Memory OS

Persistent memory system for AI agents — daily logs, long-term memory, identity files, and heartbeat-driven recall. Solves context amnesia across sessions.

This blueprint is internally consistent with its goal of creating local memory files, but review before installing: - Read references/blueprint.yaml and references/guide.md fully (the SKILL.md itself advises this). The skill relies on you performing a manual security self-audit before any file creation. - Inspect every template (SOUL.md, USER.md, MEMORY.md, HEARTBEAT.md, daily note templates) for any secrets or PII and remove or redact anything sensitive. - Consider changing AGENTS.md startup behavior to require per-session confirmation before loading MEMORY.md or other sensitive files (i.e., disable the 'Don't ask, just do it' instruction if you want explicit consent each session). - Be aware that even though the blueprint makes no network calls itself, the platform will include file contents in model prompts during normal operation; if your provider or environment forwards prompts to external APIs, those files may be transmitted off-machine. If that is a concern, avoid storing highly sensitive data in these files or ensure you're in a private/offline execution environment. - Disable or carefully configure HEARTBEAT integrations (email, calendar, project checks) until you confirm they will not cause outbound network actions without explicit approval. If you want lower risk: install only SOUL.md/USER.md and keep MEMORY.md or daily notes private or gated behind an explicit 'load memory' command. If you need help making AGENTS.md require explicit confirmation each session, ask the skill author or your operator to modify the startup protocol before installing.

Type: OpenClaw Skill Name: memory-os Version: 1.0.0 The 'memory-os' skill is a well-documented persistent memory system designed to store agent identity and session context in local Markdown files (SOUL.md, USER.md, MEMORY.md). It features a robust installation protocol including a mandatory security self-audit (Step 0) and a dry-run confirmation (Step 4) to ensure user consent. The logic is entirely local, non-destructive, and contains explicit safety instructions for the agent to prevent unauthorized external actions or data sharing.