Supermemory

Long-term agent memory with atomic fact extraction, relational versioning, semantic search, and entity profiles. Extracts facts from conversations, tracks ho...

Before installing or enabling this skill: (1) Verify the PyPI package and GitHub repository contents — run pip install only from trusted sources and inspect the code. (2) Expect a local DB at ~/.supermemory/memory.db — if you handle sensitive data, consider encrypting the DB or disabling auto-ingest. (3) The SKILL.md requires an LLM API key (Anthropic by default) and may use other provider keys; do not supply high-privilege or long-lived secrets — use least-privilege/test keys. (4) Running 'supermemory serve' exposes a local HTTP API — ensure appropriate firewall/access controls. (5) Disable automatic ingestion of agent responses until you've audited what the extractor sends to external LLMs (avoid unintended data exfiltration). (6) Ask the publisher to correct registry metadata to declare required env vars and config paths; if they cannot, treat the skill as higher risk. If you need to proceed, run the package in an isolated environment (VM/container) and review network traffic and code first.

Type: OpenClaw Skill Name: openclaw-supermemory Version: 0.2.1 The openclaw-supermemory skill is a utility for managing long-term agent memory using SQLite and local embeddings. The SKILL.md and _meta.json files describe standard functionality for fact extraction, semantic search, and entity profiling without any indicators of malicious behavior, data exfiltration, or prompt injection attacks.