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When Synthetic Data Hurts: On Catastrophic Forgetting in Skill Retrieval for LLM Agents
LLM agents increasingly rely on external skills retrieved at runtime, making skill selection from large repositories a critical challenge. We present a production skill router over 34,396 skills and a large-scale study of skill retrieval using limited real supervision and synthetic data. We found th
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