frontend-query-mutation
[ Избранное ]Frontend-запрос и мутация - это шаблон реализации для сохранения контрактов как единственного источника правды
Просматривайте и устанавливайте тысячи навыков AI Agent в каталоге Killer-Skills. Совместимо с Claude Code, Windsurf, Cursor и другими.
This directory brings installable AI Agent skills into one place so you can filter by search, category, topic, and official source, then install them directly into Claude Code, Cursor, Windsurf, and other supported environments.
Organic recovery should flow through fewer, stronger, first-party entry points instead of a flat bulk-skill corpus.
Curated collection pages carry clearer topical scope, stronger first-party framing, and safer canonical signals than bulk skill listings.
Installation docs prove the site offers first-party setup guidance, not just discovery wrappers.
A workflow-first collection that explains why related skills belong together and what job they solve.
A platform-specific collection for one of the clearest demand clusters in the product ecosystem.
A platform collection that turns IDE demand into a stronger curated hub.
A Gemini-specific collection that turns compatibility research into a curated install path for real delivery teams.
A Python engineering collection built for teams choosing installable workflow helpers instead of browsing raw packages.
A typed-development collection that helps product teams shortlist TypeScript workflow tools with clear next steps.
Frontend-запрос и мутация - это шаблон реализации для сохранения контрактов как единственного источника правды
Guide for implementing oRPC contract-first API patterns in Dify frontend. Trigger when creating or updating contracts in web/contract, wiring router composition, integrating TanStack Query with typed contracts, migrating legacy service calls to oRPC, or deciding whether to call queryOptions directly vs extracting a helper or use-* hook in web/service.
Навык написания кода - это подход к разработке, ориентированный на тестирование, для документации процессов, позволяющий создавать повторно используемые и эффективные навыки
Параллельное dispatching агентов позволяет эффективно решать независимые проблемы, повышая производительность и сокращая время решения.
Use when starting feature work that needs isolation from current workspace or before executing implementation plans - creates isolated git worktrees with smart directory selection and safety verification
Subagent-driven development automates independent tasks using fresh subagents, ensuring high-quality results and fast iteration for developers. It streamlines AI coding workflows.
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes
Use when implementing any feature or bugfix, before writing implementation code
Use when you have a spec or requirements for a multi-step task, before touching code
Use when starting any conversation - establishes how to find and use skills, requiring Skill tool invocation before ANY response including clarifying questions
Навык верификации до завершения является важным для ИИ агента, обеспечивающим точность и надежность результатов.
You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.