Skill UI

Provides implementation patterns and reference architecture for building advanced AI voice agents and automating complex phone call workflows using the Retell AI SDK. This skill is designed for developers requiring robust voice interaction, real-time telephony integration, and comprehensive conversational AI capabilities in their applications.

Execute controlled chaos experiments to proactively test system resilience, fault tolerance, and recovery capabilities. This toolkit simulates real-world failures, such as network latency, service crashes, resource exhaustion, and dependency outages, ensuring that microservices degrade gracefully and recover automatically. It is essential for modern distributed systems validation.

This skill simulates an expert cybersecurity auditor specializing in DevSecOps methodologies and comprehensive security assurance. It guides users through running detailed security audits, performing threat modeling, and assessing vulnerabilities (e.g., IDOR). Capabilities cover SAST, DAST, cloud security posture, zero-trust architectures, and compliance adherence to major frameworks like GDPR, HIPAA, and PCI-DSS, ensuring security is integrated throughout the entire SDLC.

Delivers repository-grounded AppSec threat models that map components, boundaries, assets, entry points, and attacker capabilities to abuse paths, along with prioritized mitigations tailored to codebase evidence and explicit assumptions.

This comprehensive toolkit provides end-to-end DevOps automation capabilities. It scaffolds CI/CD pipelines (GitHub Actions, CircleCI), generates robust Infrastructure as Code (IaC) modules using Terraform for major clouds (AWS, GCP, Azure), and manages complex Kubernetes deployments (Blue/Green, Rolling). Ideal for automating infrastructure setup, application deployment, and drift management in multi-cloud environments.

Guides building, tuning, and validating production Apache Spark jobs, covering DataFrame/RDD choices, partitioning, broadcast joins, skew handling, caching, and cluster configuration for big data pipelines.

This guide provides advanced patterns and best practices for optimizing Apache Spark jobs. It covers critical areas like effective partitioning, memory tuning, minimizing data skew, and optimizing different types of joins (broadcast, bucket). Use this when troubleshooting slow, large-scale data processing workflows or needing to scale Spark pipelines efficiently and reliably.

This tool collects a comprehensive, redacted diagnostic bundle from a Supabase project. It systematically tests connectivity, authentication (Auth), Realtime capabilities, Storage buckets, and Row-Level Security (RLS) policies. The resulting archive is designed for sharing with support teams to accelerate troubleshooting of complex issues like connection failures or misconfigurations.

This comprehensive guide details the complete workflow for setting up and maintaining a local Supabase development environment. It utilizes Docker and the Supabase CLI to run the entire full-stack service (Postgres, Auth, Storage, etc.) locally. It guides developers through initialization, creating version-controlled migrations using diff, seeding data, and performing clean database resets, ensuring local iteration accurately mirrors production capabilities.

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.

This skill provides comprehensive capabilities for web searching, content extraction, and web crawling using the Tavily API. It is ideal for tasks requiring up-to-date information retrieval, deep content scraping from specific URLs, or comprehensive website crawling for research purposes, making it a powerful research augmentation tool.

This skill acts as an expert test automation specialist, capable of analyzing source code across multiple languages (Python, JavaScript, TypeScript, etc.). It generates comprehensive, maintainable unit test suites using best practices, maximizing code coverage, and specifically targeting edge cases and exception handling. Use it to ensure high code quality and structural consistency.