What problem does it solve?
Manually managing development operations like agent assignment, code formatting, state persistence, and learning from past actions introduces inefficiencies and human error in AI-assisted workflows.
Core Features & Use Cases
- Pre-Operation Hooks: Automatically validate, prepare, and assign the best agents before any coding, command execution, or task initiation.
- Post-Operation Hooks: Automatically format code, analyze outcomes, update memory, and train neural patterns after every action, ensuring continuous improvement and consistency.
- Session & Memory Management: Persist development session states, restore context, and synchronize knowledge across all swarm agents for seamless collaboration.
- Use Case: Set up a CI/CD pipeline where every code edit automatically triggers a linter, updates a shared memory of changes, and trains the AI on successful coding patterns, while every task completion exports performance metrics and a summary report.
Quick Start
Initialize the hooks system with default configurations.
Then, run a pre-task hook for "Implement user authentication" to auto-spawn agents.
Then, run a post-edit hook for "src/auth.js" to auto-format and store in memory.
