Lets AI agents and test suites drive real Android devices from natural-language instructions, with logcat capture and MCP integration.
📊 Python APIs for Web Automation, E2E Testing, and Data Scraping. CDP Mode bypasses bot-detection and handles CAPTCHAs. Includes a Stealth mode for Playwright.
Набор навыков для AI(ИИ)-агентов (Claude Code, Cursor, Codex и др.), помогающий охватить полный цикл разработки на платформе 1С:Предприятие 8.3. Даёт модели абстракции над XML-форматами и CLI конфигуратора, а также глаза и руки для тестирования через веб-клиент. AI skills for 1C:Enterprise 8.3.
SSL and TLS protocol test suite and fuzzer
Production-grade Playwright + TypeScript Scaffold for Agentic Testing. Harness for all major AI coding agents baked in.
Hercules is the world’s first open-source testing agent, enabling UI, API, Security, Accessibility, and Visual validations – all without code or maintenance. Automate testing effortlessly and let Hercules handle the heavy lifting! ⚡
A command-line tool and Python library and Pytest plugin for automated testing of RESTful APIs, with a simple, concise and flexible YAML-based syntax
E2E test framework for tests with complex environment requirements.
Enable AI to control your desktop, mobile and HMI devices
A curated list of awesome Robot Framework resources and libraries
[EMNLP 2026] A multilingual benchmark for repository-level unit test generation, evaluating LLMs across 5 programming languages and real-world code under reproducible, Docker-based execution.
An agent-native QA CLI for web pages. Deterministic, no tests to write, no LLM.
Jev 决策模型驱动的 UI 自动化测试框架:不生成「下一步做什么」的文字,而是在候选元素里直接打分;一句话写用例,pytest 执行,Allure 出报告,每个操作决策中位 458 ms(UI test automation driven by the Jev decision model — scored decisions, not generated prose; ~458 ms per decision)
端到端 QA 验收编排器 · Agent Skill:上下文 → 风险 → 用例 → 脚本 → 执行 → 审查 → 报告,全程自动衔接,只在用例确认时停下等你审核。支持 Claude Code / Codex / Cursor
Click does not replace Nx, Bazel, pytest, or Jest. It sits above existing verification tools and manages which verification evidence remains applicable across AI-agent iterations.