Total 30,738 skills, AI & Machine Learning has 4962 skills
Showing 12 of 4962 skills
Refactor Scikit-learn and machine learning code to improve maintainability, reproducibility, and adherence to best practices. This skill transforms working ML code into production-ready pipelines that prevent data leakage and ensure reproducible results. It addresses preprocessing outside pipelines, missing random_state parameters, improper cross-validation, and custom transformers not following sklearn API conventions. Implements proper Pipeline and ColumnTransformer patterns, systematic hyperparameter tuning, and appropriate evaluation metrics.
Refactor PyTorch code to improve maintainability, readability, and adherence to best practices. Identifies and fixes DRY violations, long functions, deep nesting, SRP violations, and opportunities for modular components. Applies PyTorch 2.x patterns including torch.compile optimization, Automatic Mixed Precision (AMP), optimized DataLoader configuration, modular nn.Module design, gradient checkpointing, CUDA memory management, PyTorch Lightning integration, custom Dataset classes, model factory patterns, weight initialization, and reproducibility patterns.
Guides Claude in creating well-structured SKILL.md files following best practices. Provides clear guidelines for naming, structure, and content organization to make skills easy to discover and execute.
Create custom tools using the @tool decorator for domain-specific agents. Use when building agent-specific tools, implementing MCP servers, or creating in-memory tools with the Agent SDK.
Expert guidance for writing Python code using the official Google GenAI SDK (google-genai) for Gemini API and Vertex AI. Use for text generation, multimodal inputs, reasoning, tools, and media generation.
Train custom TTS voices for Piper (ONNX format) using fine-tuning or from-scratch approaches. Use when creating new synthetic voices, fine-tuning existing Piper checkpoints, preparing audio datasets for TTS training, or deploying voice models to devices like Raspberry Pi or Home Assistant. Covers dataset preparation, Whisper-based validation, training configuration, and ONNX export.
Set up and manage local skills for automatic matching and invocation
Only responsible for answering questions, finding answers from documents and code, read-only, no code modification allowed.
Compare sentiment and blogger opinions between two stocks. Use when users want to analyze NVDA vs AMD, or any two tickers side by side.
Overview of the Blockbench MCP server tools, resources, and prompts. Use to understand the full MCP capability set, learn how tools work together, or when starting a new Blockbench project. Covers all domains (modeling, animation, texturing, PBR, UI, camera) and their MCP interfaces.
A guide to creating effective Skills. This Skill should be used when users want to create new Skills (or update existing ones) to extend Claude's capabilities, including expertise, workflows, or tool integrations.
Show available Kata skills, displaying the usage guide, explaining skill reference, or when the user asks for help with Kata. Triggers include "help", "show skills", "list skills", "what skills", "kata skills", and "usage guide".