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.

Bir Skill ekle

Skills

19

Kategoriler

9

Uyumlu araçlar

5

Katkıda bulunanlar

1

19 Skill'den 1–19 arası gösteriliyor

Tool Call Testingİleri

Tests AI agent tool use with realistic fixtures, malformed inputs, permission boundaries, deterministic assertions, and recovery checks for failed or partially completed actions.

3 model
LLM Output Evaluationİleri

Defines repeatable quality evaluation for LLM outputs using representative datasets, scoring rubrics, model-graded checks, human review sampling, and regression thresholds.

3 model
Agent Evaluation Designİleri

Gerçekçi uçtan uca senaryolarda görev başarısını, araç kullanım doğruluğunu, dayanaklılığı, gecikmeyi, maliyeti ve güvenli toparlanmayı ölçen yeniden üretilebilir AI agent değerlendirmeleri oluşturur.

3 model
Prompt Regression TestingOrta

Builds regression suites for prompts and agent instructions so teams can detect quality, safety, format, and tool-selection regressions before deploying changes.

3 model
Accessibility AuditOrta

Ürün arayüzlerini semantik yapı, klavye kullanımı, odak davranışı, renk kontrastı, ekran okuyucular ve formlar dahil olmak üzere pratik erişilebilirlik gereksinimlerine göre denetler.

3 model
Browser Test Debuggingİleri

Diagnoses failing browser and end-to-end tests by correlating assertions, traces, screenshots, network activity, timing, and application state into reproducible fixes.

3 model
Visual Regression Testerİleri

Designs and implements visual regression testing for web UIs. Recommends a tooling approach (Playwright snapshots, Storybook + a diffing service, or a dedicated platform), writes screenshot tests with stable selectors and masked dynamic regions, sets sensible diff thresholds, and integrates the suite into CI with baseline management to reduce flaky failures.

4 model
Test Plan WriterOrta

Produces structured test plans for features and releases. Defines scope and objectives, derives test cases from requirements and acceptance criteria, covers functional, edge, negative, performance, and accessibility cases, sets entry/exit criteria, and maps risk to test priority. Outputs a clear plan with a traceability matrix linking tests to requirements.

4 model
BDD Scenario WriterOrta

Translates requirements and user stories into behavior-driven development scenarios in Gherkin. Writes clear Given/When/Then steps, covers happy paths, edge cases, and negative cases, uses scenario outlines with examples for data-driven tests, and keeps steps declarative and reusable. Optionally scaffolds step definitions for Cucumber or Behave.

4 model
Flaky Test DetectorOrta

Diagnoses and fixes flaky tests by analyzing test code and CI failure history for common sources of nondeterminism such as time and timezone dependence, order dependence, shared mutable state, race conditions, and unmocked network calls. Proposes targeted fixes and quarantine strategies to keep the suite trustworthy.

4 model
Contract Test Generatorİleri

Generates consumer-driven contract tests between services so that API providers and consumers stay compatible as they evolve independently. Produces Pact-style contracts, provider verification stubs, and CI wiring, and flags breaking changes before they reach production.

3 model
Property-Based Test Generatorİleri

Generates property-based tests that assert invariants across randomly generated inputs using frameworks like Hypothesis, fast-check, or jqwik. Identifies properties (round-trip, idempotence, invariants, oracle comparison), defines generators and shrinking, and sets up stateful testing for complex APIs. Surfaces edge cases that example-based tests miss.

4 model
E2E Test Scenario WriterOrta

Writes end-to-end UI tests with Playwright or Cypress that mirror real user journeys. Covers resilient selectors (roles/test-ids), network stubbing, auth setup, fixtures, waiting strategies that avoid flakiness, visual and accessibility assertions, and CI integration. Produces maintainable specs and a page-object structure.

4 model
Mutation Testing Advisorİleri

Sets up and interprets mutation testing to measure real test-suite effectiveness beyond line coverage. Configures tools like Stryker, PIT, or mutmut, explains surviving mutants, recommends targeted tests to kill them, and tunes performance for CI. Helps teams find tests that assert nothing and coverage that lies.

4 model
API Mock ServerOrta

Generates mock API servers and stubbed responses from OpenAPI specs, sample payloads, or natural-language descriptions. Produces realistic fixture data, configurable latency and error scenarios, and ready-to-run mock servers using tools like Prism, MSW, WireMock, or json-server so frontend and integration tests can proceed without the real backend.

3 model
API Load Testing GeneratorOrta

Generates comprehensive load testing scripts and configurations for APIs. Supports k6, Locust, Artillery, and JMeter formats. Creates realistic traffic patterns, ramp-up scenarios, and threshold definitions. Includes analysis templates for identifying bottlenecks and capacity planning.

3 model
Test Data GeneratorBaşlangıç

Generates realistic test data, fixtures, and seed files for databases and APIs. Creates data that respects constraints (foreign keys, unique fields, valid formats) and covers edge cases. Supports JSON, SQL, CSV, and factory patterns.

4 model
Unit Test GenerationOrta

Generates comprehensive unit tests for existing code, covering happy paths, edge cases, error conditions, and boundary values. Follows testing best practices including the test pyramid, DAMP over DRY, and the Arrange-Act-Assert pattern. Adapts to the project's existing test framework and conventions.

4 model
Accessibility ReviewOrta

Reviews web interfaces for WCAG 2.1 AA compliance. Identifies accessibility barriers including missing ARIA attributes, keyboard navigation issues, color contrast problems, and screen reader incompatibilities. Provides remediation code with proper semantic HTML.

3 model

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.

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