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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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RabbitAI-Lab/rabbit-plugins-upstream
最近来源活动
2026年7月26日 20:50
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SKILL.md
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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.
# 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.
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