self-improving-agent-python

Implement a 3-layer self-improvement process for agents to evaluate tasks, learn from outcomes, optimize performance, and share knowledge across agents.

This skill appears to do what it says: it stores evaluations, lessons, and optimization plans as JSON files in your WorkBuddy workspace and can copy a shared 'collective-wisdom.json' into every workspace under ~/.workbuddy. Before installing or running it: (1) confirm you are okay with the skill creating and writing files under ~/.workbuddy and across any workspace-* directories on the machine, (2) inspect the included scripts (they are all present and readable) and backup any existing shared-context/ self-improvement files you care about, (3) if you run sync_learning.py on a multi-user or shared machine, be aware it will write into other workspaces under ~/.workbuddy, and (4) run the scripts as a non-privileged user and in an isolated workspace if you want to limit impact. No network endpoints or credentials are used by the skill.

Type: OpenClaw Skill Name: self-improving-agent-python Version: 1.0.1 The skill bundle provides a framework for an AI agent to track its own performance, record lessons learned, and synchronize these insights across different local workspaces. The Python scripts (evaluate_task.py, learn_lesson.py, optimize_agent.py, and sync_learning.py) perform standard filesystem operations within the designated ~/.workbuddy directory and do not contain any network activity, obfuscation, or unauthorized data access.