Automatically converts raw long conversations into structured, themed Markdown knowledge cards with source traceability, running incrementally and silently i...

Before installing or enabling this skill, consider the following: - It will read your conversation logs from ~/.openclaw/agents/main/sessions/*.jsonl and send those conversations to Google's Gemini API for processing. Any secrets or personal data in those conversations will be transmitted to an external service even though the prompt instructs the model to redact secrets — that is not a guaranteed client-side safe filter. - The registry metadata does not declare the GEMINI_API_KEY requirement or the config paths the code uses; treat that omission as a red flag and verify the behavior yourself. - The script writes Markdown topic files and a state.json in ~/.openclaw/workspace/, and it embeds filesystem paths/line numbers pointing back to raw session files — this can make raw data easier to find and expose. - Mitigations: (1) Run the script manually for testing rather than enabling automatic runs; (2) inspect the session JSONL files to ensure they contain no sensitive info before sending; (3) prefer using a dedicated, limited-scope API key and monitor its usage; (4) consider adding client-side redaction (remove/replace API keys, PII) before sending content to the model; (5) lock down file permissions on ~/.openclaw/workspace and the .env file; (6) if organizational policy forbids sending conversation contents to third-party models, do not enable this skill. If you want help producing a safe wrapper that does client-side redaction or that runs in an isolated environment, I can assist with a patch or run strategy.

Type: OpenClaw Skill Name: auto-memory-distiller Version: 1.0.0 The skill is a legitimate utility designed to summarize OpenClaw session logs into structured Markdown memory cards using the Gemini API. It features incremental processing via a state file (state.json), basic path traversal protection for output files, and explicit instructions within the LLM prompt to redact sensitive information like API keys from the distilled output (distiller.py). While it processes potentially sensitive conversation logs and sends them to an external LLM provider, this behavior is transparently documented and aligned with its stated purpose.