# Knowledge Vault

> Long-term RAG memory storage for your agent, powered by TiDB Vector.

- Skill: `johnalbertini14-glitch/knowledge-vault` (Agent Skill, multi-file: 6 files)
- Install (CLI): `npx skillmds@latest add johnalbertini14-glitch/knowledge-vault`
- Raw SKILL.md: https://api.skillmd.com/api/skills/johnalbertini14-glitch/knowledge-vault/raw
- Safety review: pending (external: skill-scanner PASS, skillspector PASS)
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: AI & ML
- Author: johnalbertini14-glitch (https://skillmd.com/u/johnalbertini14-glitch)
- Updated: 2026-09-09
- Page: https://skillmd.com/skills/johnalbertini14-glitch/knowledge-vault

---


# Knowledge Vault (Powered by TiDB Zero)

## Overview
**Knowledge Vault** is a Long-Term Memory module for AI Agents, powered by **TiDB Vector Search (RAG)**.

Traditional agent memory (context window) is ephemeral and limited. Knowledge Vault allows agents to:
1.  **Store:** Ingest documents, notes, and facts as vector embeddings.
2.  **Retrieve:** Semantically search for relevant information based on user queries ("RAG").
3.  **Remember:** Access unlimited historical context without overflowing the LLM prompt.

## Why use this?
*   **Infinite Recall:** Store millions of documents without confusing the agent.
*   **Contextual Relevance:** Find *exact* paragraphs related to a question, not just keywords.
*   **Privacy:** Keep your knowledge base private in your own TiDB Cloud instance.

## Prerequisites
*   **TiDB Cloud (Serverless):** With Vector Search enabled.
*   **Embedding Model:** Requires `GEMINI_API_KEY` (or compatible).

### 🔐 Security & Provisioning
This skill operates in two modes:
1.  **Bring Your Own Database (Recommended):** Set `TIDB_HOST`, `TIDB_USER`, `TIDB_PASSWORD` environment variables. The skill will use your existing database.
2.  **Auto-Provisioning (Fallback):** If no credentials are found, the skill calls the **TiDB Zero API** to create a temporary, ephemeral database for you. It caches the connection string locally (`~/.openclaw_knowledge_vault_dsn`) to persist memory across runs.

## Installation

### 1. Add to `TOOLS.md`
```markdown
- **knowledge-vault**: Store and retrieve knowledge using vector search.
  - **Location:** `{baseDir}/skills/knowledge_vault/SKILL.md`
  - **Command:** `python {baseDir}/skills/knowledge_vault/run.py --action search --query "<QUESTION>"`
```

### 2. Add to `AGENTS.md` (Protocol)
Copy [PROTOCOL.md](PROTOCOL.md).

## Usage
*   **Add Knowledge:**
    ```bash
    python {baseDir}/run.py --action add --content "The user prefers spicy food but is allergic to peanuts."
    ```
*   **Search (RAG):**
    ```bash
    python {baseDir}/run.py --action search --query "What are the user's dietary restrictions?"
    ```