Skill UI

A comprehensive guide detailing advanced techniques for attacking Microsoft Active Directory (AD) environments. It covers the entire red team lifecycle, including reconnaissance (BloodHound, PowerView), credential harvesting (Mimikatz, AS-REP Roasting), and critical attacks such as Kerberos exploitation, Pass-the-Ticket/Hash, and NTLM relay attacks. Essential for penetration testing and defensive validation.

A specialized skill for architecting, building, and productionizing complex Agent Development Kit (ADK) agents and multi-agent systems. This process emphasizes best practices, including clean module structure, robust tool integration, comprehensive regression testing, and deployment automation for reliable, shippable AI solutions. Use this when requiring the creation of structured, enterprise-grade agent code.

A comprehensive framework for rigorously testing and benchmarking LLM agents. It moves beyond simple pass/fail checks to assess complex behaviors, reliability metrics, and capability consistency across multiple runs. Ideal for production monitoring and identifying subtle failure modes in advanced AI agents.

A systematic workflow designed to significantly improve the reliability and performance of existing AI agents. It covers detailed performance analysis, including gathering metrics (e.g., task success rate, latency), classifying failure modes, and advanced prompt engineering techniques (like Chain-of-Thought and Constitutional AI). The process culminates in structured A/B testing and controlled deployment, ensuring measurable, robust improvements.

A comprehensive guide to building production-ready Apache Airflow Directed Acyclic Graphs (DAGs). This skill covers best practices for operators, sensors, testing, deployment, and designing robust data pipelines. Use this when orchestrating complex workflows, managing ETL processes, or ensuring reliable batch job execution in a production environment.

This advanced skill details dual-use security techniques for analyzing protected binaries, conducting malware analysis, and performing authorized penetration testing. It strictly mandates that users confirm explicit written authorization, adhere to defined scope, and ensure legal compliance (e.g., CFAA, DMCA). Use cases include CTF competitions, academic research, and internal security auditing, emphasizing defensive recommendations and evidence preservation.

This advanced skill details dual-use security techniques for analyzing protected binaries, conducting malware analysis, and performing authorized penetration testing. It strictly mandates that users confirm explicit written authorization, adhere to defined scope, and ensure legal compliance (e.g., CFAA, DMCA). Use cases include CTF competitions, academic research, and internal security auditing, emphasizing defensive recommendations and evidence preservation.

A comprehensive workflow designed for creating, maintaining, and deploying high-quality API documentation. This process guides users through several phases, including API discovery, generating OpenAPI specifications (Swagger), writing detailed developer guides, adding functional code examples, setting up interactive testing interfaces, and structuring the final documentation site.

A comprehensive workflow designed for creating, maintaining, and deploying high-quality API documentation. This process guides users through several phases, including API discovery, generating OpenAPI specifications (Swagger), writing detailed developer guides, adding functional code examples, setting up interactive testing interfaces, and structuring the final documentation site.

Configures a robust CI/CD pipeline for Apollo.io integrations using GitHub Actions. It implements multi-stage testing, including unit tests (using MSW mocks for zero API calls), live integration tests (gated to main branch), and secret scanning. Ensures reliable and safe deployment practices for SaaS applications.

This skill provides a minimal working example for integrating with the Apollo.io API. It demonstrates the three core operations: searching for people, enriching individual contacts (to get emails/phones), and enriching entire organizations. It is ideal for developers starting a new Apollo integration, testing API setup, or learning basic data enrichment patterns.

This comprehensive guide sets up a robust and isolated local development environment for Apollo.io integrations. It covers essential steps including configuring sandbox API keys, implementing a Mock Service Worker (MSW) for reliable offline API mocking, setting up detailed request logging, and configuring Vitest for efficient local testing. Ideal for developers building and debugging complex, API-dependent features.