---

name: memory-cache description: High-performance temporary storage system using Redis. Supports namespaced keys (mema:*), TTL management, and session context caching. Use for: (1) Saving agent state, (2) Caching API results, (3) Sharing data between sub-agents. metadata: {"openclaw":{"requires":{"bins":["python3"],"env":["REDIS_URL"]},"install":[{"id":"pip-dependencies","kind":"exec","command":"pip install -r requirements.txt"}]}}

Memory Cache

Standardized Redis-backed caching system for OpenClaw agents.

Prerequisites

• Binary: python3 must be available on the host.
• Credentials: REDIS_URL environment variable (e.g., redis://localhost:6379/0).

Setup

1. Copy env.example.txt to .env.
2. Configure your connection in .env.
3. Dependencies are listed in requirements.txt.

Core Workflows

1. Store and Retrieve

• Store: python3 $WORKSPACE/skills/memory-cache/scripts/cache_manager.py set mema:cache:<name> <value> [--ttl 3600]
• Fetch: python3 $WORKSPACE/skills/memory-cache/scripts/cache_manager.py get mema:cache:<name>

2. Search & Maintenance

• Scan: python3 $WORKSPACE/skills/memory-cache/scripts/cache_manager.py scan [pattern]
• Ping: python3 $WORKSPACE/skills/memory-cache/scripts/cache_manager.py ping

Key Naming Convention

Strictly enforce the mema: prefix:

• mema:context:* – Session state.
• mema:cache:* – Volatile data.
• mema:state:* – Persistent state.