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1999azzar

Memory Cache

by azzar budiyanto · GitHub ↗ · v1.1.9
cross-platform ✓ Security Clean
2242
Downloads
1
Stars
9
Active Installs
11
Versions
Install in OpenClaw
/install memory-cache
Description
High-performance temporary storage system using Redis. Supports namespaced keys (mema:*), TTL management, and JSON serialization for session context and API...
Usage Guidance
This skill appears to do what it says: a Redis-backed cache accessed via a local Python script. Before installing, confirm: (1) REDIS_URL points to a trusted Redis instance (a misconfigured or public Redis can leak or accept data); (2) you understand that the skill will read a .env file and environment variables (do not store unrelated secrets there); (3) the script will create a .venv inside the skill directory and install packages from requirements.txt (no external downloads); (4) keys can be up to 512 MiB in value — avoid storing sensitive or large blobs unless intended. Also ask the publisher to fix the metadata mismatch (registry shows no required env vars while SKILL.md requires REDIS_URL) and to confirm the intended workspace path usage ($WORKSPACE). If you need tighter controls, restrict network access to the Redis host and avoid using the cache for secrets or long-term storage.
Capability Analysis
Type: OpenClaw Skill Name: memory-cache Version: 1.1.9 The skill bundle provides a Redis-backed memory cache system. All code and documentation align with the stated purpose of a high-performance temporary storage system. The `SKILL.md` instructions do not contain any prompt injection attempts. The `scripts/cache_manager.py` script includes robust key validation, uses `scan_iter` for safe key scanning, and handles Redis connections securely via environment variables. The `scripts/cache.sh` script safely sets up a virtual environment and executes the Python script without introducing shell injection vulnerabilities. There is no evidence of data exfiltration, malicious execution, persistence mechanisms, or obfuscation. The dependencies are standard and appropriate for the functionality.
Capability Assessment
Purpose & Capability
Name/description (Redis-backed cache with mema: namespace) aligns with the included Python script and shell helper. The functionality (set/get/scan/ttl/expire/ping) and declared dependencies (redis, python-dotenv, python3) are appropriate for the stated purpose.
Instruction Scope
SKILL.md instructs using a .env (env.example.txt) and running the provided cache_manager.py via python3 or scripts/cache.sh which creates a local virtualenv and installs requirements. The script loads environment variables (.env and the process environment) and only communicates with Redis; it does not contact external endpoints beyond the Redis server. Note: example command references $WORKSPACE path — runtime must ensure correct path mapping.
Install Mechanism
No remote downloads or arbitrary URLs; installation is local pip install -r requirements.txt performed by the provided script or by the SKILL.md metadata. Requirements are standard (redis, python-dotenv). The script will create a .venv directory inside the skill tree to install dependencies.
Credentials
The runtime requires REDIS_URL (and supports REDIS_HOST/PORT/PASSWORD/DB/timeouts), which is proportional to a Redis cache skill. However, top-level registry metadata lists no required env vars while SKILL.md metadata declares REDIS_URL — this mismatch should be clarified. The script reads .env and environment variables, so any secrets present in .env will be loaded.
Persistence & Privilege
always is false and model invocation is allowed (default), which is appropriate. The skill writes a local .venv but does not modify other skills or system-wide agent configurations. No elevated privileges or permanent always-on presence are requested.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install memory-cache
  3. After installation, invoke the skill by name or use /memory-cache
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.1.9
Simplified implementation: removed wrapper script, declared dependencies clearly in metadata, and ensured full manifest inclusion. Addressed all audit flags.
v1.1.8
Ensured inclusion of env.example.txt and verified full manifest with scripts and metadata.
v1.1.7
Final manifest and metadata fix. Standardized script naming and env declaration.
v1.1.6
Addressed audit findings: corrected install metadata, declared python3 requirement, ensured env.example inclusion, and verified manifest.
v1.1.5
CRITICAL: Fixed metadata inconsistencies (id: node -> pip), declared python3 requirement, renamed wrapper to cache.sh for clarity, and verified full manifest inclusion.
v1.1.4
CRITICAL: Fixed manifest inclusion for all files by using .py and .txt extensions. All logic and docs verified.
v1.1.3
Final manifest fix: renamed scripts/cache to scripts/cache.py and included env.example.txt to ensure ClawHub inclusion.
v1.1.2
Ensured all files including env.example and scripts are in the manifest. Updated metadata.
v1.1.1
CRITICAL: Ensured inclusion of .env.example and verified manifest contents via isolated build.
v1.1.0
Addressed audit: added .env.example, explicitly included wrapper script (as cache.sh), and declared env dependencies in metadata.
v1.0.0
Initial release – high-performance temporary storage and context caching using Redis. - Provides CLI tool for managing keys, values, TTLs, and Redis connectivity. - Strict key naming convention enforced: mema:<category>:<name>. - Supports categories for context, cache, state, and queue with recommended TTLs. - Includes example usage and full command documentation. - Returns specific exit codes for success, Redis errors, or invalid keys.
Metadata
Slug memory-cache
Version 1.1.9
License
All-time Installs 9
Active Installs 9
Total Versions 11
Frequently Asked Questions

What is Memory Cache?

High-performance temporary storage system using Redis. Supports namespaced keys (mema:*), TTL management, and JSON serialization for session context and API... It is an AI Agent Skill for Claude Code / OpenClaw, with 2242 downloads so far.

How do I install Memory Cache?

Run "/install memory-cache" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Memory Cache free?

Yes, Memory Cache is completely free (open-source). You can download, install and use it at no cost.

Which platforms does Memory Cache support?

Memory Cache is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Memory Cache?

It is built and maintained by azzar budiyanto (@1999azzar); the current version is v1.1.9.

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