Skill UI

This skill provides a comprehensive setup for Customer.io CI/CD pipelines. It includes GitHub Actions workflows for running unit and integration tests, managing test fixtures, and implementing pre-commit hooks. It ensures robust, automated validation of Customer.io code changes, providing a reliable quality gate during the development and deployment lifecycle.

Automates database-focused test work by offering best-practice guidance, fixtures, and configurations for unit, integration, and mocking scenarios in test automation workflows.

This guide establishes a robust local development environment for Deepgram integrations. It covers setting up test fixtures using sample audio, mocking API responses for isolated unit testing, configuring watch-mode development servers, and running comprehensive unit and integration tests using Vitest. Use this setup when initiating a Deepgram feature or requiring a reliable, fast development cycle.

This guide details a complete local development workflow for integrating with Fireflies.ai GraphQL. It outlines setting up the project structure, recording real API responses as mock fixtures, creating a custom mock client, and writing robust unit tests. Use this methodology to ensure fast, reliable, and isolated development cycles without dependency on live APIs or worrying about rate limits.

Automates fixture generator tasks for test automation, offering best-practice guidance, ready-to-use code/configuration, and validation for unit, integration, and mocking scenarios.

Generates realistic users, products, orders, or schema-driven data via the test-data-generator plugin for populating test databases, simulating user behavior, and creating fixtures for automated or API testing.

A comprehensive guide and implementation for setting up a fast, cost-effective local development loop for the Perplexity Sonar API. It includes generating type-safe client wrappers, utilizing fixtures for reliable mocking, and establishing a complete test suite with hot-reloading capabilities. This ensures stable development and manages high API call costs during iteration.

Provides a comprehensive pytest-focused testing strategy for Python applications, covering TDD cycles, fixtures, parametrization, coverage tools, and test infrastructure setup for reliable suites.

This comprehensive guide provides robust strategies for testing Python code using industry best practices. It covers essential techniques like pytest, fixtures, mocking, parameterization, and implementing Test-Driven Development (TDD). Use this skill when writing unit tests, setting up complex test suites, performing integration testing, or establishing continuous testing infrastructure in CI/CD pipelines.

A comprehensive guide and setup for building a fast, reliable local development workflow for language learning applications. It includes setting up mock tutor responses for offline testing, generating audio test fixtures using TTS, and implementing a debug mode for detailed pronunciation scoring analysis. Ideal for engineers setting up a new Speak-based integration or refining existing test pipelines.

This skill automates the creation of comprehensive test suites for any codebase. Utilizing advanced AI capabilities, it analyzes function signatures, automatically identifies potential edge cases, generates meaningful assertions, and produces necessary mock data and fixture files. It is essential for developers needing robust unit tests, increasing code coverage, and adopting Test-Driven Development (TDD) workflows across various frameworks like Jest or pytest.

This tool automates the creation of production-ready End-to-End (E2E) tests using the Playwright framework. Users can provide natural language descriptions (like user stories, feature names, or component paths) to automatically generate comprehensive test suites. It follows best practices, including utilizing role-based locators, structuring tests with setup/act/assert phases, and generating supporting files like page objects and fixtures for maintainability.