ralph-tasks

You can manage a JSON-based task queue for autonomous AI coding by adding, listing, and removing tasks from a persistent queue. A provided wake-up script initiates a continuous execution loop that processes tasks sequentially, updates status, and commits code changes.

Automating sequential task processing for AI coding agents is best handled through a continuous execution loop triggered by a wake-up script. This mechanism processes tasks sequentially, updates their status, commits code changes, and automatically logs learnings throughout the workflow.

Yes, you can add tasks to the workflow automation queue with codebase context exploration. The system supports contextual task addition by optionally utilizing an Explore agent to discover relevant codebase context before queuing the task for the autonomous loop.

An autonomous agent handles task status updates and code commits by running a continuous execution loop. As it sequentially processes tasks from the JSON queue, it automatically updates their status, commits the resulting code changes, and logs learnings for future reference.

No external dependencies are required to run the autonomous task queue script. The skill operates independently using its internal scripts and JSON-based task queue to manage the continuous execution loop for your AI coding workflow.