Mining Agent Skills from Production Traces
Agent skills that record procedural instructions are increasingly mined from execution traces rather than curated by hand. Skill-mining pipelines often use known task outcomes or feedback to guide skill construction. In production, reliable information on whether a run has succeeded may be unavailable. We study how the sampling of execution traces, access to success or failure information, and the form of the mined skills affect downstream task performance. Holding the mining pipeline fixed, we compare six combinations of mining evidence and skill forms. Mining evidence has three levels: successful trajectories only, successes and failures with their outcome labels, or the same mix with l...
| Authors | Yue Ran Kang, Colton Mikolajczyk, Chhaya Methani et al. |
|---|---|
| Primary category | cs.AI |
| Published | 5 October 2026 |
| Last updated at source | 5 October 2026 |
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