Overview
What It Does
Vector Memory Hack packages a focused media & files workflow for an AI agent. 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, <10ms search time. It is best suited to users who can review the resulting actions and provide only the accounts, files, or command access needed for the task. It is not a substitute for human approval on destructive, financial, security-sensitive, or public-facing actions.
Task ideas
Popular Use Cases
- Create or edit a common file format
- Extract information from uploaded files
- Convert content into a polished deliverable
- Automate repetitive media operations
Installation
Install this Agent Skill
OpenClaw
clawhub install @mig6671/vector-memory-hackCommands derived from the public ClawHub API record. Checked 2026-09-02. Review the source before running them.
Before you start
Requirements
| OpenClaw or ClawHub | Required / review |
| Review the source instructions before installation | Required / review |
| Paid service | Check source |
| Supported system | Check source |
Popularity context
Why It’s Popular
Vector Memory Hack addresses a recognizable media files workflow and is included from current public ClawHub adoption.
Alternatives
