found 54 skills in registry
Generate unit, integration, and end-to-end tests for existing code. Use when a user asks to write tests, add test coverage, create unit tests, generate integration tests, build e2e tests, improve code coverage, write specs, or add testing to a project. Supports Jest, Vitest, Pytest, Playwright, React Testing Library, and Cypress. Analyzes code to produce meaningful assertions, edge cases, and mock setups.
Use when Codex is building or iterating on a web game (HTML/JS) and needs a reliable development + testing loop: implement small changes, run a Playwright-based test script with short input bursts and intentional pauses, inspect screenshots/text, and review console errors with render_game_to_text.
Expert guidance for Checkly, the synthetic monitoring platform that runs Playwright-based browser checks and API checks from locations worldwide. Helps developers implement monitoring-as-code (MaC) with the Checkly CLI, set up API and browser checks, configure alerting, and integrate monitoring into CI/CD pipelines.
When the user wants to write end-to-end tests for React Native apps using Detox's gray-box testing approach. Also use when the user mentions "detox," "React Native testing," "React Native E2E," "gray-box testing," or "Wix Detox." For general mobile testing, see appium. For simpler mobile UI flows, see maestro.
Automate browsers and scrape dynamic websites with Puppeteer. Use when a user asks to scrape JavaScript-rendered pages, automate browser interactions, take screenshots of web pages, generate PDFs from URLs, test web UIs, fill out forms programmatically, crawl SPAs, extract data from dynamic sites, automate login flows, or build web scrapers that need a real browser. Covers headless Chrome, page navigation, DOM interaction, network interception, screenshots, PDF generation, and stealth techniques
Assists with end-to-end testing of web applications using Cypress. Use when writing E2E tests, setting up component testing, configuring CI pipelines with parallelization, or building custom test commands. Trigger words: cypress, e2e testing, end-to-end, cypress run, cy.get, integration testing, browser testing.
Build reliable web scrapers and crawlers with Crawlee — Apify's open-source framework for structured web scraping. Use when someone asks to "scrape a website", "build a crawler", "Crawlee", "web scraping at scale", "scrape JavaScript-rendered pages", "crawl with Playwright/Puppeteer", or "extract data from websites reliably". Covers HTTP crawling, browser crawling, request queues, proxy rotation, and data export.
End-to-end workflow for fine-tuning LLMs using Kaggle datasets. Use when downloading datasets from Kaggle for model training, preparing conversation/customer service data for chatbot fine-tuning, or building domain-specific AI assistants. Covers dataset discovery, download, preprocessing into chat format, and integration with PEFT/LoRA training.
Implement the manager-prioritized milestone of an existing plan and carry it to closure, including adjacent fixes needed to pass gates and close the milestone cleanly. Use when a manager/reviewer says to start the next milestone and expects end-to-end delivery with evidence.
Write Unit and E2E tests with Jest, mocking strategies, and database isolation in NestJS. Use when writing NestJS unit tests, E2E tests with supertest, or mock providers. (triggers: **/*.spec.ts, test/**/*.e2e-spec.ts, Test.createTestingModule, supertest, jest, beforeEach)
Run an end-to-end workflow that chains `research-refine` and `experiment-plan`. Use when the user wants a one-shot pipeline from vague research direction to focused final proposal plus detailed experiment roadmap, or asks to "串起来", build a pipeline, do it end-to-end, or generate both the method and experiment plan together.
Full research pipeline: Workflow 1 (idea discovery) → implementation → Workflow 2 (auto review loop). Goes from a broad research direction all the way to a submission-ready paper. Use when user says \"全流程\", \"full pipeline\", \"从找idea到投稿\", \"end-to-end research\", or wants the complete autonomous research lifecycle.
Create an end-to-end customer journey map with stages, touchpoints, emotions, pain points, and opportunities. Use when mapping the customer experience, identifying friction points, improving onboarding, or visualizing the user journey.
Browser debugging, performance profiling, and automation via Chrome DevTools MCP. Use when user says "debug this page", "take a screenshot", "check network requests", "profile performance", "inspect console errors", or "analyze page load". Do NOT use for full E2E test suites (use playwright-skill) or non-browser debugging.
Designs and implements testing strategies for any codebase. Use when adding tests, improving coverage, setting up testing infrastructure, debugging test failures, or when asked about unit tests, integration tests, or E2E testing.
Run Playwright tests at scale using Azure Playwright Workspaces (formerly Microsoft Playwright Testing). Use when scaling browser tests across cloud-hosted browsers, integrating with CI/CD pipelines, or publishing test results to the Azure portal.
Master end-to-end testing with Playwright and Cypress to build reliable test suites that catch bugs, improve confidence, and enable fast deployment. Use when implementing E2E tests, debugging flaky tests, or establishing testing standards.
Use ONLY when the user explicitly says: 'use the skill web-to-markdown ...' (or 'use a skill web-to-markdown ...'). Converts webpage URLs to clean Markdown by calling the local web2md CLI (Puppeteer + Readability), suitable for JS-rendered pages.
Complete browser automation with Playwright. Auto-detects dev servers, writes clean test scripts to /tmp. Test pages, fill forms, take screenshots, check responsive design, validate UX, test login flows, check links, automate any browser task. Use when user wants to test websites, automate browser interactions, validate web functionality, or perform any browser-based testing. Do NOT use for quick page debugging or network inspection (use chrome-devtools instead).
Build end-to-end MLOps pipelines from data preparation through model training, validation, and production deployment. Use when creating ML pipelines, implementing MLOps practices, or automating model training and deployment workflows.