Vfs

What This Skill Does

The Vfs (AI Virtual Memory) skill by bkmashiro is a sophisticated, multi-agent shared memory management system designed for OpenClaw. It elevates simple file storage into a smart, context-aware repository. By combining embedding-based semantic search with FTS5 indexing, Vfs enables AI agents to recall information with extreme efficiency. It features advanced memory lifecycle management, including automatic decay, archival, and trash collection, ensuring that your agent's memory remains relevant and performant. Its unique Gossip Protocol allows for decentralized knowledge discovery, while the Librarian module provides centralized, high-speed knowledge routing to reduce redundant operations by 95%.

Installation

To integrate this skill into your OpenClaw environment, execute the following command in your terminal: clawhub install openclaw/skills/skills/bkmashiro/vfs After installation, you can verify the configuration by initializing the AVM client within your agent workflows or by mounting the memory via FUSE for direct file system access.

Use Cases

• Long-term Knowledge Retention: Perfect for agents that need to remember project details, user preferences, or historical technical data across weeks or months of interaction.
• Multi-Agent Collaboration: Teams of agents can use the Librarian or Gossip Protocol to share insights, ensuring that one agent’s discovery about a market trend or technical bug becomes immediately discoverable to others.
• Contextual Search: Ideal for retrieving specific snippets from large documentation sets without exhausting token budgets, thanks to intelligent truncation and TopicIndex recall.
• Offline/Decentralized Environments: The Gossip Protocol allows agents to find experts or relevant information even in decentralized architectures without a central server dependency.

Example Prompts

1. "Save the current NVDA stock market technical analysis to memory with high importance."
2. "Search the memory for previous discussions regarding the database optimization strategy we decided on last month."
3. "Which of our agents has the most information about current Kubernetes deployment issues?"

Tips & Limitations

• Token Budgeting: Always utilize the --max-tokens parameter during recall operations to avoid context window overflows when querying extensive knowledge bases.
• Topic Indexing: Use hashtags in your notes to leverage the TopicIndex capability, which enables O(1) recall compared to the slower 4-hop fallback of standard semantic searches.
• Privacy: If you are in a high-privacy environment, prefer the Gossip Protocol as it only broadcasts the existence of topics (via bloom filters) rather than sharing full content payloads.
• Limitations: While powerful, the Gossip Protocol has a <15% false positive rate for topic existence, which is a design trade-off for the O(1) local lookup speed.