1作者: wozzio30 天前原帖
URL: <a href="https:&#x2F;&#x2F;github.com&#x2F;WozzHQ&#x2F;wozz" rel="nofollow">https:&#x2F;&#x2F;github.com&#x2F;WozzHQ&#x2F;wozz</a><p>Hi HN,<p>I built Wozz, an open-source CLI and GitHub Action to catch expensive Kubernetes configs before they merge.<p>The Motivation I noticed that most cloud cost tools (like Kubecost) only show you the bill 30 days later. By then, the over-provisioned sidecar or massive Java heap is already in production. I wanted something that acts like a unit test for resource requests blocking fat finger mistakes in the PR rather than waiting for the bill.<p>How it works Wozz runs in two modes:<p>In CI&#x2F;CD (The Linter): It parses the git diff of your manifests (deployment.yaml, etc.), calculates the cost delta (requests × replicas), and posts a comment if the change exceeds a threshold (e.g., +$50&#x2F;mo). It also checks HorizontalPodAutoscaler limits to flag worst-case scaling risks.<p>Locally (The Auditor): It scans your current kubecontext to compare reserved requests vs. actual live usage (kubectl top). This helps find the &quot;Sleep Insurance&quot; gap—where devs request 4GB RAM just to be safe, but the app only uses 200MB.<p>Implementation Details<p>Stack: TypeScript&#x2F;Node.js.<p>Math: Instead of querying AWS Cost APIs (which requires sensitive creds and is slow), it uses a configurable Blended Rate (e.g., $0.04&#x2F;GB&#x2F;hr) to estimate costs deterministically.<p>Privacy: It runs 100% locally or in your runner. No manifests or secrets are sent to any external server.<p>Repo <a href="https:&#x2F;&#x2F;github.com&#x2F;WozzHQ&#x2F;wozz" rel="nofollow">https:&#x2F;&#x2F;github.com&#x2F;WozzHQ&#x2F;wozz</a><p>Feedback I’m currently using a static Blended Rate for the cost math to keep the tool fast and stateless. I’m curious if this approximation is accurate enough for your team&#x27;s guardrails, or if you strictly require real-time Spot Instance pricing to trust a tool like this?
7作者: egglemonsoup30 天前原帖
I created a daily game where you get a random Bible verse and try to identify the book (e.g. &quot;Psalms&quot;, &quot;Genesis&quot;, &quot;Luke&quot;) in as few guesses as possible.<p>I have absolutely no clue how I got the idea, other than the fact that I grew up in the Orthodox Church and all my other coding projects have been faith-related (a terrible mobile app (1) and slightly broken Byzantine chant website (2) ). I&#x27;m a relatively new developer and I&#x27;ve been hungry for a project to build that people will actually use and share around, so I hoped this would fit the bill.<p>Sure enough, friends and family have been making it part of their daily routine. When priests AND my nonreligious college friends started sending me their results every day, I knew I had <i>something</i>. It was really exciting.<p>------<p>When the idea popped into my head, I started working on it right away. I created the project at 1AM and had a MVP&#x2F;SLC version done a few hours later. That was a few weeks ago.<p>I am using SvelteKit, no external APIs, and SQLite for the database. It&#x27;s hosted on an Ubuntu machine in my living room. Coding agents like Roo&#x2F;Kilo Code assisted heavily in the development, but after I had already decided on the overall architecture and how I wanted things to work together.<p>The game is free, has no signup, and I’m not running any ads. I’m looking for any and all feedback, and especially suggestions for how I can make the game more interesting, fun, and&#x2F;or educational.<p>Thank you HN!
1作者: afrazullal30 天前原帖
Hey HN, We all know the pain: The code is clean, the product is solid, but the landing page isn&#x27;t converting. I built Vect (vect.pro) to solve this. It’s an Autonomous Marketing OS, but the core feature is the Conversion Killer Detector. Instead of just &quot;generating text&quot;, it acts as a hostile auditor. It simulates a skeptical buyer&#x27;s inner monologue to flag exactly where your copy is vague, passive, or confusing. The Tech: Frontend: React + TypeScript (Command Center UI). Reasoning: Gemini 2.5 Flash for the audit logic. Simulation: It runs your copy through 10 distinct &quot;Skeptic&quot; personas to find friction points. It’s free to try the audit. I built this to help technical founders stop losing sales to bad copy. Link: <a href="https:&#x2F;&#x2F;vect.pro&#x2F;" rel="nofollow">https:&#x2F;&#x2F;vect.pro&#x2F;</a>
1作者: chw9e30 天前原帖
AI coding agents can build iOS UI, but they can&#x27;t verify it. They can update a screen, but the UI might drift or break, and nobody catches it until a human checks.<p>qckfx gives your agent a baseline. Record a simulator session once. Every tap, scroll, and network response gets captured. On replay, each screen is compared against the original.<p>With our MCP, your agent triggers the tests and gets back visual diffs of exactly what changed. Updating the baselines is one click.<p>Under the hood:<p>- Full network replay (HTTP &amp; WebSocket)<p>- Initial disk &amp; keychain state captured during recording and restored on every run<p>- Precise scroll positioning (built from scratch; XCUITest only exposes this on macOS and iPad)<p>- No AI in the loop at runtime, fast execution<p>No SDK or code changes needed. Nothing to commit to git. Just download the app and go.<p>Everything runs locally. Your data stays on your machine.<p><a href="https:&#x2F;&#x2F;qckfx.com" rel="nofollow">https:&#x2F;&#x2F;qckfx.com</a>