Skill UI

This skill provides comprehensive guidance on leveraging d3.js (Data-Driven Documents) to create sophisticated, interactive, and publication-quality data visualizations. It covers core concepts like data binding, implementing various chart types (network graphs, geo-maps, etc.), handling complex transitions, and ensuring responsiveness across modern JavaScript frameworks (React, Vue, Vanilla JS). Learn the standard workflow for scale definition, axis creation, and drawing custom visual elements with fine-grained control.

Provides comprehensive guidance for developing robust, cross-platform Command Line Interface (CLI) applications. Covers the entire workflow from initial UX analysis and command design to implementation using popular frameworks (e.g., commander, click, cobra). Key features include advanced argument parsing, handling shell completions, displaying progress bars, and ensuring reliable terminal interactions across Windows, macOS, and Linux.

Provides comprehensive guidance on building robust evaluation frameworks for complex agent systems. It addresses the inherent challenges of non-determinism and multiple valid paths, enabling systematic performance testing, validating context engineering choices, and measuring continuous improvements across multiple quality dimensions (e.g., factual accuracy, tool efficiency).

A comprehensive guide for building professional, high-performance native iOS applications. Covers modern frameworks like SwiftUI and Swift 6, alongside deep expertise in UIKit, Core Data, networking (REST/GraphQL), performance profiling, and full App Store lifecycle management. Ideal for developers needing guidance on modern Apple ecosystem best practices.

Provides automated guidance for configuring learning rate schedulers during ML training, covering best practices, setup patterns, and framework-ready code snippets for PyTorch, TensorFlow, and Scikit-learn while validating against common standards.

Structured guidance for TAM/SAM/SOM calculations, combining top-down, bottom-up, and value-theory methods for startup market analysis and fundraising planning.

This skill provides comprehensive guidance on training Mixture of Experts (MoE) models, including architectures like Mixtral and DeepSeek-V3. It details techniques for achieving large-scale model capacity with significantly reduced computational costs (e.g., 5x reduction vs. dense models). Topics covered include top-k routing, load balancing, expert parallelism, and integration with frameworks like DeepSpeed and HuggingFace for efficient, resource-constrained training.

Provides language- and framework-specific security best practices guidance by loading reference documents, detecting vulnerabilities, and generating prioritized reports when asked.

This skill provides a dedicated lab environment and pattern guidance for exploring and utilizing advanced, complex capabilities within the Claude AI framework. Use it when you need a structured space to test, develop, and understand advanced AI workflows and powerful features.

Test Data Builder Guidance auto-activates when you ask about test data strategies, best practices, or configuration for automation frameworks, delivering step-by-step patterns, production-ready samples, and validation against common standards.

Automates guidance for configuring test retries in automation suites, walking through setup, best practices, and frameworks such as Jest or pytest so teams can stabilize flaky runs.

Provides an OWASP 2025-aligned vulnerability scanning mindset, supply chain defenses, attack surface mapping, and risk prioritization guidance with runtime scripts for automated validation of modern application security.