Specification
- Skill ID
- ruvnet/ruflo/embeddings
- Publisher
- ruvnet
- Repository
- ruflo
- Installs
- 0
- Files
- 1
- Synced
- Sep 23, 2026
How to use it
Open any RiverX project, open the Skills panel in the chat, and search for this identifier. The files are fetched from the source repository at install time.
ruvnet/ruflo/embeddingsInstalls these files- SKILL.md
What this skill tells the agent
Embeddings Skill
Purpose
Vector embeddings for semantic search and pattern matching with HNSW indexing.
Features
| Feature | Description |
|---|---|
| sql.js | Cross-platform SQLite persistent cache (WASM) |
| HNSW | 150x-12,500x faster search |
| Hyperbolic | Poincare ball model for hierarchical data |
| Normalization | L2, L1, min-max, z-score |
| Chunking | Configurable overlap and size |
| 75x faster | With agentic-flow ONNX integration |
Commands
Initialize Embeddings
npx claude-flow embeddings init --backend sqliteEmbed Text
npx claude-flow embeddings embed --text "authentication patterns"Batch Embed
npx claude-flow embeddings batch --file documents.jsonSemantic Search
npx claude-flow embeddings search --query "security best practices" --top-k 5Memory Integration
# Store with embeddings
npx claude-flow memory store --key "pattern-1" --value "description" --embed
# Search with embeddings
npx claude-flow memory search --query "related patterns" --semanticQuantization
| Type | Memory Reduction | Speed |
|---|---|---|
| Int8 | 3.92x | Fast |
| Int4 | 7.84x | Faster |
| Binary | 32x | Fastest |
Best Practices
- Use HNSW for large pattern databases
- Enable quantization for memory efficiency
- Use hyperbolic for hierarchical relationships
- Normalize embeddings for consistency
More from ruvnet
Use this skill in a project
Open any RiverX project, search the Skills panel for ruvnet/ruflo/embeddings, and install it in one click.