Enables AI agents to review past decisions, identify reasoning loops, and produce insights for self-improvement to enhance their cognitive processes.

This skill appears to be what it claims: a small local reflection logger/analyzer. Before installing: - Expect it to store full prompts, responses, and supplied metadata in plaintext under .agent_memory in the working directory; do not run it where prompts/responses contain secrets you cannot store. - The SKILL.md references agent_memory_reflector.py but the provided file is tool.py—verify filenames before running and inspect the source (tool.py) yourself. - There are no network calls or credential requests in the code, which reduces exfiltration risk; nevertheless, review the code if you will run it on sensitive data. - If you need privacy: modify the code to encrypt logs, change the storage path, or sanitize/redact sensitive fields before logging; consider running the skill inside an isolated container or environment. - The listed price ($29) in SKILL.md is unrelated to technical behavior; verify licensing/purchase outside this package if relevant.

Type: OpenClaw Skill Name: agent-memory-reflector Version: 1.0.0 The Agent Memory Reflector is a legitimate utility for logging and analyzing AI agent interactions locally. The code (tool.py) uses standard Python libraries to store interaction history in a local directory (.agent_memory) and provides basic pattern detection for reasoning loops or uncertainty, with no evidence of network activity, data exfiltration, or malicious execution.