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memory-cache

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.

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SKILL.md

Full skill instructions

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.