Skill UI

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.

A comprehensive toolset for the full backend development lifecycle. This suite enables developers to scaffold API routes from OpenAPI specifications, manage complex database migrations and optimization (PostgreSQL), and perform rigorous load/performance testing. It supports building robust microservices, securing REST APIs, and ensuring system scalability.

This skill guides developers through major Sentry SDK version upgrades (e.g., v7 to v8, Python v1 to v2). It helps detect deprecated APIs, runs automated codemods (like @sentry/migr8), and applies manual fixes for breaking changes, ensuring a smooth transition while maintaining robust error tracking and observability.

Serve production-grade LLM APIs with vLLM, leveraging PagedAttention, continuous batching, quantization, and tensor parallelism to maximize throughput while keeping latency, GPU usage, and scalability under control for OpenAI-compatible deployments.

A specialized methodology for reviewing APIs, configuration schemas, and interfaces to identify 'footguns'—design choices where the path of least resistance leads to insecurity. This analysis focuses on making secure usage the default, covering topics like dangerous defaults, primitive vs. semantic type safety, and insecure algorithm selection. It is crucial for architects and reviewers to prevent developer misuse at the design level.

A comprehensive developer reference covering the full spectrum of Shopify development, including Liquid templating, OS 2.0 architecture, GraphQL APIs (Admin and Storefront), and modern headless solutions using Hydrogen. This guide assists in building advanced themes, custom apps, implementing serverless business logic via Functions, and optimizing performance for modern e-commerce storefronts.

This guide details setting up a robust CI integration pipeline for Speak language learning platform integrations. It utilizes GitHub Actions with mocked API testing and audio validation to ensure code reliability and functional correctness before deployment. Ideal for developers managing complex language learning products and APIs.

This guide provides a comprehensive deep dive for migrating language learning platforms, covering everything from importing student progress to transitioning from legacy speech APIs. It details configuration using modern SDKs, integrating services like OpenAI's GPT-4o and Whisper, and includes verification steps. It is essential for managing complex platform migrations and ensuring a smooth operational transition.

This guide provides robust patterns for managing external API rate limits, specifically detailing the implementation of exponential backoff, request queuing, and throttling strategies. It uses TypeScript examples to ensure stable and reliable API interactions. Use this when building production-grade applications that require frequent, high-volume calls to rate-limited services, such as language learning APIs.

Guides Spring Boot 3.x engineers through configuration scaffolds, REST controllers, Spring Security 6 authentication flows, Spring Data JPA repositories, and reactive WebFlux endpoints, making it easier to build microservices and Java REST APIs.

A comprehensive guide for migrating and upgrading the Supabase SDK (JS/TS and Python) and CLI. This tool detects breaking changes, covers major version jumps (e.g., v1 to v2), and provides automated code migration patterns for Auth, Realtime, and Storage APIs. Use this when updating your project to a new Supabase version or when encountering API deprecations.

This comprehensive guide demonstrates how to achieve highly testable Swift code using protocol-based dependency injection. By abstracting external concerns—such as file systems, networking, and external APIs—into small, focused protocols, developers can write deterministic unit tests that mock side effects and error paths, ensuring robust architecture across different environments (App, Test, Preview).