Workbuddy Smart Learning

基于反馈和行为信号，Workbuddy Smart Learning实现任务模式识别、知识蒸馏及自适应警报，持续优化执行效率。

This skill appears to do what it says: it reads local memory/markdown files and session signals, analyzes patterns, and writes templates, alerts and threshold state into a .workbuddy/memory folder. There is no network code or requested credentials in the provided files. Before installing: (1) confirm the workspace path used by the skill (learn.py has a Windows default c:/Users/Administrator/...), so change it if you don't want it to access that location; (2) be aware it will read your MEMORY.md and other .md files under the workspace and will write YAML/JSON artifacts there — do not run it on a workspace containing highly sensitive material unless you are comfortable with local persistence; (3) review any generated templates/avoid_*.yaml files before using them to run automated actions; (4) if you expect cross-workspace/template sharing or remote publication (mentioned in README), note the code does not implement sharing — any external sharing would be an additional risk if added later.

Type: OpenClaw Skill Name: workbuddy-smart-learning Version: 1.0.0 The WorkBuddy Smart Learning System is a comprehensive framework for an AI agent to self-optimize through feedback loops, pattern recognition, and knowledge distillation. The bundle includes modules for collecting explicit user feedback (feedback.py), tracking implicit performance signals (signal_collector.py), profiling task complexity (task_profiler.py), and generating reusable YAML templates (knowledge_distiller.py). All data operations are confined to the local `.workbuddy` directory within the workspace, and the code lacks any indicators of data exfiltration, remote execution, or malicious prompt injection. Hardcoded Windows file paths in the test blocks (e.g., in learn.py) appear to be development artifacts rather than intentional malicious vectors.