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Agent Skills Learned How to Forget Bad Advice

SkillProx replays diagnosis-driven edits, rolls back regressions and audits whether each stored instruction still earns its place.

Published Updated Story ID: mp-2026-08-10-010
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Summary

SkillProx replays diagnosis-driven edits, rolls back regressions and audits whether each stored instruction still earns its place.

The framework treats textual agent skills as modular knowledge rather than model weights. Its forward step tests proposed edits on the same task batch and reverses regressions; its backward step decomposes a skill into auditable units, estimates each unit's contribution and consolidates or removes it behind a validation gate. Across multiple language-model backbones, the authors report a three-percentage-point average accuracy gain over their strongest gradient-based baseline. The evidence is benchmark-bound preprint work.

Why it matters

SkillProx replays diagnosis-driven edits, rolls back regressions and audits whether each stored instruction still earns its place.

Limits and context

No additional limitation was separately recorded.

Key claims

  1. SkillProx replays diagnosis-driven edits, rolls back regressions and audits whether each stored instruction still earns its place.

    Evidence: source-2026-08-10-010

Sources

  1. arXiv preprint 2608.07449arXiv · primary research

Corrections

No corrections have been recorded for this story.