OpenMemo Memory – Persistent Memory for OpenClaw Agents

Provides OpenClaw agents with local, scene-aware, persistent structured memory for task deduplication and long-term workflow recall.

This skill appears to do what it claims and is local-first by default, but review these points before installing: - The skill talks to an OpenMemo server (default http://localhost:8765). It will not contact remote endpoints unless you explicitly change the endpoint and set allow_remote=True — do not do that unless you trust the remote service. - The memory tools encourage storing decisions, rationale, and error details. Avoid writing secrets (passwords, API keys, PII) into memories, or configure retention/access controls in your OpenMemo adapter. - Installing requires running third-party packages (openmemo, openmemo-openclaw) via pip and starting a local server (openmemo serve). Inspect those packages (PyPI/GitHub) if you need to verify their behavior before running. - Running a local server exposes an HTTP endpoint on your machine; run it with appropriate filesystem and network restrictions and monitor which processes/users can access it. What would change this assessment: evidence of hard-coded remote endpoints, requests for unrelated credentials or config paths, or code that attempts to read system files/network resources beyond the local adapter would be suspicious. If you want extra assurance, review the OpenMemo adapter source and run it in an isolated environment before connecting it to production agents.

Type: OpenClaw Skill Name: openmemo-clawhub-skill Version: 0.1.0 OpenMemo is a legitimate skill bundle designed to provide persistent, structured memory for OpenClaw agents. It uses a dual-mode architecture (skill.py) that guides users through installing a local adapter if not present. The skill communicates exclusively with a local endpoint (http://localhost:8765) by default, with explicit checks in config.py to prevent unauthorized remote data transfer. The tools (recall_memory, write_memory, check_task_memory in tools.py) and agent instructions (SKILL.md, rules.py) are consistent with the stated goal of task deduplication and experience recall. No malicious behavior, obfuscation, or exfiltration attempts were detected.