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Similar agent skills can share instructions but differ in their conditions of use. Query-based text selection may retain shared instructions and omit these distinctions. We introduce SkillContrast, a training-free selector that compares retrieved skills and retains their differing text with local context for a pretrain...
SameCapRisk-Bench is introduced, an auditable benchmark with 1,190 skill-risk units and 1,686 evaluation query cases: 694 marked-sibling units under public library pressure and 496 hard role-flip units where the same two skills swap helpful/risky roles across paired queries.
SMART is described, a rigorous symbolic performance-modeling library for ML systems whose main branch contains almost no code, and Regenerated implementations reproduce hand-audited reference models to round-off precision, suggesting that design docs can be the durable artifact for ML-systems co-design tools.
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