Skill UI

A comprehensive guide to mastering structured concurrency, reactive streams, and state management in Kotlin. Covers advanced topics like Flow operators (debounce, retryWhen), StateFlow for UI state, and implementing robust asynchronous logic for Android and Kotlin Multiplatform projects. Essential for modern Android development.

This skill provides access to the Anthropic Claude Managed Agent runtime, which is a cloud-native, persistent environment for running complex, long-running, or asynchronous AI tasks. Unlike local WASM agents, the managed runtime provides a full container, persistent filesystem, and robust state management across multiple turns. It supports the entire agent lifecycle: creation, prompting, status inspection, event logging, and mandatory termination.

A comprehensive guide covering best practices for building and debugging Nuxt 4 applications. It details patterns for ensuring hydration safety, optimizing data fetching with `useFetch` and `useAsyncData`, managing complex routing rules, and implementing lazy loading for superior performance across SSR and client-side environments.

This guide provides comprehensive patterns for writing reliable and maintainable tests in Rust, adhering to the TDD methodology. It covers unit testing, integration testing, asynchronous programming with Tokio, property-based testing, mocking, and robust error/panic handling. Ideal for developers looking to elevate their Rust code quality and coverage.

A comprehensive guide to architectural patterns for building scalable, production-ready backend services using Java and Spring Boot. Covers essential topics including RESTful API design, layered architecture (Controller, Service, Repository), data persistence (JPA), caching, asynchronous processing, robust error handling, and middleware filtering.

Coordinate frontend/backend or service-to-service work through one authoritative machine-checkable contract (OpenAPI, AsyncAPI, Protobuf, or JSON Schema), with generated consumer types and contract-verified integration to prevent field drift and mock/production shape mismatch.

This SDK allows asynchronous Python programming to control a live web browser, simulating user interactions for web automation, testing, and data extraction. Users can navigate pages, locate elements, fill forms, click buttons, and capture snapshots of the current page's content. It enforces a 'perceive → act → verify' cycle, making it ideal for building robust web scrapers and end-to-end testing tools.

This skill is designed for deep forensic analysis of asynchronous processing chains, specifically focusing on 'drift'—behavioral or configuration differences between a synchronous request path and subsequent worker-executed tasks. Use it to trace payloads, inspect worker-only state, follow retry mechanisms, handle dead-letter queues, or connect enqueued items to eventual side effects (e.g., file writes, cache updates, emails). It is a specialized downstream tool, requiring prior orchestration context.

A specialized skill for analyzing and reproducing complex, timing-dependent bugs in concurrent systems. Use this to investigate race windows, ordering bugs, lock gaps, stale reads, or state inconsistencies where the final outcome depends critically on request timing or asynchronous execution order. Essential for deep security auditing and debugging of distributed transactions.

A specialized, downstream skill designed for forensic analysis within a confined sandbox environment, particularly for CTF challenges. It guides the user to inspect the full stack behavior, including API interactions, server routing, browser state (cookies, local storage), and asynchronous worker processes. Use this skill to trace complex, end-to-end request flows, debug authentication/session leaks, or diagnose discrepancies between frontend UI and backend enforcement.

This skill facilitates the extraction of population-scale (cohort-level) clinical text from Electronic Health Records (EHR) or FHIR data warehouses using the FHIR Bulk Data Access ($export) operation. It manages the asynchronous job kickoff, polling, and downloading of NDJSON files. The resulting data stream is designed to be fed in batches into OpenMed for mandatory de-identification and Named Entity Recognition (NER) analysis.

This specialized skill provides a deep workflow for reverse engineering stripped Go and Rust binaries. It guides the recovery of lost runtime metadata, including symbols, pclntab data, and panic strings. The process addresses language-specific challenges, such as Go's interface structures and Rust's complex async state machines, serving as a crucial complement to general decompilers like IDA or Ghidra.