소개
Amp-Skill provides deep insights into how AI agents are interrupted during tasks by distilling usage patterns from Amp thread history. Built on a DuckDB foundation, it identifies critical rejection scenarios such as 'two-lock' cascades—where an agent repeatedly attempts rejected actions—and high-rejection threads involving sensitive file types like .org or security scripts. By analyzing abandonment and revert data, this skill enables developers to implement smarter backoff strategies and coordinate alternative approaches using triadic logic, ultimately leading to more responsive and context-aware agent interactions.
