_URL -f docs/.chunks/sync.sql

/docs:rag-init

Generate a database migration for storing documentation embeddings with pgvector.

/docs:rag-init                     # Default: 1536 dimensions
/docs:rag-init --dimensions 3072   # For text-embedding-3-large
/docs:rag-init --table my_docs     # Custom table name

What it does:

1. Detects your framework (Laravel, Prisma, TypeORM, Drizzle, Django)
2. Generates the appropriate migration file
3. Creates table with pgvector support for similarity search

Supported Frameworks:

Framework	Detection	Output
Laravel	composer.json	PHP migration with $table->vector()
Prisma	schema.prisma	Prisma schema addition
TypeORM	package.json	TypeScript migration class
Drizzle	drizzle-orm	Schema + SQL migration
Django	manage.py	Django migration with pgvector
Fallback	None detected	Raw PostgreSQL SQL

Table Structure:

doc_embeddings
├── id             UUID PRIMARY KEY
├── file_path      VARCHAR(500)      # Path to .md file
├── content        TEXT              # Document content
├── chunk_index    INTEGER           # For large docs split into chunks
├── title          VARCHAR(255)      # Document title
├── metadata       JSONB             # Tags, module, category, etc.
├── embedding      VECTOR(1536)      # OpenAI embedding
├── created_at     TIMESTAMP
└── updated_at     TIMESTAMP

Indexes:

• file_path - B-tree index for path lookups
• embedding - HNSW index for fast vector similarity search

Requirements:

• PostgreSQL with pgvector extension

Example workflow:

# 1. Generate migration
/docs:rag-init

# 2. Run migration
php artisan migrate          # Laravel
npx prisma migrate dev       # Prisma
python manage.py migrate     # Django

# 3. Chunk your docs
aidocs rag-chunks

# 4. Generate embeddings and sync
aidocs rag-vectors

/docs:rag

The easy way - Setup RAG (Retrieval Augmented Generation) for your documentation in one command:

/docs:rag                     # Full setup
/docs:rag --skip-migration    # Skip migration (table already exists)
/docs:rag --force             # Re-chunk and re-sync everything
/docs:rag --dry               # Preview what would happen

What it does automatically:

1. Checks/creates documentation chunks (aidocs rag-chunks)
2. Generates database migration (/docs:rag-init)
3. Prompts you to run the migration
4. Generates embeddings and SQL (aidocs rag-vectors)

Output:

✅ RAG Setup Complete!

📊 Summary:
   Documentation files: 8
   Chunks created: 24
   Embeddings generated: 24

📄 Files created:
   ✓ docs/.chunks/manifest.json
   ✓ database/migrations/..._create_doc_embeddings_table.php
   ✓ docs/.chunks/sync.sql

🚀 Final step:
   psql $DATABASE_URL -f docs/.chunks/sync.sql

Requirements:

• PostgreSQL with pgvector extension
• OPENAI_API_KEY environment variable

/docs:export-pdf

Export markdown documentation to PDF with auto-generated table of contents using Playwright MCP.

/docs:export-pdf docs/pages/dashboard.md                    # Export single file
/docs:export-pdf docs/flows/sync-users.md --output manual.pdf  # Custom filename

What it does:

1. Reads the markdown file
2. Extracts H1/H2 headings to build a clickable table of contents
3. Converts markdown to styled HTML (code blocks, tables, images)
4. Uses Playwright MCP to render and export as PDF
5. Saves to docs/exports/ directory

Output: docs/exports/{filename}.pdf

Features:

• Auto-generated TOC from H1/H2 headings with clickable links
• PDF-friendly styling (page breaks at H1, code block formatting)
• Embedded images (converted to base64)
• A4 format with proper margins

Example:

📄 Exporting: docs/pages/dashboard.md

📑 Table of Contents:
   • Dashboard Overview
     • Key Metrics
     • Navigation
   • Components
   • Configuration

🖨️ Rendering PDF...
   Format: A4
   Pages: 5

✅ PDF exported!
   📁 docs/exports/dashboard.pdf (245 KB)

Requirements:

• Playwright MCP must be available

Knowledge Base

The intelligent commands build a docs/.knowledge/ folder:

docs/.knowledge/
├── _meta/                    # Project info
├── modules/
│   ├── campaigns/
│   │   ├── entity.json       # Entity definition
│   │   ├── routes.json       # API routes
│   │   ├── validation.json   # Validation rules
│   │   ├── flows/            # User flows
│   │   └── ui-states/        # Conditional UI
│   └── users/
│       └── ...
├── relationships/            # Cross-module relationships
└── cross-module-flows/       # Flows spanning modules

This knowledge powers smarter documentation generation.

Intelligent Workflow

For Single Flow (Quick)

/docs:flow "sync users from discord"    → Analyzes code, generates docs with diagrams
/docs:flow "import payments from csv"   → Includes UI screenshots if route detected

For Entire Project (Batch)

/docs:discover               → Scans codebase, finds all modules
         ↓
/docs:plan                   → Creates ordered documentation plan
         ↓
/docs:execute                → Generates all docs with screenshots

Example Session

# Option A: Document a specific flow
/docs:flow "sync users from discord"       # Backend integration
/docs:flow "import payments from csv"      # Import with UI screenshots
/docs:flow "how stripe webhooks work"      # Webhook handling

# Option B: Document entire project
/docs:discover                             # Find all modules
/docs:plan                                 # Create plan (docs/plan.yml)
/docs:execute                              # Generate all documentation

# Resume if interrupted
/docs:execute --continue

# After code changes
/docs:update --base main

What Makes It Smart

Capability	How It Works
Conditional UI	Clicks checkboxes/toggles, observes what fields appear
Validation Discovery	Submits empty/invalid forms, captures error messages
Cross-Page Tracking	Creates data, verifies it appears in lists/dashboards
Entity Lifecycle	Documents full create → view → edit → delete flow
Modular Analysis	One module at a time, scales to large projects
Code + UI Correlation	Matches frontend components to backend validation

Configuration

After running /docs:init, a docs/config.yml is created:

project:
  name: "My App"
  type: saas

style:
  tone: friendly  # friendly | professional | technical | minimal

urls:
  base: "https://myapp.com"

auth:
  method: file    # file | env | manual

output:
  directory: ./docs

Authentication Methods

Method	Description
file	Credentials stored in docs/.auth (gitignored)
env	Read from DOCS_AUTH_USER and DOCS_AUTH_PASS
manual	Pass --auth user:pass each time

Output

Generated documentation includes:

• Overview - What the page is for
• Features - What users can do
• Key Actions - Buttons and actions explained
• Screenshots - Full-page captures
• How-to Guides - Step-by-step flows (optional)
• Related Pages - Navigation links

Requirements

• Python 3.11+
• Claude Code (or Cursor/Copilot)
• Playwright MCP (for browser-based commands)

Installing Playwright MCP

Add to your ~/.claude.json or project .mcp.json:

{
  "mcpServers": {
    "playwright": {
      "command": "npx",
      "args": ["@anthropic/mcp-playwright"]
    }
  }
}

Development

git clone https://github.com/binarcode/aidocs-cli.git
cd aidocs-cli
uv venv && uv pip install -e .
aidocs check

License

MIT