展示HN：AI Lint 让你的代理工作更快、更好
我最近在使用我制作的一个工具，叫做“AI Lint”。它是一个关于最佳实践和反模式的集合，我注意到代理在使用这些最佳实践时既有失败的情况，也有过度依赖的情况。
这个工具还包含了一些调试和架构的一般模式，帮助代理在大型代码库中管理复杂性。
看到Codex说：“此外，为了深入了解，我需要先遵循这个仓库的AI Lint规则。我可以开始阅读这些规则，然后检查最近的更改。你希望我继续吗？”这真的很酷。
这些都是非语法性的、非机械性的高级工程智慧，针对特定的语言和框架，基于经验，旨在让AI模拟高级架构师的“品味”，而不仅仅是反复敲代码直到“基本可用”。
AI代码混乱的问题是真实存在的，嵌入一些硬性规则和拒绝标准到仓库中，让代理必须遵循，以防止他们的无效操作（并减少目标达成的时间），比事后修复他们的问题要容易得多。
我经历过这样的情况，现在我创建了AI Lint。这也是你的工具。虽然需要付费，但有一个免费的试用版可以让你了解这个工具的概念：AI能够流利地理解语法，但他们不容易掌握一种语言的“精髓”。
我对这个名字感到自豪，因为它确实传达了这个工具的意义——既是“AI的Lint”，也是“原生AI Lint”，它利用了AI在复杂细微理解和任务执行方面的优势，同时弥补了它们在复杂情况下提供正确解决方案时的不足。
付费版本还包含了安全秘密部分、如何编写AI将遵循的规则的指南，以及一个可以用来解决不同规则之间冲突的覆盖协议（这都是权衡），或者仅仅是为了符合你自己团队的口味而覆盖Lint。
总体来说，代理是必要的，并且将会继续存在。在此期间，我认为像这样的特定领域上下文增强和超精确的工具，将帮助他们快速跳转到任务，同时保持上下文的清晰度，这将是两个（还有很多）巨大的杠杆。目前，AI仍然缺乏高级开发人员所带来的深度、智慧和优秀的设计/架构直觉——但高级开发人员在没有帮助的情况下，工作速度无法与AI相提并论。因此，找到一种最佳的合作方式是更好的选择。因为使用一个需要你重做的低质量AI是没有意义的。AI Lint是朝这个方向迈出的一个小而希望有用的步骤。
我希望你能尝试一下，发现它的价值并为此付费，同时通过关注未来的新版本，支持它的发展，这些新版本将涵盖更多语言、框架和有用的领域。
快来看看吧！ [https://ai-lint.dosaygo.com](https://ai-lint.dosaygo.com) :)
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I've been using this thing I made called "AI Lint" it's a collection of doctrine, ant rejected anti-patterns that I noticed agents both failing to use and overly leaning into.<p>It's also general patterns for debugging, and architecture to help agents manage complexity in large codebases.<p>It's kind of cool to watch Codex say: <i>"Also, to dig in, I need to follow the repo’s AI Lint rules first. I can start reading those and then inspect the recent changes. Do you want me to proceed?"</i><p>These are non-syntactic, non-mehanical, senior engineering wisdom that is tailored to specific languages and frameworks, won of experience, and aiming to let the AI simulate an senior architect's "taste", rather than just hammering away until code "basically works".<p>The problem of AI spaghetti code is real, and it's easier to embed some hard doctrine and rejects into the repo that agents must follow to prevent their nonsense (and reduce time to target) than it is to fix their problems later.<p>Been there, done that. Now I built AI Lint. And it's yours too. For a fee, but there's a free taster to get the idea: AI get syntax fluently, but they don't readily pick up the "grain" of a language.<p>I'm proud of the name I think it really resonsates and captures what this is both "lint for AI" but also "AI-native lint" that leans into their strength of complex nuance understanding and task following, while patching their weaknesses for really bringing the right solutions to bear at the right time in compelx situations.<p>The paid version also has sections for secrets security, a guide on how to author your own doctrine that AI will follow, and an override protocol you can use to resolve conflicts between conflicting doctrine (it's all tradeoffs), or just override the lint for your own team's taste.<p>On the whole agents are needed and going to be here. In the meantime I think domain specific context-boosting like this, and super precise tooling to let them quickly jump to tasks while retaining contextual clarity is going to be two (among many) huge levers. For now, AI still lack what senior devs bring to the table - depth, wisdom, and great design/arch instincts -- but senior devs can't work as fast, unaided, as an AI can. So it's better to figure out a way to work together optimally. As there's no point using an AI that makes subpar work you have to redo. AI Lint is a small, hopefully useful, step in that direction.<p>I hope you will try it, find value in it and pay for it, and support its future development by staying on board as new packs land for additional language, frameworks and useful domains.<p>Check it out! <a href="https://ai-lint.dosaygo.com" rel="nofollow">https://ai-lint.dosaygo.com</a> :)