Two vector search systems in one skill, and they're not interchangeable. The embeddings_* tools handle large corpora (millions of vectors) with HNSW indexing that's 150x to 12,500x faster than brute force, depending on size. The ruvllm_hnsw_* tools are a WASM router capped at 11 patterns for sub-millisecond routing, not corpus search. If you're memory constrained with 5,000+ vectors, RaBitQ gives you 32x memory reduction via 1-bit quantization. The hyperbolic option maps hierarchical data to Poincare ball space instead of using cosine distance. Know which path you need before you start, the capacity limits are real and the use cases don't overlap.
npx skills add https://github.com/ruvnet/ruflo --skill vector-search