Skip to main content

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

Project description

aidocs

AI-powered documentation generator for web applications.

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    │
                    └────────────────────────┘

Installation

# Install from PyPI
uv tool install aidocs

# Or install from GitHub
uv tool install aidocs --from git+https://github.com/binarcode/aidocs-cli.git

# Or use pipx
pipx install aidocs

Updating

When a new version is released, update the CLI and reinstall commands in your project:

# 1. Update the CLI
aidocs update

# 2. Reinstall commands in your project (adds new slash commands)
cd your-project
aidocs init . --force

The --force flag overwrites existing command files, adding any new commands from the latest version.

Tip: Run aidocs update --github to get the latest unreleased features from GitHub.

Quick Start

# Install the CLI
uv tool install aidocs

# Add to your project
aidocs init .

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-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 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

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:

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

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

aidocs-0.12.1.tar.gz (83.2 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

aidocs-0.12.1-py3-none-any.whl (96.2 kB view details)

Uploaded Python 3

File details

Details for the file aidocs-0.12.1.tar.gz.

File metadata

  • Download URL: aidocs-0.12.1.tar.gz
  • Upload date:
  • Size: 83.2 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for aidocs-0.12.1.tar.gz
Algorithm Hash digest
SHA256 2a104cb7838c762e1bff5feb0419d53151391784ff1b4d0d04c032f9d28d73b1
MD5 d1d8574179ac1dd980df4f3f19f89ab8
BLAKE2b-256 20ee8f4b3ac24c3e526c7e565730f76398e8b688971c40fcd1c1a005fb8aba11

See more details on using hashes here.

Provenance

The following attestation bundles were made for aidocs-0.12.1.tar.gz:

Publisher: publish.yml on BinarCode/aidocs-cli

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file aidocs-0.12.1-py3-none-any.whl.

File metadata

  • Download URL: aidocs-0.12.1-py3-none-any.whl
  • Upload date:
  • Size: 96.2 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for aidocs-0.12.1-py3-none-any.whl
Algorithm Hash digest
SHA256 ad8efd2472c203f6e21508499b024e6ce9396318f822e9f2f6a83ca695e843d0
MD5 ad62ad82defd67e0a3832a0b62201ef4
BLAKE2b-256 a69f1ac93e5e5873f4de525ef52811d5283257f9728c8bcb45f2b03d1ac43a1b

See more details on using hashes here.

Provenance

The following attestation bundles were made for aidocs-0.12.1-py3-none-any.whl:

Publisher: publish.yml on BinarCode/aidocs-cli

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page