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Products that do what Iris — Code Health does

Your code has a health score. Find out what's hurting it.

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    tl;dr we at Escape (YC W23), we scanned 5651+ public APIs on the internet with our in house feedback driven API exploration tech, and ranked them using security, performance, reliability, and design criteria. The results are public on https://apirank.dev. You can request that we index your own API to the list for free and see how it compares to others. Why we did that? During a YC meetup I spoke with a fellow founder that told me how hard it was to pick the right external APIs to use within your own projects. I realized that most of what we build relies on public APIs from external…

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    Hi HN! This is a little site I put together while learning the Elm language as part of a hackathon at my work, I thought you might enjoy it. Be sure to click the `(source)` buttons next to the graphs: you can edit them interactively & write your own queries against the entire data set. The syntax isn't well documented yet, but you can probably get the general idea pretty quickly based on the examples there. If you like it, have questions, etc. let me know! If folks think this is cool, maybe I can get it turned into a legit project. :)

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    A small CLI that runs the checks you'd normally do manually: DNS, HTTPS, SSL expiry, redirects, response time, email records, domain expiry, and more. Zero dependencies, JSON output, install via Homebrew.

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    As software engineers we are often confronted with the decision of whether to code something ourselves or to add an existing library that does it for us. Whether we like it or not – we are adding dependencies sooner or later. And it's arguably good practice to check a new dependency beforehand: Is it maintained? By whom? How many issues does it have and how many of those are bugs? Are they being fixed? What's on the roadmap? What's the release frequency and how often do APIs break? One of our favorite solutions that already exist to answer such questions is the OpenSSF Scorecard project…

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    I built a CLI that detects patterns AI coding tools leave behind: empty catch blocks, hardcoded secrets, as any everywhere, comments that restate the code, god functions, SQL concatenation. 24 rules across JS/TS and Python. Zero config, runs offline, regex-based so it's fast. npx @yuvrajangadsingh/vibecheck . Also ships as a GitHub Action for inline PR annotations and standalone binaries (no Node required). Why: CodeRabbit found AI-generated PRs have 1.7x more issues than human PRs. Veracode says 45% of AI code samples have security vulnerabilities. "Vibe coding" is everywhere now…

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