Skills vector-memory
Smart memory search with automatic vector fallback. Uses semantic embeddings when available, falls back to built-in search otherwise. Zero configuration - works immediately after ClawHub install. No setup required - just install and memory_search works immediately, gets better after optional sync.
git clone https://github.com/openclaw/skills
T=$(mktemp -d) && git clone --depth=1 https://github.com/openclaw/skills "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/bluepointdigital/vector-memory" ~/.claude/skills/clawdbot-skills-vector-memory && rm -rf "$T"
skills/bluepointdigital/vector-memory/SKILL.mdVector Memory
Smart memory search that automatically selects the best method:
- Vector search (semantic, high quality) when synced
- Built-in search (keyword, fast) as fallback
Zero configuration required. Works immediately after install.
Quick Start
Install from ClawHub
npx clawhub install vector-memory
Done!
memory_search now works with automatic method selection.
Optional: Sync for Better Results
node vector-memory/smart_memory.js --sync
After sync, searches use neural embeddings for semantic understanding.
How It Works
Smart Selection
// Same call, automatic best method memory_search("James principles values") // If vector ready: finds "autonomy, competence, creation" (semantic match) // If not ready: uses keyword search (fallback)
Behavior Flow
- Check: Is vector index ready?
- Yes: Use semantic search (synonyms, concepts)
- No: Use built-in search (keywords)
- Vector fails: Automatically fall back
Tools
memory_search
Auto-selects best method
Parameters:
(string): Search queryquery
(number): Max results (default: 5)max_results
Returns: Matches with path, lines, score, snippet
memory_get
Get full content from file.
memory_sync
Index memory files for vector search. Run after edits.
memory_status
Check which method is active.
Comparison
| Feature | Built-in | Vector | Smart Wrapper |
|---|---|---|---|
| Synonyms | ❌ | ✅ | ✅ (when ready) |
| Setup | Built-in | Requires sync | ✅ Zero config |
| Fallback | N/A | Manual | ✅ Automatic |
Usage
Immediate (no action needed):
node vector-memory/smart_memory.js --search "query"
Better quality (after sync):
# One-time setup node vector-memory/smart_memory.js --sync # Now all searches use vector node vector-memory/smart_memory.js --search "query"
Files
| File | Purpose |
|---|---|
| Main entry - auto-selects method |
| Vector implementation |
| OpenClaw wrapper |
Configuration
None required.
Optional environment variables:
export MEMORY_DIR=/path/to/memory export MEMORY_FILE=/path/to/MEMORY.md
Scaling
- < 1000 chunks: Built-in + JSON (current)
- > 1000 chunks: Use pgvector (see references/pgvector.md)
References
- Integration - Detailed setup
- pgvector - Large-scale deployment