This project provides a universal context engineering solution and a structured development workflow (PREVC) for AI agents, aiming to simplify context management and improve AI-generated code quality. It targets developers seeking to move beyond "autopilot" AI coding by enabling spec-driven development, human checkpoints, and consistent results across various AI tools.

How It Works

The core innovation is the .context/ directory, a unified structure for documentation, agent playbooks, work plans, and skills, designed to be compatible across multiple AI coding environments. This centralizes context, eliminating fragmentation. Development is guided by the PREVC (Planning, Review, Execution, Validation, Confirmation) workflow, a 5-phase process ensuring specifications precede code, context is maintained, and human oversight is integrated at critical junctures. The project also features an MCP (Model Context Protocol) server, acting as a gateway that equips AI assistants with standardized tools for code exploration, planning, and agent orchestration, facilitating seamless interaction with the codebase.

Quick Start & Requirements

• Primary install/run command: npx @ai-coders/context for CLI usage, or npx @ai-coders/context mcp:install for MCP server setup.
• Prerequisites: Node.js 20+ is required. An API key from a supported provider (OpenRouter, OpenAI, Anthropic, Google) is needed for AI features unless using the MCP server's integrated LLM.
• Links: PT-BR Tutorial: https://www.youtube.com/watch?v=5BPrfZAModk, Documentation User Guide (linked within README).

Highlighted Details

• Universal .context/ directory standardizes AI agent context management across diverse tools.
• PREVC (Planning, Review, Execution, Validation, Confirmation) workflow enforces structured, spec-driven AI development.
• Scale-Adaptive Routing dynamically adjusts workflow complexity based on project size.
• MCP server enables AI assistants with a gateway pattern and action-based tools for code exploration, planning, and agent orchestration.
• On-demand "Skills" provide specialized AI capabilities like commit message generation, code reviews, and security audits.
• Seamless export/import synchronization supports integration with numerous AI coding assistants including Cursor, Claude, Copilot, and Windsurf.

Maintenance & Community

The project is developed by AI Coders Academy, with resources and tutorials available via their YouTube Channel. Direct connection with the creator, Vini, is also encouraged. Specific details on community channels (e.g., Discord/Slack), roadmap, or active sponsorships are not explicitly detailed in the README.

Licensing & Compatibility

The project is released under the MIT License, permitting broad commercial use and integration without significant copyleft restrictions. It is designed for compatibility with a wide array of AI coding tools.

Limitations & Caveats

Effectiveness is contingent on the quality of underlying LLMs and user-defined specifications. Setup requires Node.js and may necessitate API keys for specific AI providers, potentially adding complexity. While extensive, integration with every niche AI tool may require manual MCP server configuration.