Skills memory-cache

Name: memory-cache
Author: openclaw

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.

install

source · Clone the upstream repo

git clone https://github.com/openclaw/skills

Claude Code · Install into ~/.claude/skills/

T=$(mktemp -d) && git clone --depth=1 https://github.com/openclaw/skills "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/1999azzar/memory-cache" ~/.claude/skills/openclaw-skills-memory-cache && rm -rf "$T"

OpenClaw · Install into ~/.openclaw/skills/

T=$(mktemp -d) && git clone --depth=1 https://github.com/openclaw/skills "$T" && mkdir -p ~/.openclaw/skills && cp -r "$T/skills/1999azzar/memory-cache" ~/.openclaw/skills/openclaw-skills-memory-cache && rm -rf "$T"

manifest: skills/1999azzar/memory-cache/SKILL.md

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

Copy
```
env.example.txt
```
to
```
.env
```
.
Configure your connection in
```
.env
```
.
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.