ralph-loop

Automated agent-driven development loops implement features by running AI agents iteratively to write code and test it against defined user stories until all acceptance criteria are met. You define features as user stories with testable criteria, and the loop handles implementation and verification.

An agent-driven development loop is a continuous process where AI agents execute iteratively to implement and verify features. It works by defining features as user stories with testable acceptance criteria, then running agents in a loop to refine and complete tasks until all criteria are satisfied.

Set up the automated development loop using the ralph-setup recipe, which provides configurations for AI coding agents and recipes for user story setup and management. This integration ensures your features are defined as testable user stories before the agent loop begins execution.

Yes, this Skill integrates with AI coding agent configurations to verify features against testable acceptance criteria. Agents work iteratively to build features based on defined user stories and continuously refine them until all specific, verifiable requirements are met.

Yes, automated agent-driven development requires predefined user stories with testable acceptance criteria to function. The AI agents rely on these defined stories as input to know what to implement and verify, ensuring features are developed to meet specific, verifiable requirements.

The automated agent loop relies entirely on the quality of your defined user stories and testable acceptance criteria. Without clear, verifiable requirements, the AI agents cannot effectively implement or validate features, making precise story definition essential for successful continuous integration.