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Vector Memory Hack

by @mig6671

Fast semantic search for AI agent memory files using TF-IDF and SQLite. Enables instant context retrieval from MEMORY.md or any markdown documentation. Use when the agent needs to (1) Find relevant context before starting a task, (2) Search through large memory files efficiently, (3) Retrieve specific rules or decisions without reading entire files, (4) Enable semantic similarity search instead of keyword matching. Lightweight alternative to heavy embedding models - zero external dependencies, <

Versionv1.0.3
Source

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What to do next

Skills are meant to be used inside your own AI agent. Install it, run a quick smoke test, then ask your agent to apply it to your real task.

1
Install into your agentCopy the ClawHub install command and run it where your OpenClaw/agent environment is configured.
2
Run a smoke testUse the test prompt below to confirm the skill loads and understands the workflow before relying on it.
3
Use it in your own agentPaste your actual task into Manus, OpenClaw, Claude Code, Cursor, or another agent that supports skills.
I just installed the Vector Memory Hack skill. Please run a quick smoke test: explain what this skill can do, ask me for the minimum input it needs, then produce one small sample output for a realistic task.