This project provides a local-first CLI issue tracker designed to enhance AI-assisted development workflows. It addresses the challenge of managing tasks and preserving context across AI sessions, offering a streamlined experience for developers leveraging AI coding assistants. The primary benefit is robust, context-aware task management integrated directly into the development environment, minimizing context switching and improving AI collaboration efficiency.

How It Works

Chainlink operates as a local-first application, storing all issue data in a SQLite database (.chainlink/issues.db). Its core innovation lies in its deep integration with AI agents, particularly through behavioral guardrails and a context provider script. Key features include session management with context preservation (handoff notes, breadcrumb tracking) that survives AI context resets, and AI code hooks that inject best practices, enforce issue tracking, and manage large task decomposition. The context provider script enables integration with virtually any AI coding assistant by generating relevant project context.

Quick Start & Requirements

• Primary Install: Install via Cargo: cargo install chainlink-tracker.
• Prerequisites: Rust toolchain required for building from source. Python 3.6+ is necessary for the AI code hooks to function.
• Links: GitHub Repository (implied), VS Code Extension

Highlighted Details

• AI Code Hooks: Behavioral guardrails for AI sessions (e.g., Claude Code) enforcing coding standards, issue tracking adherence, and structured task breakdown.
• Context Compression Resilience: Session breadcrumbs and handoff notes allow context to be preserved even after AI context window resets.
• Local-First & No Sync: All data is stored locally, eliminating external service dependencies and sync complexity.
• Universal AI Integration: A context provider script facilitates integration with any AI coding assistant, not just specific platforms.
• Customizable Rules: Flexible configuration of AI behavior and tracking modes (strict, normal, relaxed) via markdown files.

Maintenance & Community

No specific details regarding notable contributors, sponsorships, or community channels (like Discord/Slack) were found in the provided README.

Licensing & Compatibility

• License: MIT.
• Compatibility: The MIT license is permissive, allowing for commercial use and integration into closed-source projects without significant restrictions.

Limitations & Caveats

The AI code hooks require Python 3.6+ to be installed and accessible. While the context provider script aims for broad compatibility, seamless integration with non-Claude AI agents may require manual setup via shell aliases or similar methods. The local-first design means there are no built-in features for multi-user collaboration or cloud synchronization.