开发者工具2 days ago
NodeESP — Visual programming for ESP32
NodeESP是ESP32的可视化编程工具，通过节点拖拽创建GPIO逻辑和MQTT工作流。
@NodeESP · X
- Project for sale
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NodeESP是ESP32的可视化编程工具，通过节点拖拽创建GPIO逻辑和MQTT工作流。
@NodeESP · X
- Project for sale
用Resumedit创建和分析简历，获取ATS优化建议，管理求职申请。
@vilder222 · X
resume tool to land interviews quickly:
Transform any YouTube video into concise, actionable insights
@ekstraktapp · X
Lumora Lens自动化社交媒体规划、品牌内容创建和排期发布。
@LumoraLens · X
Lumora Lens fully automates social media for small businesses including posts, DMs, comments and Google reviews
用可视化无代码构建器构建和部署多智能体工作流。
@Otogent · X
记录一次浏览器任务，然后在新数据上自动重放。
@OikosAutomation · X
Betii - 瑞典彩票AI分析和模拟工具，支持赔率分析和系统优化。
@MarcusNilsson83 · X
Check out what I just built with Lovable!
提交系统架构设计，体验AI触发的生产事故模拟实战。
u/No-Preference-846 · Reddit
I built an AI-augmented system design practice tool that triggers a live production incident when you submit your design - not just a critique Every system design prep resource I used was static — read a diagram, read the tradeoffs, move to the next one. Nothing ever pushed back on what I actually built. So I built ChaosBench . You design a system on a canvas — drag components, wire them up — and when you submit it, an LLM (Gemini) finds the actual weak point in your specific design and
用 AI 分析 GitHub pull request 获得合并信心分数。
@aryawarti_aky · X
Hey Daniel ! I Built PRisk — an AI-powered pull request risk intelligence platform for GitHub & Gitea. Paste a PR URL and get an evidence-backed Merge Confidence Score before you merge. 🔗 I'd love to hear your feedback!
AI工具，通过分析会议记录检测范围蔓延，为代理商和自由职业者标记风险。
@theshaunak_twit · X
由AI驱动的代码审查工具，在microVM中运行代码来捕获更多错误。
u/dumbfoundded · Reddit
Ito, AI Code Review that Runs Code I've been using AI code review tools but none of them actually run code so I built one: https://www.ito.ai/ The way it works is that it uses microVMs to spin up your environment with all of the services running. Then a bunch of AI agents go and test the application to collect runtime evidence. The result is you get test cases along with evidence about whether or not the test cases pass or fail. The runtime evidence can be videos, request/response curls, db
