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Informations about the package ai-project-scanner

AI Project Scanner

Generate AI-ready documentation and project maps for software projects.

AI Project Scanner helps developers and AI assistants understand existing codebases before making changes.

Instead of asking an AI assistant to explore an unfamiliar project from scratch, AI Project Scanner generates structured project knowledge that can be consumed in minutes.

🚧 Current Status

AI Project Scanner is actively under development.

Current Stable Release

v0.3.5

Current Release

Spring Boot Route Intelligence

Spring Boot framework detection and REST API route extraction are now supported, including controller prefixes, route handlers, HTTP methods, multiple paths, and route metadata.

✨ Features

🧠 Project Vision

AI Project Scanner is evolving beyond documentation generation.

The long-term goal is to build a:

Software Knowledge Engine

that helps both developers and AI assistants understand software projects quickly.

The planned knowledge pipeline is:

Each release should make the scanner understand software a little better.

🔍 Framework Detection

AI Project Scanner can detect multiple frameworks and technologies within the same project.

Current framework support includes:

The scanner is designed to work with projects containing multiple frameworks or technologies rather than assuming that a project has only one framework.

🛣️ API Route Extraction

AI Project Scanner currently supports API route extraction for:

Route information is normalized into a framework-independent representation so that generated documentation can describe routes consistently across different ecosystems.

Spring Boot

Spring Boot route extraction supports common Spring MVC controller annotations:

The scanner can detect:

Spring Boot route extraction currently uses source-based analysis rather than a complete Java AST parser. Advanced Java and Spring annotation resolution may be added in future releases.

📊 Route Intelligence

AI Project Scanner generates route documentation including:

Route information is also included in:

Route intelligence includes:

📦 Installation

Composer

Install the package:

Run:

PHAR

Download the latest PHAR from GitHub Releases.

Run:

🚀 Usage

Scan the Current Project

Scan Another Project

Scan a Laravel Project

Scan an Express Project

Scan a Spring Boot Project

📁 Generated AI Documentation

The scanner generates an ai/ directory containing structured project knowledge:

🤖 Which File Should AI Read First?

Start with:

Then use:

PROJECT_CONTEXT.md provides the initial project understanding and points AI assistants toward the most relevant project information.

📚 Generated Files

PROJECT_CONTEXT.md

Provides high-level AI onboarding information.

Includes:

PROJECT_STRUCTURE.md

Provides a categorized view of the project structure.

Includes categories such as:

API_ROUTES.md

Provides framework-independent API route documentation.

Example:

Method URI Handler
GET /api/users index
GET /api/users/{id} details
POST /api/users save

ROUTE_GRAPH.md

Provides a readable routing overview grouped by controller or router.

PROJECT_TREE.md

Provides a hierarchical view of the scanned project.

PROJECT_MAP.json

Provides machine-readable project metadata including:

SCAN_REPORT.md

Provides project analysis statistics including:

FRAMEWORKS.md

Provides detected framework and technology information.

🚫 Ignore Files

AI Project Scanner respects:

Default ignored locations include:

Ignored directories are pruned during scanning so unnecessary files are not traversed.

💡 Why AI Project Scanner Exists

AI assistants are powerful, but an unfamiliar codebase still requires exploration.

Before making a change, an AI assistant often needs to discover:

AI Project Scanner creates structured project knowledge so AI assistants can understand a codebase faster and make safer suggestions.

🗺️ Roadmap

Completed

v0.1.x

🔭 Next: Component Intelligence

The next knowledge layer is Component Intelligence.

The goal is to allow AI Project Scanner to recognize application components rather than only project files and routes.

Initial component intelligence will focus on:

The component model should remain framework-independent while allowing individual frameworks to provide their own extraction strategies.

🌱 Future

Future knowledge layers may include:

🧭 Architecture Philosophy

AI Project Scanner follows a simple architectural principle:

Scan once. Understand progressively. Generate reusable knowledge.

The filesystem scanner discovers the project.

Detectors interpret the discovered files.

Framework-specific extractors provide specialized intelligence.

Framework-independent DTOs carry structured knowledge.

Generators transform that knowledge into documentation.

This keeps the scanner extensible without coupling the filesystem layer to framework-specific behavior.

🧪 Development

Install dependencies:

Run the complete test suite:

Or:

The project currently uses PHPUnit for regression testing.

🤝 Contributing

Contributions are welcome.

Before contributing, please review:

Recommended workflow:

Make focused changes, add tests where appropriate, and submit a Pull Request.

🔐 Security

Please do not publicly disclose security vulnerabilities through GitHub Issues.

See:

for responsible disclosure information.

📄 License

AI Project Scanner is released under the MIT License.

See:

📦 Package

Composer package:

Install:

🚀 Project Philosophy

AI Project Scanner is being built for developers who want AI to understand their software before changing it.

The goal isn't simply to generate more documentation.

The goal is to progressively transform a software project into structured knowledge that both humans and AI assistants can understand.

Built one knowledge layer at a time. 🚀

All versions of ai-project-scanner with dependencies

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