This project addresses the challenge of managing AI development workflows by providing a standardized, dependency-free set of markdown files. It targets engineers and power users working with AI IDEs, offering a way to ensure consistent AI-assisted development processes without the typical versioning and dependency issues of traditional tools. The primary benefit is a predictable and robust AI development environment that integrates seamlessly across various AI coding assistants.

How It Works

Flow-kit operates on a "pure markdown" philosophy, eschewing traditional runtime executables. It comprises a structured collection of markdown files—methodology, rules, prompts, and templates—that AI models can directly reference using @ syntax within their IDEs. This approach defines a multi-stage development lifecycle, from initial change proposals to final integration, allowing AI agents to follow a defined process by reading and acting upon these markdown artifacts. This design prevents version conflicts and dependency hell, making the workflow stable and independent of upstream tool updates.

Quick Start & Requirements

• Primary install: Copy the entire flow-kit/ folder into your project's root directory.
• Prerequisites: No specific software installations (e.g., npm, pip) are required for flow-kit itself. It relies on AI IDEs supporting local file referencing (e.g., @flow-kit/METHODOLOGY.md). Compatible with Windsurf, Claude Code, Cursor, Copilot, Gemini, Cline, and others.
• Estimated setup time: Approximately 30 seconds.
• Links: The README serves as the primary documentation.

Highlighted Details

• Dependency-Free Workflow: Utilizes markdown files as the sole artifact, eliminating runtime dependencies and versioning issues.
• Universal AI Compatibility: Works with any AI IDE capable of referencing local files via @ syntax.
• Structured Development Stages: Defines a clear 8-stage process from 0-change to 7-integration, each with dedicated prompts and templates.
• GO.md Unified Entry Point: Simplifies interaction by automatically determining the current stage, generating change IDs, and loading necessary context.
• Brownfield Safety Rails: Includes specific mechanisms like I-intel-scan and DESIGN 0.5 to align with existing project architectures and prevent destructive AI actions.
• Optional Runtime Adapters: Forge can be integrated for stricter runtime enforcement in Claude Code, though flow-kit functions independently.

Maintenance & Community

The project is maintained by rihebty. The README does not detail specific community channels, contributors, or sponsorships.

Licensing & Compatibility

• License: MIT.
• Compatibility: The MIT license and lack of runtime dependencies make it highly compatible with commercial and closed-source projects.

Limitations & Caveats

The "pure markdown" approach necessitates more manual steps compared to integrated tools. While designed for consistency, AI behavior can still vary, and the README notes a potential for AI to skip steps. The workflow can be token-intensive, particularly for full cycles, although context management is optimized per task. Without optional runtime adapters like Forge, adherence to the defined workflow relies solely on the AI's interpretation.