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Install in OpenClaw
/install memprocessor
Description
Enables AI agents to develop independent, evolving personas through organic memory growth, self-reflection, and layered memory management.
Usage Guidance
This package appears to implement the advertised persona/memory functionality, but there are multiple coherence and security concerns you should address before running it: 1) Do not run as root; change BASE_DIR from /root/.openclaw to a directory you control (or a temporary/isolated path). 2) Review and modify config.py (HOST, PORT, ALLOWED_ORIGINS, API_KEY) so the HTTP API is not publicly open or unauthenticated by default. 3) Inspect requirements.txt for any dependencies that make network calls or download models; decide whether to run in an isolated VM/container. 4) Be aware the service will persist user-provided content to disk (L3 markdown files, SQLite, FAISS index). If that content is sensitive, plan encryption or limited retention. 5) Fix documentation mismatches (example docs show port 9090 but config defaults to 8080). 6) If you need stronger assurance, ask the maintainer for an explanation of the default BASE_DIR choice, a documented authentication model, and full contents of embedding and persona service files to confirm whether they call external APIs. Running this code in a sandboxed environment (container/VM) and performing a manual code review of omitted service files (embedding/persona_service) is recommended before enabling it in any production agent.
Capability Analysis
Type: OpenClaw Skill
Name: memprocessor
Version: 0.1.1
The skill bundle is classified as suspicious primarily due to the use of 'pickle.loads' in 'app/core/l1_storage.py', which is a well-known Remote Code Execution (RCE) vulnerability if the cached data is tampered with. Furthermore, 'memory-manager.sh' and 'app/config.py' contain hardcoded paths to the '/root' directory and specific Conda environments, suggesting the application expects to run with elevated privileges and lacks proper environment isolation. While the 'persona' generation and multi-tier memory logic appear consistent with the stated purpose, these high-risk technical choices and broad filesystem assumptions pose a security risk to the host system.
Capability Assessment
Purpose & Capability
The repository implements a multi-layer memory system, persona engine, REST API, and CLI which aligns with the 'Memory Processor' description. However the registry metadata claimed 'instruction-only' (no install spec) while many code files are present; that mismatch is noteworthy. Also the app uses a fixed BASE_DIR (/root/.openclaw) for persistent storage which is a surprising design choice for a general-purpose skill and suggests it will write files as root unless reconfigured.
Instruction Scope
SKILL.md instructs installing requirements and running the bundled start-simple.py and demonstrates curl usage. The instructions omit key operational details: default config writes persistent data to BASE_DIR, the server defaults (config.py) specify PORT=8080 but README/SKILL examples use port 9090 — an inconsistency. The documentation does not call out that the service exposes an HTTP API with ALLOWED_ORIGINS ['*'] by default and an optional API_KEY that is empty by default, meaning it may run unauthenticated and accept incoming requests. The runtime instructions therefore leave broad discretion (network exposure, persistent storage) without warning.
Install Mechanism
There is no platform install spec in the registry; the SKILL.md expects the user to run 'pip install -r requirements.txt' and run the bundled Python scripts. The package contains requirements.txt and pyproject.toml and code files (no external download URLs). This is typical for a Python project but means the user will execute third-party Python dependencies locally — inspect requirements.txt before installing.
Credentials
Registry declares no required env vars, but the code reads many configuration settings (via pydantic Settings), including REDIS credentials, SQLITE path and an API_KEY. Defaults: BASE_DIR is hard-coded to '/root/.openclaw', ALLOWED_ORIGINS defaults to ['*'], API_KEY is empty. The skill will therefore create and persist files under /root/.openclaw, open a HTTP port, and allow wide CORS unless you change settings. Requesting no credentials is coherent, but the lack of required-declared config paths is inconsistent with actual disk and network access in the code.
Persistence & Privilege
The skill is not forced-always or privileged in the registry, but the code intentionally persists data across four storage layers (in-memory, SQLite, markdown files, FAISS vectors) under a fixed base directory. That persistent presence and the default to bind to all interfaces (HOST 0.0.0.0) and permissive CORS are significant privileges and should be treated as such; the SKILL.md does not warn about them.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install memprocessor - After installation, invoke the skill by name or use
/memprocessor - Provide required inputs per the skill's parameter spec and get structured output
Version History
v0.1.1
DreamMoon-MemProcessor 0.1.1 introduces a pioneering memory system focused on organic persona generation for AI agents.
- Enables AI agents to grow personas organically through experience and reflection
- Features a 10-dimensional persona model (Big Five + AI traits)
- Employs a four-layer memory architecture for efficient information management
- Supports automatic persistence and semantic search
- Provides quick start instructions for easy setup and persona generation
Metadata
Frequently Asked Questions
What is Memory Processor?
Enables AI agents to develop independent, evolving personas through organic memory growth, self-reflection, and layered memory management. It is an AI Agent Skill for Claude Code / OpenClaw, with 298 downloads so far.
How do I install Memory Processor?
Run "/install memprocessor" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is Memory Processor free?
Yes, Memory Processor is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does Memory Processor support?
Memory Processor is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created Memory Processor?
It is built and maintained by zfanmy (@zfanmy); the current version is v0.1.1.
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