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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.

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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.

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Install for OpenClaw

Quick setup
  1. Download the package from Yavira.
  2. Extract the archive and review SKILL.md first.
  3. Import or place the package into your OpenClaw setup.

Requirements

Target platform
OpenClaw
Install method
Manual import
Extraction
Extract archive
Prerequisites
OpenClaw
Primary doc
SKILL.md

Package facts

Download mode
Yavira redirect
Package format
ZIP package
Source platform
Tencent SkillHub
What's included
install.sh, MEMORY_STRUCTURE.md, CHANGELOG.md, README.md, AGENTS.md, SKILL.md

Validation

  • Use the Yavira download entry.
  • Review SKILL.md after the package is downloaded.
  • Confirm the extracted package contains the expected setup assets.

Install with your agent

Agent handoff

Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.

  1. Download the package from Yavira.
  2. Extract it into a folder your agent can access.
  3. Paste one of the prompts below and point your agent at the extracted folder.
New install

I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Then review README.md for any prerequisites, environment setup, or post-install checks. Tell me what you changed and call out any manual steps you could not complete.

Upgrade existing

I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Then review README.md for any prerequisites, environment setup, or post-install checks. Summarize what changed and any follow-up checks I should run.

Trust & source

Release facts

Source
Tencent SkillHub
Verification
Indexed source record
Version
1.0.0

Documentation

ClawHub primary doc Primary doc: SKILL.md 15 sections Open source page

Vector 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.

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.

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

memory_search

Auto-selects best method Parameters: query (string): Search query max_results (number): Max results (default: 5) 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

FeatureBuilt-inVectorSmart WrapperSynonymsβŒβœ…βœ… (when ready)SetupBuilt-inRequires syncβœ… Zero configFallbackN/AManualβœ… 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

FilePurposesmart_memory.jsMain entry - auto-selects methodvector_memory_local.jsVector implementationmemory.jsOpenClaw 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

Category context

Code helpers, APIs, CLIs, browser automation, testing, and developer operations.

Source: Tencent SkillHub

Largest current source with strong distribution and engagement signals.

Package contents

Included in package
5 Docs1 Scripts
  • SKILL.md Primary doc
  • AGENTS.md Docs
  • CHANGELOG.md Docs
  • MEMORY_STRUCTURE.md Docs
  • README.md Docs
  • install.sh Scripts