AI/ML

A comprehensive Java SDK skill for Amazon Bedrock with practical patterns for model invocation, streaming, embeddings, and Spring Boot integration, though security guidance could be enhanced.

Provides guidance for using scikit-learn to build classification, regression, and clustering models. Includes code examples for data splitting, preprocessing, training, and evaluation. Covers common pitfalls like data leakage and offers algorithm selection cheat sheets.

A comprehensive skill for implementing RAG systems with LangChain4j, providing practical code examples, configuration patterns, and best practices for Java developers building knowledge-enhanced AI applications.

This skill fetches weekly trending programming models from OpenRouter rankings, providing model IDs, context windows, pricing, and usage stats. It helps developers select appropriate AI models for code review tasks and cost optimization. The script outputs structured JSON with metadata and summary statistics.

A comprehensive skill for building type-safe, declarative AI services in Java using LangChain4j patterns, offering excellent practicality and maintainability for Java developers implementing AI features.

Provides structured templates and best practices for PyTorch Lightning development, covering LightningModule organization, Trainer configuration, data pipelines, distributed training strategies, and common debugging patterns.

This skill provides a structured guide to Chain-of-Thought prompting and its variants for improving LLM reasoning. It includes decision matrices, prompt templates, and research-backed patterns for techniques like Zero-shot CoT, Self-Consistency, Tree of Thoughts, and ReAct. The documentation helps users select appropriate methods for different reasoning tasks.

Provides guidance for using Stable Baselines3, a PyTorch RL library with PPO, SAC, DQN algorithms. Covers training agents, custom environments, vectorized envs, callbacks, and evaluation. Includes ready-to-use scripts for common RL workflows and troubleshooting tips.

A CLI tool for generating images using Google's Gemini 3 Pro API. It provides a straightforward interface for text-to-image creation, image editing, and applying styles via markdown templates. Handles aspect ratios, retries on errors, and includes clear error codes.

Provides vector search capabilities for AgentDB with HNSW indexing and quantization. Supports CLI operations, API integration, and MCP server for Claude. Includes benchmarks showing 150x-12,500x speed improvements over traditional methods.

This skill provides direct access to Python's statsmodels library for statistical modeling. It covers OLS, logistic regression, ARIMA, GLM, and hypothesis testing with code examples. The documentation includes model selection guidance, formula API usage, and common applications like marketing response prediction.

This skill provides a complete workflow for single-cell RNA-seq analysis using Scanpy, covering data loading, QC, normalization, dimensionality reduction, clustering, and visualization. It includes practical code examples for common tasks and publication-quality figure customization.