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alex-voloshin-dev
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project-init

Scan project directories to identify tech stacks and generate AGENTS.md, ARCHITECTURE.md, and TESTING.md files.

2|Updated Mar 19, 2026
Search Tags:#automation#architecture#documentation#onboarding#bootstrapping#project-management
One-click install
npx skills add https://github.com/alex-voloshin-dev/ai-skills --skill project-init-alex-voloshin-dev
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: project-init
Source: https://github.com/alex-voloshin-dev/ai-skills/tree/main/.windsurf/skills/project-init
Command: npx skills add https://github.com/alex-voloshin-dev/ai-skills --skill project-init-alex-voloshin-dev

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill solves the "cold start" problem for AI agents by automatically scanning a codebase to generate the essential documentation and context files required for effective AI-assisted development.

Core Features & Use Cases

  • Automated Context Generation: Scans tech stacks and directory structures to create standardized AGENTS.md, ARCHITECTURE.md, and TESTING.md files.
  • Monorepo Support: Intelligently identifies subprojects and boundaries to generate scoped documentation for complex, multi-service repositories.
  • Use Case: When onboarding an AI agent to a legacy or complex monorepo, use this Skill to instantly map the architecture, define testing protocols, and establish clear behavioral guidelines for the agent.

Quick Start

Run the project-init skill to scan the current directory and generate all necessary AI context files for this project.

Frequently Asked Questions about project-init

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

FAQPage Schema
How do I generate AI context documentation for a new codebase?▼

To generate AI context documentation, run a deep-scan of your project directory to identify tech stacks and architectural boundaries, which automatically produces standardized AGENTS.md, ARCHITECTURE.md, and TESTING.md files for AI agents.

What is the best way to onboard an AI agent to a complex monorepo?▼

Onboarding an AI agent to a complex monorepo requires scoped documentation. A deep-scan identifies subprojects and architectural boundaries to generate scoped context files, mapping dependencies and establishing clear behavioral guidelines for each service.

Can I automatically map architecture and testing protocols for a legacy repository?▼

Yes, you can automatically map architecture and testing protocols by scanning the legacy repository's directory structures and configuration files to generate standardized ARCHITECTURE.md and TESTING.md documents.

Do I need read access to project configuration files to bootstrap AI context?▼

Yes, bootstrapping AI context requires read access to project configuration files and directory structures to accurately map dependencies, identify tech stacks, and define architectural boundaries.

What files are needed to provide AI agents with operational context?▼

AI agents need standardized AGENTS.md, ARCHITECTURE.md, and TESTING.md files to receive the necessary operational context, including architectural boundaries, testing protocols, and behavioral guidelines.

Does automated project bootstrapping work with multi-service repositories?▼

Yes, automated project bootstrapping works with multi-service repositories by intelligently identifying subprojects and architectural boundaries to generate scoped documentation for complex monorepos.

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