Create, test, and iteratively improve AI agent skills with structured evaluation and benchmarking.

Guides you through the full skill development lifecycle: intent capture, drafting, test case creation, evaluation, and iteration based on user feedback Runs parallel test cases with and without the skill to measure impact, capturing timing and token usage for quantitative comparison Generates an interactive browser-based reviewer showing outputs, qualitative feedback, and benchmark metrics (pass rates, latency, token efficiency) across iterations Includes description optimization to improve skill triggering accuracy by testing 20 realistic trigger/non-trigger queries and iterating the description through up to 5 rounds