What problem does it solve? It prevents impulsive adoption of new tools, frameworks, and workflows by forcing primary-source research, overlap analysis against the existing agent setup, and a clear verdict before any change is made. ## Core Features & Use Cases - Structured evaluation workflow: Checks a rejection log, frames the candidate's claim, researches primary sources, maps fit across setup layers (memory, agent behavior, harnesses, orchestration, efficiency, operations), and delivers a verdict. - Hard verdict contract: Every evaluation ends in exactly one of adopt, borrow, or reject, with a ranked list of borrowable ideas or a bounded reversible experiment. - Append-only rejection log: Records each rejection with claim, evidence, and revisit conditions in a Higgins vault file to avoid re-evaluating dismissed ideas. - Use Case: When you discover a new agent memory framework, run scout to compare it against your Higgins vault and existing retrieval stack, then receive a borrow verdict listing only the provenance and staleness ideas worth extracting. ## Quick Start Ask the agent to scout a specific project or idea, for example: scout the OKF Agent Memory project and tell me whether it is worth adopting for my setup.