AI 智能体2 weeks ago
Roverly — Agentic Testing
Scale software testing by deploying deterministic agents across web, iOS, and Android. Replace manual QA and brittle automation.
@RoverlyAI · X
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15 projects
Scale software testing by deploying deterministic agents across web, iOS, and Android. Replace manual QA and brittle automation.
@RoverlyAI · X
测试和监控 API，获取实时洞察和进行负载测试。
@SajidAbuba74138 · X
A tool for developers
与 AI 招聘官练习面试，获得实时反馈。
BenGallagh · HN
AI mock interview tool that scores your answers – free, no signup
通过 REST API 或 MCP 创建临时邮箱来捕获验证邮件并提取代码。
@anhphong_dev · X
将用户故事转换为自动化测试用例，支持API、Web UI、移动及性能测试。
rupesh_kabra · Product Hunt
QAEverest AI AI-Powered QA Platform for Smarter Software Testing
Jira测试管理插件,支持测试用例和可追溯性。
@pakosteve · X
Improve your SaaS quality when scaling (by register requirements and test via MCP)
与AI面试官练习编码和系统设计面试。
u/redskinnypete · Reddit
I made an AI interviewer for coding and Design interviews I built an AI-powered mock interviewer that simulates a real system design interview. It listens to your approach, asks follow-up questions based on your design, challenges your decisions, and provides detailed feedback on what you did well and where you can improve. I have tried to make it feel like a real interview as much as I could to simulate the pressure and the expectations in an interview. Please give it a try. Hope you wil
Practise realistic AI mock interviews with adaptive follow-up questions, role-specific preparation, and evidence-backed feedback from HotSeat.
@FaizaanShaikh25 · X
SaaS + AI builder here 👋 Introducing HotSeat think you can handle the interview and get a top score? 👀 Try it: Would love some honest feedback!
用REST API编程方式生成Midjourney图像的服务
lys623 · HN
Midjourney API with webhooks, polling
Salable：基于 Stripe 的混合计费平台，处理定价、权限和团队访问。
@__orderandchaos · X
阅读免费的Earnings Call文本或通过API和MCP服务器集成。
@RobGuerra90 · X
Building : access earnings call transcripts via a cheap API or MCP server. Pull any company's call right into your workflow.
为技术文档创建 AI 助手，立即回答用户问题。
@emilsnotes · X
Our customers using Claude Code move faster than we can ship features. So we stopped fighting it and leaned in. Here's why it's paying off: 👇️ Some context: powers AI agents that answer millions of technical questions per month. Those conversations are a goldmine - they tell you exactly what users struggle with and where your docs fall short. We've built a lot of analytics on top of this (Coverage Gaps, Top Questions, and more), and teams love them. But here's the honest truth: no dashboard covers every edge case for every company. Meanwhile, our sharpest customers were already exporting kapa data and throwing their coding agents at it in ways we never designed for. So instead of chasing every workflow with a UI, we took the best practices we've seen actually work and packaged them as Kapa Skills - installable in Claude Code, Cursor, or Codex: 1/ Analyze Coverage Gaps: your agent works through the topics kapa couldn't answer and writes the missing content straig