scikit-learn

完整的Claude插件生态系统:504个专业代理、313个开发命令、16个工作流、39个钩子、56个MCP服务器、18个输出样式，专业化分类，即装即用。额外提供151个Agent Skills知识库(独立管理)

Simplifies neurophysiological signal processing and analysis with Python, enabling researchers to easily clean, extract features, and visualize EEG, ECG, and other biosignals.

Parallelize and scale data processing workflows with distributed computing, enabling efficient large-scale analytics on multi-core and cluster environments.

Simplifies probabilistic programming with PyMC, enabling Bayesian statistical modeling, inference, and complex model design with intuitive Python workflows.

Generates and manipulates digital canvas designs with advanced drawing, layering, and styling capabilities for creative and technical projects.

Generates molecular feature descriptors and representations for machine learning models in computational chemistry and drug discovery.

Automates laboratory robotic workflows by providing Python interfaces for controlling liquid handling robots and lab automation equipment.

Validates and cross-checks task requirements, inputs, and potential outcomes before finalizing work to ensure accuracy and prevent errors.

Automatically tracks and recalls context from previous interactions, enabling seamless, context-aware conversations across multiple chat sessions.

Helps researchers craft precise, structured academic papers with advanced language models, improving clarity, grammar, and citation formatting