Why I stopped using semantic embeddings for tool selection and switched back to BM25 [D]

In three linesAn agent developer ditched semantic embeddings for tool selection, switching to BM25. With 140 MCP tools in production, cosine similarity on short descriptions (<50 tokens) failed (64% accuracy): key discriminators (specific nouns) diluted in embedding space. BM25 on flat-text projection achieves 81% top-1.

Summary generated by Claude — human-verified