Agent Memory Persistent Workspace Memory System

This skill appears to do what it says: create a file-based persistent memory structure and give your agent instructions to load it at startup. Before installing or using it, consider the following: - Review and control where you run the init script: it writes files into the chosen workspace. Don't run it in a directory that already contains sensitive files or system config. - Be cautious about adding the provided 'Session Start Protocol' to your agent's system prompt. That action intentionally grants long-lived, persistent instructions to the agent — only add it if you understand and trust the workspace and the files that the agent will read. - Treat HANDOFF.md and daily logs as potentially powerful: if untrusted users or integrations can write to those files, the agent may read and follow malicious instructions on next start. Restrict file write permissions and only allow trusted writers. - Never store secrets (API keys, passwords, private tokens) in these markdown files; the skill has no encryption or secret management. - The script itself is local and uses the Python standard library — review the templates and init_memory.py (they are short and readable) before running. If you want additional safety, run the init step in an empty sandbox workspace and inspect files it creates. - If you plan to use channel isolation features, confirm your agent/framework actually enforces those isolation rules. This package only creates directories and recommends conventions — enforcement depends on your agent implementation. If you want tighter guarantees, consider: running in a restricted workspace, applying filesystem permissions, and integrating a vetted secret store or vector DB instead of plaintext long-term memory files.

These patterns were detected by automated regex scanning. They may be normal for skills that integrate with external APIs. Check the VirusTotal and OpenClaw results above for context-aware analysis.