Manage and query your agent's distilled long-term memory with lightweight, fast SQLite-powered tools and automated daily extraction.

What to consider before installing: - Missing main extractor: The repository's extract_memory.py is an empty file, yet SKILL.md and README instruct you to run it automatically. Running the installed entry point as-is will likely do nothing or raise errors. Ask the author to provide/restore the extraction script or confirm which script should be used (nightly_meta_extract.py appears to contain extraction logic). - Path inconsistencies: The docs reference multiple similar paths (~/.openclaw/extensions/..., /home/node/.openclaw/workspace/scripts/..., ~/.openclaw/workspace). Confirm where the scripts will actually be installed and which HEARTBEAT.md line you should use to avoid executing the wrong script or a different system script. - Test vs runtime mismatch: Tests and other scripts assume extraction logic exists and will read workspace files (memory/*.md, REGRESSIONS.md) and update MEMORY.md and an SQLite DB. These are local file operations only, but they will read potentially sensitive workspace files and write to ~/.openclaw/database/insight.db — review those directories and ensure you trust the code before letting it run automatically. - No network exfiltration observed: I found no network calls, embedded endpoints, or credential exfil patterns — the tool appears local-only. Still, because it reads/writes files automatically, run it in preview/review mode first (the scripts support a --review flag) and/or in a sandboxed environment to verify behavior. - Recommended actions before enabling automation: 1. Ask the author to provide the missing extract_memory.py or confirm that nightly_meta_extract.py should be used; ensure the entry points in setup.py are correct. 2. Run extraction in review/preview mode: copy a few sample memory files into a test workspace and run the script with --review to inspect what would be written to the DB. 3. Set CLAW_MEMORY_DB_PATH and CLAW_MEMORY_WORKSPACE to a test location (not your real workspace) to verify behavior safely. 4. Inspect REGRESSIONS.md and MEMORY.md prior to running to confirm expected parsing won't cause overwrites. 5. If you plan to enable automatic heartbeat execution, update HEARTBEAT.md to call the correct script path and ensure the script is the intended implementation. If the author supplies the missing extractor and fixes the path/packaging inconsistencies, the skill appears coherent and local-only; until then, treat it as incomplete and proceed cautiously.

Type: OpenClaw Skill Name: claw-memory-lite Version: 1.0.1 The claw-memory-lite skill bundle provides a legitimate and well-documented local long-term memory system for OpenClaw agents. It uses a SQLite database (`insight.db`) to store and query distilled insights from daily logs, and includes 'meta-learning' scripts (`friction_detector.py`, `trust_scorer.py`, `regressions_guardrail.py`) that analyze failure records to improve agent performance. All operations are confined to the local `.openclaw` directory, and the code lacks any indicators of data exfiltration, unauthorized network access, or malicious prompt injection.