Command Code 记录了 2,358,177 月访问量，月度环比增长为 -12.1%，定价为免费增值，定价请咨询。testRigor 记录了 105,865 月访问量，增长率为 -2.7%，定价为免费试用，定价请咨询，免费。
testRigor is an agentic AI test automation platform that lets you build end-to-end tests in plain English instead of code. It covers web, mobile, native desktop, API, email, SMS, phone calls, 2FA, and mainframe testing, includes free unlimited Generative AI, and self-heals tests so manual QA teams can automate without engineering help.
| 维度 / 指标 |  | |
|---|---|---|
| 官方域名 | commandcode.ai | testrigor.com |
| 定价模式 | 免费增值，定价请咨询 | 免费试用，定价请咨询，免费 |
| 月访问量 | 235.82万 (2,358,177) | 10.59万 (105,865) |
| 月度环比流量变化 | -32.57万 (-12.1%) | -2948 (-2.7%) |
| 主要市场与份额 | 🇨🇳 中国 (47%) | 🇺🇸 美国 (24.9%) |
| 直接访问 / 月 | 174.96万 | 5.55万 |
| 用户评分 | 4.3 | 4.5 |
| 支持的平台 | 网站 | 网站 |
会学习你编码品味的 AI 编程智能体
持续强化学习层把每一次采纳、拒绝和手动编辑变成信号，再把反复出现的模式转化为可复用的项目级技能。
自动修复格式错误的工具调用，让较弱的开放权重模型也能可靠完成智能体循环，接近前沿模型的水平。
交互式 CLI 用于结对，无头标志用于脚本化，后台沙箱智能体则用于更长时间的自主任务。
自定义 /agents 与持久化 /memory 跨会话携带项目上下文，让你不必反复解释代码库与规范。
testRigor is an agentic AI test automation platform that lets you build end-to-end tests in plain English instead of code. It covers web, mobile, native desktop, API, email, SMS, phone calls, 2FA, and mainframe testing, includes free unlimited Generative AI, and self-heals tests so manual QA teams can automate without engineering help.
Build and maintain end-to-end tests using free-flowing plain English. testRigor interprets your instructions exactly as written and executes them, with no coding required.
Tests adapt to UI changes automatically, so you spend far less time fixing broken selectors and scripts. Customers report near-zero maintenance versus Selenium and Appium.
Cover web, iOS and Android mobile, native Windows desktop, API, email, SMS, phone calls, 2FA, and mainframe testing from a single tool.
Generate tests directly in testRigor or through Claude Code using MCP and Skills, and import existing manual test cases to get started quickly.
专项更强Offers industry-leading reasoning and artifact generation, but lacks direct terminal-first integration and local preference memory.
免费 / 开源Orchestrates multiple CLI coding agents in parallel git worktrees, but is less focused on single-user preference learning.
