Pidan Memory

Local persistent vector memory system using LanceDB and Ollama for semantic search and multi-user isolated long-term AI assistant memory.

This skill appears to implement the described local memory system, but review and consider the following before installing: - Metadata mismatch: The registry lists no required binaries/env-vars, but the hook and docs require python3 and a running Ollama (localhost:11434). The code also expects the OPENCLAW_USER_ID environment variable for permission checks. Make sure you understand and set these before enabling the hook. - Privacy: Enabling the Hook causes automatic capture of message content and writing to ~/.openclaw/workspace/memory. If you enable it, verify the data directory and retention policies, and confirm whether any sensitive content could be recorded. - Environment exposure: handler.ts passes process.env to the spawned Python process. That means any environment variables available to the host process will be visible to the script. Avoid running it in a context containing secrets you don't want exposed. - Installer scripts: The included scripts can install Ollama and pull models. The Linux installer uses curl | sh (remote install script); run such scripts only from trusted sources or inspect them first. Model downloads can be large and the download 'accelerator' script repeatedly kills and restarts downloads — this is unusual but not obviously malicious. - Recommended steps: inspect the full installer script from https://ollama.ai/install.sh before running; run the skill in a sandbox or test environment first; back up and inspect ~/.openclaw/workspace/memory before enabling automatic hooks; and confirm that OPENCLAW_USER_ID will be set by your platform as expected. If you want, I can list the exact files and lines that reference OPENCLAW_USER_ID, the curl|sh install command, and where process.env is forwarded so you can inspect them in detail.

Type: OpenClaw Skill Name: pidan-memory Version: 1.1.2 The pidan-memory skill bundle implements a local vector-based memory system using LanceDB and Ollama. It includes automated chat analysis (auto_memory.py), semantic search (memory_lance.py), and service management scripts. While the installer (scripts/install_ollama.sh) uses the risky 'curl | sh' pattern, it points to the official Ollama domain to install a legitimate dependency. The system demonstrates security consciousness by prioritizing environment variables (OPENCLAW_USER_ID) over user-supplied parameters for permission checks during memory deletion and sharing operations.