Подборка installable AI Agent Skills для developer workflow в automation для Claude Code, Cursor и Windsurf.
Эта страница посвящена практической автоматизации workflow для реальных инженерных команд. Инструменты помогают ИИ-агентам и разработчикам автоматизировать повторяющиеся шаги, связывать сервисы и поддерживать стабильное выполнение от прототипа до продакшена. MCP может использоваться как слой интеграции, но ключевая ценность — надежный результат разработки.
This collection should not trap users in comparison mode or pretend to install the whole collection. Its job is to narrow the shortlist to one skill, then send the next click into installation, validation, and rollout. Installation happens on the skill path.
Move from automation-tool comparison into the install flow, validation checklist, and first command path before expanding further.
Open the Install PathOnce the install path is clear, move into the solution, CLI, or editorial surface that best matches this collection. That keeps platform, framework, and operations demand narrowing into a more verifiable high-intent journey.
A use-case page for users searching for repeatable automation patterns instead of one-off tools.
Workflow automation demand is easier to satisfy with curated intent clusters than with flat directory coverage.
A solution page for teams turning SOPs, handoffs, and operations into repeatable AI-assisted execution paths.
Operational intent deserves a stronger bridge than generic tooling lists can provide.
Reviewed on 2026-04-17 against workflow automation fit, install clarity, operator handoff, and production usefulness. This page now acts as an installation-first gateway instead of a generic automation list.
We prioritize this page because automation-intent users should move quickly from comparison into installation and validation. That path is stronger for recovery than trapping them in broad tooling research.
Use this page when you need one automation toolchain that can move from prototype into repeatable team execution.
Use the collection as an editorial filter when you need automation tools that can be rolled out without excessive operator ambiguity.
Confirm what the CLI writes and how sync behaves after the install path is clear.
Use the workflow solution page after installation to decide how the automation tool should fit into the delivery system.
Обзор бэкенд-кода - это процесс анализа кода для выявления проблем качества, безопасности и поддержки.
The component-refactoring skill simplifies high-complexity React components, improving code quality and reducing maintenance efforts for developers. It utilizes patterns and workflows to refactor components, making them more efficient and easier to understand.
Generate Vitest + React Testing Library tests for Dify frontend components, hooks, and utilities. Triggers on testing, spec files, coverage, Vitest, RTL, unit tests, integration tests, or write/review test requests.
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.
This frontend-code-review skill reviews frontend files, such as .tsx, .ts, and .js, and applies a checklist to ensure code quality, performance, and business logic, helping developers and teams maintain high standards.
Frontend-запрос и мутация - это шаблон реализации для сохранения контрактов как единственного источника правды
Навык агента ИИ - это набор инструкций, которые учат агента выполнять конкретную задачу.
Creates GitHub pull requests with properly formatted titles that pass the check-pr-title CI validation. Use when creating PRs, submitting changes for review, or when the user says /pr or asks to create a pull request.
Fetch and display the full transcript from a Loom video URL. Use when the user wants to get or read a Loom transcript.
Reproduce a bug from a Linear ticket with a failing test. Expects the full ticket context (title, description, comments) to be provided as input.
Навык линейного анализа проблем является мощным инструментом для автоматизации рабочих процессов, позволяющим интегрировать инструменты seperti Linear MCP и GitHub CLI для более глубокого анализа.
Навык создания проблем в GitHub позволяет разработчикам создавать проблемы с аутентификацией для улучшения сотрудничества и управления проектами.
Навык ИИ Агента n8n-conventions предоставляет быструю справку по конвенциям n8n, помогая разработать рабочие процессы автоматизации с Claude Code и другими помощниками кодирования ИИ.
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El desarrollo basado en especificaciones permite una integración más eficiente de APIs y flujos de datos
Detects code smells, anti-patterns, and debugging issues. Use when: fixing bugs, reviewing code quality, or refactoring.
Guides PRD, ADR, Design Doc, and Work Plan creation. Use when: planning features, writing specs, or creating technical documents.
Applies TDD process, test quality criteria, and mock guidelines. Use when: writing unit tests, using mocks, or reviewing test quality.
Sync scripts to SuperOps - commits changes and pushes to SuperOps platform
Do not reset back to the generic directory. Move sideways through these adjacent high-intent collections to narrow the shortlist toward the install path that best matches your team.
A high-trust collection that lets the site lead with official and strongly verified ecosystems instead of random long-tail repos.
Trusted-brand collections are the fastest way to rebuild authority after pruning.
A workflow-first collection that explains why related skills belong together and what job they solve.
Workflow collections add first-party judgment that generic skill detail pages struggle to communicate.
A platform-specific collection for one of the clearest demand clusters in the product ecosystem.
Platform collections let the site recover with narrower, more trustworthy topical intent.
A clean surface for editor-specific demand with explicit workflow intent.
Editor-specific demand should land on curated surfaces, not random repo coverage.
This collection should not keep users browsing forever. These three questions explain how to shortlist, install, and validate the next step.
Эти подборки построены вокруг автоматизации рабочих процессов, документов, данных и переиспользуемых стеков навыков.
Каталог лучше подходит для прямого поиска, а подборки помогают найти взаимодополняющие навыки, объединённые вокруг рабочего процесса.
Да. Навыки в этих подборках обычно работают в Claude Code, Cursor, Windsurf и других поддерживаемых средах через единый процесс установки.
These are the supporting surfaces for this collection after the install direction is clear and the primary next paths have already narrowed the decision.
A workflow-first collection that explains why related skills belong together and what job they solve.
Workflow collections add first-party judgment that generic skill detail pages struggle to communicate.
A high-trust collection that lets the site lead with official and strongly verified ecosystems instead of random long-tail repos.
Trusted-brand collections are the fastest way to rebuild authority after pruning.