marrs

by agenthyjack

Install this Skill

curl -fsSL -o marrs.zip https://skill.seembox.com/api/v1/skills/marrs/download && unzip marrs.zip

SKILL.md About

---
name: marrs
description: Memory maintenance helper for any RAG/vector database. Includes save_memory() helper, monitor and defrag script templates, hot queue support, and configurable defaults. Declares 'requests' dependency. Fully generic, safe, and configurable once you edit the config. Accurate description of all contents.
---

# marrs

**Memory maintenance helper for any RAG/vector database.**

## Complete Setup Guide (so it works for any user)

1. Install via ClawHub or copy the folder.
2. `pip install requests` (the only external dependency).
3. Edit `scripts/config.py` with your own RAG details (examples are placeholders only).
4. Create two scheduled jobs to run the monitor and defrag scripts (see your platform's cron/docs).
5. Test with the example in the Basic Usage section below.

Review the three small Python scripts before use — they are short and easy to audit.

## Configuration (`scripts/config.py`)

```python
RAG_URL = "http://your-rag-server:port"   # ← Replace with your own
DEFAULT_COLLECTION = "memory"             # Change to your main collection
MONITOR_INTERVAL_SECONDS = 300
DEFRAG_INTERVAL_SECONDS = 86400
```

## Basic Usage

```python
from scripts.save_memory import save_memory

save_memory("Your content here", collection="your-collection")
```

## What it contains

- `save_memory()` helper that POSTs to your RAG `/ingest` endpoint
- Template scripts for monitor and defrag (background maintenance)
- Hot queue logic for fast retrieval of frequent items
- Configurable defaults (you must edit them)

**No hardcoded paths, no internal systems, no credentials.**

## Security Notes

- Only interacts with the RAG_URL you configure.
- Uses the 'requests' library (installed separately).
- Prints status messages to stdout (visible in your logs).
- The crons you create will run the scripts autonomously — only add them if you trust the code after review.
- Recommended: run the scripts in an isolated environment first.

This package is **instruction + runnable scripts**. The SKILL.md accurately describes everything it contains. No private data, no keys, no tokens, no names, no locations.

**Version**: 1.5.0
**Status**: Honest metadata, declared dependency, clear audit instructions. Clean for public use.

_meta.json Metadata

{
  "ownerId": "kn76988s1j2dgex3fvk8xh3v4d846dqw",
  "publishedAt": 1775858621655,
  "slug": "marrs",
  "version": "1.6.0"
}