SkillSeek matches an LLM-mediated retrieval loop on 89 SkillsBench tasks with BM25 plus a small reranker, cutting per-trial spend from USD 51.30 to USD 27.54
The work presents SkillSeek, an open-source two-stage skill retriever (a BGE-base bi-encoder feeding a small cross-encoder, exposed over MCP), and across a grid of two skill pools and two backbones on the 89-task SkillsBench benchmark observes that plain bm25 alone records a pass rate at or above Liu et al.'s LLM-mediated loop on three of four settings, with a small cross-encoder covering the remaining difference on the fourth (34K pool with Qwen3.5) at the same 0.442, while total per-trial spend drops from USD 51.30 to USD 27.54 (within fifty cents of the USD 27.41 no-skill baseline), a pattern the authors attribute to a first-stage recall ceiling.