Skills
AI agent Skills için açık kayıt: önerilen modeller, örnek prompt'lar ve uyumlu araçlar içeren yapılandırılmış prompt'lar ve iş akışları.
Bazı açıklamalar otomatik çevrilmiş pilot içeriklerdir ve henüz editör tarafından incelenmemiştir.
Skills
21
Kategoriler
9
Uyumlu araçlar
5
Katkıda bulunanlar
1
Converts a design specification or screenshot into accessible, responsive production UI while preserving component boundaries, design tokens, semantic structure, and states.
Designs reliable JSON and typed outputs for LLM features, including schemas, validation, recovery paths, versioning, examples, and contracts for downstream consumers.
Bilinmeyen bir repository'yi mimari, kurallar, yerel kurulum, önemli çalışma yolları ve güvenli ilk değişiklikler hakkında kısa bir mühendislik rehberine dönüştürür.
Sets up and maintains Git hooks for a repository. Recommends a manager (Husky, Lefthook, or pre-commit), wires up pre-commit and commit-msg hooks for linting, formatting, type checks, secret scanning, and conventional-commit validation, and keeps hooks fast with staged-file filtering. Produces config plus a short contributor guide.
Builds robust webhook producers and consumers. Covers signature verification, idempotency keys, retry with exponential backoff, dead-letter handling, event ordering, and replay endpoints, and generates handler code plus tests so integrations survive duplicates and outages.
Adds clear, accurate inline comments and API doc blocks to existing code without changing behavior. Generates docstrings and structured comments (JSDoc, Google/NumPy style, Javadoc, Rustdoc) that explain intent, parameters, return values, side effects, and edge cases, while avoiding noisy comments that merely restate the code.
Generates mobile application prototypes and implementations for iOS and Android. Creates SwiftUI views, Jetpack Compose layouts, and React Native components from descriptions or wireframe images. Handles navigation patterns, state management, and platform-specific design guidelines.
Analyzes and resolves git merge conflicts by understanding the intent of both sides. Examines the conflict markers, surrounding context, and commit history to produce a correct merged result that preserves both changes without breaking functionality.
Generates complete OpenAPI 3.1 specifications from API descriptions, existing code, or route definitions. Includes request/response schemas, authentication, error responses, examples, and server configurations. Produces valid YAML ready for Swagger UI.
Generates production-ready React components with TypeScript, proper props interfaces, accessibility attributes, responsive design, and test files. Follows modern patterns including Server Components, Suspense boundaries, and composition over inheritance.
Generates TypeScript type definitions from various sources — JSON data, API responses, database schemas, or plain descriptions. Produces strict types with proper generics, utility types, discriminated unions, and JSDoc comments.
Designs and implements comprehensive error handling for APIs. Covers error response formats (RFC 7807 Problem Details), HTTP status code selection, error logging strategies, retry logic, and client-friendly error messages with proper i18n support.
Explains complex code in plain language at the requested level of detail. Breaks down algorithms, design patterns, and architecture decisions. Adapts explanation depth from high-level overview to line-by-line walkthrough based on audience.
Guides systematic code refactoring while preserving exact behavior. Identifies code smells, suggests appropriate refactoring patterns, and executes transformations incrementally with verification at each step. Follows Chesterton's Fence principle — understands why code exists before changing it.
Identifies and resolves performance bottlenecks in code and systems. Covers algorithmic complexity analysis, memory optimization, caching strategies, database query tuning, and frontend performance (Core Web Vitals). Follows a measure-first approach.
Designs, optimizes, and iterates on prompts for LLM applications. Covers system prompt design, few-shot examples, chain-of-thought reasoning, output formatting, and prompt testing strategies. Helps build reliable AI-powered features.
Systematic debugging workflow that helps identify, isolate, and fix bugs. Follows a structured approach: reproduce, localize, reduce, fix, guard. Analyzes error messages, stack traces, and logs to pinpoint root causes rather than symptoms.
Contract-first yaklaşımıyla RESTful ve GraphQL API'leri tasarlar. Endpoint yapısını, istek ve yanıt şemalarını, hata yönetimini, sürümlemeyi, pagination'ı, kimlik doğrulamayı ve rate limiting'i kapsar. OpenAPI/Swagger spesifikasyonları ve uygulama iskeletleri üretir.
Builds, explains, and tests regular expressions from natural language descriptions. Supports multiple regex flavors (PCRE, JavaScript, Python, Go). Provides step-by-step breakdowns, test cases, and performance considerations for complex patterns.
Kod kalitesi, olası hatalar, performans, güvenlik açıkları ve stil ihlalleri hakkında uygulanabilir öneriler sunan otomatik kod incelemesi. Değişiklikleri kıdemli bir mühendisin titizliğiyle analiz eder ve kod örnekleriyle somut düzeltmeler önerir.
Translates code between programming languages while preserving logic, idioms, and best practices of the target language. Handles differences in type systems, error handling, concurrency models, and standard library APIs. Produces idiomatic target code, not line-by-line transliteration.
Skills ve MCP sunucuları
aralarındaki fark nedir?Skills“ne yapılacağı”
Bir Skill; talimatları, örnek prompt'u ve önerilen modelleri paketleyerek agent'ın görevi tutarlı şekilde yapmasını sağlar. Skills yeni bağlantılar değil, bilgi ekler.
MCP sunucuları“nasıl bağlanılacağı”
Bir MCP sunucusu, gerçek sistemlere (veritabanları, API'ler ve dosyalar) bir taşıma yöntemi üzerinden bağlanarak agent'a yeni yetenekler kazandırır. MCP görev talimatları değil, bağlantılar ve eylemler ekler.
Kısa kural: modelin bir görevi iyi yapması gerekiyorsa Skill, bir araca veya sisteme erişmesi gerekiyorsa MCP sunucusu kullanın. Birlikte çalışabilirler; Skill, MCP sunucusunun sunduğu araçlardan yararlanabilir.
Faydalı bir Skill mi geliştirdiniz?
Bir SKILL.md gönderin; açık kaynaklıdır ve topluluk tarafından sürdürülür.