How to build a self-improvement loop for your Skills

In recent discussions, the concept of "loops" has been highlighted as a method to enhance the capabilities of agents through self-improvement cycles. A practical example involves using cloud agents and Skills to create self-improvement loops, where agents refine their Skills based on external feedback. Specifically, the process is demonstrated with an issue triage Skill that categorizes issues into buckets like "ready-to-implement" or "needs-info." This system involves an inner agent loop that applies the Skill and records interactions, and an outer agent loop that evaluates these runs and modifies the Skill based on feedback, such as changes made by human reviewers. This feedback mechanism is facilitated through Warp and Oz's cloud agent platform, integrating with GitHub's issue tracking, allowing for continuous improvement with each iteration. The framework behind this approach is used to manage the Warp open-source repository and is available for others to adopt.

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