Skill UI

This skill generates a comprehensive, minimal, and enforceable security policy document (Blue Book) for applications handling sensitive data. It structures requirements using MUST/SHOULD/CAN language, explicitly defining assumptions, scope, threat models, and security gates. It is essential for establishing clear security guardrails and ensuring compliance early in the development lifecycle.

Automates security policy creation within Security Advanced workflows by offering step-by-step guidance, best-practice templates, and validation of outputs for compliance, penetration testing, and threat modeling use cases.

This skill specializes in transforming theoretical threat models, risk assessments, and business context into concrete, actionable security requirements. It is essential for writing detailed security user stories, defining robust acceptance criteria, building comprehensive security test cases, and ensuring compliance requirement mapping. Use it when bridging the gap between identifying a vulnerability and specifying how the system must be secured.

This skill implements a robust, multi-layered security hardening process based on the Defense-in-Depth strategy and DevSecOps principles. It coordinates specialized agents to perform comprehensive security assessments (SAST, DAST, SBOM, Threat Modeling), identify critical vulnerabilities, and execute layered remediation. The process covers application code, backend APIs, frontend components, and mobile platforms, ensuring a resilient security posture across the entire development lifecycle.

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 guide details the expertise needed for a Senior Data Engineer. It covers building, optimizing, and governing scalable data pipelines and robust ETL/ELT systems using modern tools like Spark, Kafka, Airflow, and dbt. Includes decision frameworks for architecting data solutions (Batch vs Streaming, Lakehouse vs Warehouse) and implementing advanced data modeling patterns.

This central skill specializes in performing comprehensive threat modeling using STRIDE and calculating risk via DREAD scoring. It guides users through defining scope, identifying threats, and planning mitigations for new architectures. Crucially, it acts as a security router, directing specialized requests—such as pen-testing, incident response, cloud posture checks, and AI security reviews—to the appropriate dedicated skill.

Automates Sequelize model creation for backend development, offering step-by-step guidance, best practices, and production-ready code/config validation when working with Node.js, Python, Go, databases, caching, messaging, and microservices.

Automates SIEM rule generation within advanced security workflows, guiding through industry best practices, compliance checks, and threat modeling to deliver production-ready configurations verified against common standards.

This skill simulates a complete, multi-agent software development lifecycle following the principles of Agile and Scrum. It guides the project through six distinct, iterative phases: Architectural Planning, Parallel Implementation, Comprehensive Testing (Unit/E2E), Review, and Finalization. The process uses a convergent diffusion model, refining specifications and resolving conflicts across multiple specialized agents until the project converges and is deemed complete.

This skill provides a structured approach to systematically identify security threats by applying the STRIDE methodology (Spoofing, Tampering, Repudiation, Information Disclosure, Denial of Service, Elevation of Privilege). It is crucial for conducting thorough threat modeling sessions, analyzing system architectures, reviewing security design decisions, and creating robust security documentation for compliance and auditing purposes.

This pattern demonstrates how to build a robust, thread-safe data persistence layer in Swift using the 'actor' model. It combines fast in-memory caching with reliable file-backed storage, automatically eliminating data races and the need for manual locks. Ideal for offline-first applications and managing shared mutable state in modern Swift concurrency.