Memory Health Probe

QMD memory system telemetry — measure index health, BM25 retrieval quality, coverage maps, and trend analysis. Use when running QMD memory backend and need d...

This skill appears to do exactly what it says: local telemetry for a QMD memory backend. Before installing or running it, do the following: (1) Review the script (scripts/memory_probe.py) yourself or run it in --dry-run to see exactly what it prints; (2) Confirm LANGFUSE_URL is localhost and not pointed at an external host; if you don't run Langfuse locally, treat the network calls as failing and inspect what would be sent; (3) Be aware it reads ~/.openclaw/logs/gateway.log and gateway.err.log — those logs can contain sensitive metadata, so run it in a trusted environment or sanitize logs if needed; (4) If you don't want qmd:// path or other metadata in telemetry, remove or sanitize those fields before sending; (5) Optionally change hardcoded Langfuse keys/URL to environment variables so the agent doesn't ship static credentials. Overall the skill is coherent, but audit data flows you consider sensitive before allowing it to run regularly.

Type: OpenClaw Skill Name: memory-health-probe Version: 1.0.1 The script `scripts/memory_probe.py` performs automated searches against the local QMD memory index using a 'canonical query set' that includes highly sensitive targets such as '1Password service account token' and 'Telegram personal account'. While the results are logged to a local Langfuse instance (localhost:3100) and local JSON files, the specific targeting of credentials and private account information for 'telemetry' purposes acts as a discovery mechanism for sensitive data. Furthermore, the `SKILL.md` file contains a misleading security note claiming base64 is used for local storage encoding, whereas it is actually used for HTTP Basic Authentication.