Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Tencent SkillHub ยท Developer Tools
Lancedb Memory
Manage and retrieve long-term memories with LanceDB using semantic vector search, category filtering, and detailed metadata storage.
skill openclawclawhub Free
Manage and retrieve long-term memories with LanceDB using semantic vector search, category filtering, and detailed metadata storage.
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Install for OpenClaw
Quick setup
- Download the package from Yavira.
- Extract the archive and review SKILL.md first.
- Import or place the package into your OpenClaw setup.
Package facts
- Download mode
- Yavira redirect
- Package format
- ZIP package
- Source platform
- Tencent SkillHub
- What's included
- SKILL.md, clawdbot_memory.py, final_memory.py, lancedb_memory.py, simple_memory.py, working_memory.py
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.
- Download the package from Yavira.
- Extract it into a folder your agent can access.
- 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. 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. 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
Provenance
- Publisher
- pntrivedy
- Source page
- View original listing
- Canonical URL
- Open canonical page
Documentation
Global instance
lancedb_memory = LanceMemoryDB() def add_memory(content: str, category: str = "general", tags: List[str] = None, importance: int = 5, metadata: Dict[str, Any] = None) -> int: """Add a memory to the LanceDB store.""" return lancedb_memory.add_memory(content, category, tags, importance, metadata) def search_memories(query: str, category: str = None, limit: int = 10) -> List[Dict]: """Search memories using semantic similarity.""" return lancedb_memory.search_memories(query, category, limit) def get_memories_by_category(category: str, limit: int = 50) -> List[Dict]: """Get memories by category.""" return lancedb_memory.get_memories_by_category(category, limit) def get_memory_stats() -> Dict[str, Any]: """Get memory storage statistics.""" return lancedb_memory.get_memory_stats()
Example usage
if name == "main": # Test the database print("Testing LanceDB memory integration...") # Add a test memory test_id = add_memory( content="This is a test memory for LanceDB integration", category="test", tags=["lancedb", "integration", "test"], importance=8 ) print(f"Added memory with ID: {test_id}") # Search for memories results = search_memories("test memory") print(f"Search results: {len(results)} memories found") # Get stats stats = get_memory_stats() print(f"Memory stats: {stats}")
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 Scripts1 Docs
- SKILL.md
- clawdbot_memory.py
- final_memory.py
- lancedb_memory.py
- simple_memory.py
- working_memory.py