Vector Embed

Generate and store vector embeddings using the ruvector npm package.

When to use

Use this skill to embed text, code, or documents into 384-dimensional vectors for semantic search, similarity comparison, or clustering. ruvector uses ONNX all-MiniLM-L6-v2 with HNSW indexing (52,000+ inserts/sec, ~0.045ms search).

Steps

1. Ensure ruvector@0.2.25 is available:

   npm ls ruvector 2>/dev/null | grep '0.2.25' || npm install ruvector@0.2.25
   

   If embed text later reports ONNX WASM files not bundled, also run:

   npm install ruvector-onnx-embeddings-wasm
   

2. Embed the input (use the text subcommand, with text as a positional arg):