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OpenClaw

Memory Cache

Memory Cache

1999azzar0 source installs☆ 0 Repository stars
View source ↗InstallationSKILL.md ↗

Installation

Follow the repository instructions for this skill and your agent. Review the files and dependencies before adding it to your workflow.

SkillHub CLI

skillhub install 1999azzar/memory-cache

Inspect the source and compatibility requirements, then follow its installation steps.

Give your agent the source link and ask it to inspect instructions and dependencies before explaining the installation steps.

View source ↗Guides

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.

Source information

Source
github
Repository
openclaw/skills
Path
skills/1999azzar/memory-cache
Version
—
Commit
d307d3d6d356f86b9ce0fda3e169b3b1468d85d8
Classification source
rules
Status
active
Visibility
public

These signals come from indexed source analysis and may lag behind changes. Check the current source files.

Extracted content

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
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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