onboard

Scan a project's structure and generate a .md file of its AI-context.

Updated Jan 19, 2026

Search Tags:#typescript #documentation #onboarding #codebase #nodejs #scan #ai-context

Ready to run

npx skills add https://github.com/howdycarter/Mothership --skill onboard-howdycarter

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: onboard
Source: https://github.com/howdycarter/Mothership/tree/main/.claude/skills/onboard
Command: npx skills add https://github.com/howdycarter/Mothership --skill onboard-howdycarter

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Scans a project to generate a concise, AI-friendly codebase document that captures stack, structure, conventions, and dependencies for context.

Core Features & Use Cases

Automatically detects project structure (package.json, tsconfig.json, directories) and identifies the tech stack, framework, language, and deployment hints.
Produces a readable .mothership/codebase.md that can be consumed by AI agents to understand codebases and context.
Use Case: Onboard a new AI agent to a repository by generating a ready-to-consume codebase snapshot.

Quick Start

Run onboard with your project path to generate .mothership/codebase.md.

Frequently Asked Questions about onboard

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I generate AI-ready documentation from my codebase?▼

To generate AI-ready documentation, you scan your project structure to produce a codebase.md file. This file captures your stack, conventions, and dependencies into a concise markdown snapshot for AI agents to consume.

What is the best way to onboard an AI agent to a Node.js and TypeScript repository?▼

Onboarding an AI agent involves generating a structured markdown snapshot of your codebase. By scanning package.json and tsconfig.json, you can map routing and component patterns into a readable document for AI context.

Can I use this to document project structure and tech stack conventions automatically?▼

Yes, you can automatically document project structure and conventions. The scanning process detects directories, identifies your framework and language, and extracts deployment hints to output a comprehensive codebase document.

Does the generated codebase documentation work with diverse project layouts?▼

The generated codebase documentation applies to diverse stacks and project layouts. It maps your specific routing and component patterns to produce a structured markdown file that accurately reflects your unique project structure.

How do I create a codebase.md file for AI context consumption?▼

You create a codebase.md file by running a project scan with your designated path. The scan reads your configuration files and outputs the structured markdown document into a .mothership directory for AI consumption.

What limitations exist when scanning a codebase to identify tech stack and dependencies?▼

A limitation of scanning a codebase to identify dependencies is that the generated markdown snapshot is a static representation. It captures the project state at the time of the scan and requires re-running to reflect subsequent codebase changes.