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ai-factory

v2.1.0

Published

CLI tool for automating AI agent context setup in projects

Readme

logo

AI Factory

Stop configuring. Start building.

You want to build with AI, but setting up the right context, prompts, and workflows takes time. AI Factory handles all of that so you can focus on what matters — shipping quality code.

One command. Full AI-powered development environment.

ai-factory init

Why AI Factory?

  • Zero configuration — detects your stack, installs relevant skills, configures integrations
  • Best practices built-in — logging, commits, code review, all following industry standards
  • Spec-driven development — AI follows plans, not random exploration. Predictable, resumable, reviewable
  • Community skills — leverage skills.sh ecosystem or generate custom skills
  • Works with your stack — Next.js, Laravel, Django, Express, and more
  • Multi-agent support — Claude Code, Cursor, Windsurf, Roo Code, Kilo Code, Antigravity, OpenCode, Warp, Zencoder, Codex CLI, GitHub Copilot, Gemini CLI, Junie, Qwen Code, or any agent

Installation

Using npm

npm install -g ai-factory

Using mise

mise use -g npm:ai-factory

Quick Start

# In your project directory
ai-factory init

This will:

  • Ask which AI agent you use
  • Detect your project stack
  • Install relevant skills
  • Configure MCP servers (for supported agents)

Then open your AI agent and start working:

/aif

Usage

If the package is installed:

ai-factory init

Or running without installation via npx:

npx ai-factory init

Upgrading from v1 to v2

# 1) Update the CLI package
npm install -g ai-factory@latest

# 2) Migrate existing skills to v2 naming
ai-factory upgrade

ai-factory upgrade removes old bare-named skills (commit, feature, etc.) and installs new aif-* prefixed versions. Custom skills are preserved.

Example Workflow

# Plan a feature — creates branch, analyzes codebase, builds step-by-step plan
/aif-plan Add user authentication with OAuth

# Optionally refine the plan with deeper analysis
/aif-improve

# Execute the plan — implements tasks one by one, commits at checkpoints
/aif-implement

# Fix a bug — AI learns from every fix and gets smarter over time
/aif-fix TypeError: Cannot read property 'name' of undefined

# Set up CI pipeline — GitHub Actions or GitLab CI with linting, SA, tests
/aif-ci github

# Generate project documentation — README + docs/ with topics
/aif-docs

See the full Development Workflow with diagram and decision table.

Auto-Generated Documentation

AI Factory can generate and maintain your project docs with a single command:

/aif-docs          # Creates README + docs/ structure from your codebase
/aif-docs --web    # Also generates a static HTML documentation site
  • Generates docs from scratch — analyzes your codebase and creates a lean README + detailed docs/ pages by topic
  • Cleans up scattered files — finds loose CONTRIBUTING.md, ARCHITECTURE.md, SETUP.md in your root and consolidates them into a structured docs/ directory
  • Keeps docs in sync — integrates with /aif-implement so documentation is updated automatically after each feature
  • Builds a docs website--web generates a static HTML site with navigation and dark mode, ready to host

Documentation

| Guide | Description | |-------|-------------| | Getting Started | What is AI Factory, supported agents, CLI commands | | Development Workflow | Workflow diagram, when to use what, spec-driven approach | | Reflex Loop | Iterative generate → evaluate → critique → refine workflow | | Core Skills | All slash commands — feature, task, fix, implement, evolve, docs, and more | | Plan Files | Plan files, self-improvement patches, skill acquisition | | Security | Two-level security scanning for external skills | | Configuration | .ai-factory.json, MCP servers, project structure, best practices |


happy

Links

License

MIT