vector-embed
Generate embeddings via npx ruvector@0.2.25 embed text (ONNX all-MiniLM-L6-v2, 384-dim), normalize, and store in HNSW index
Profile →npx skills add ruvnet/ruflo --skill vector-embed --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# 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**: ```bash 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: ```bash npm install ruvector-onnx-embeddings-wasm ``` 2. **Embed the input** (use the `text` subcommand, with text as a positional arg): - Single string: `npx -y ruvector@0.2.25 embed text "your text here"` - With output file: `npx -y ruvector@0.2.25 embed text "your text here" -o vec.json` - For a file: read its content via the Read tool, then pass it as the positional argument. - For batch: loop over files in shell — ruvector@0.2.25 has no built-in `--batch`/`--glob` flags. 3. **Adaptive (LoRA) variant**: `npx -y ruvector@0.2.25 embed text "..." --adaptive --domain code` 4. **Confirm** — report vector dimension (384), norm, and any output path wr
- When to use
- Steps
- MCP alternative
- Caveats
npm ls ruvector 2>/dev/null | grep '0.2.25' || npm install ruvector@0.2.25 npm install ruvector-onnx-embeddings-wasm claude mcp add ruvector -- npx -y ruvector@0.2.25 mcp start
What does the vector-embed skill do?
Generate embeddings via npx ruvector@0.2.25 embed text (ONNX all-MiniLM-L6-v2, 384-dim), normalize, and store in HNSW index
How do I install it?
Run `npx skills add ruvnet/ruflo --skill vector-embed --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From ruvnet/ruflo, a repository with 67,015 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.