Openclaw Deeprecall

Provides persistent two-tier memory with semantic fact search and raw content retrieval, plus automatic cleanup of temporary session files.

This skill appears to implement a legitimate two-tier memory and summarization system, but there are notable privacy and configuration mismatches you should consider before installing: - Credential access: The summarizer reads OpenClaw configuration files (e.g., ~/.openclaw/openclaw.json, /etc/openclaw/openclaw.json, workspace/openclaw.json) to obtain LLM provider baseUrl and apiKey. Even though the manifest does not declare required credentials, the code will try to read and use those API keys. If those files contain secrets you don't want shared with this skill, do not install or run it until you review or remove those keys. - Permanent storage: By default the tool stores raw session content in the L2 archive (memory.db) and the SKILL explicitly states those records are permanent and never deleted. If you have sensitive data in session .md files, disable raw storing (use --no-store-raw where possible), or ensure the DB is stored in an isolated location you control, or encrypt/remove L2 storage. - Cross-workspace access: Path detection searches parent directories and 'agents' structures and may find configs or memory directories belonging to other agents. Run this skill in an isolated workspace (or set OPENCLAW_WORKSPACE to a dedicated directory) and test with dry-run options first. - Test safely first: Use summarize --test-config and cleanup --dry-run to observe behavior. Consider setting deeprecall.summarizer.preferred_provider to a local/test provider or null to trigger rule-based extraction, and use --no-store-raw while testing. - Desired changes: Prefer that the skill explicitly declare it requires OpenClaw provider credentials (or require OPENCLAW_API_KEY env), and provide an option to disable L2 archiving permanently. If you cannot confirm those changes, treat installation as potentially exposing local OpenClaw credentials and persistent raw data.

Type: OpenClaw Skill Name: openclaw-deeprecall Version: 0.1.2 The DeepRecall skill bundle provides a legitimate two-tier memory retrieval system for AI agents, using SQLite for structured storage and local Markdown files for raw logs. The code follows its stated purpose, utilizing parameterized SQL queries in `memory_retriever.py` to prevent injection and implementing a controlled file cleanup mechanism restricted to `.md` files within the agent's workspace. While `memory_summarizer.py` performs outbound network requests to LLM providers, it correctly retrieves API credentials from the user's existing OpenClaw configuration and limits data transmission to the content of memory files for summarization purposes.