Show HN: Safe-NPM – only install packages that are +90 days old https://ift.tt/Wxy0jSP

Show HN: Safe-NPM – only install packages that are +90 days old This past quarter has been awash with sophisticated npm supply chain attacks like [Shai-Hulud]( https://ift.tt/kAc68OP... () and the [Chalk/debug Compromise]( https://www.wiz.io/blog/widespread-npm-supply-chain-attack-b... ). This CLI helps protect users from recently compromised packages by only downloading packages that have been public for a while (default is 90 days or older). Install: npm install -g @dendronhq/safe-npm Usage: safe-npm install react@^18 lodash How it works: - Queries npm registry for all versions matching your semver range - Filters out anything published in the last 90 days - Installs the newest "aged" version Limitations: - Won't protect against packages malicious from day one - Doesn't control transitive dependencies (yet - looking into overrides) - Delays access to legitimate new features This is meant as a 80/20 measure against recently compromised NPM packages and is not a silver bullet. Please give it a try and let me know if you have feedback. https://ift.tt/Ac7wOt4 November 24, 2025 at 03:44AM

Show HN: Fixing Google Nano Banana Pixel Art with Rust https://ift.tt/S87giyU

Show HN: Fixing Google Nano Banana Pixel Art with Rust https://ift.tt/VIyEhZH November 26, 2025 at 09:16PM

Show HN: Secure private diffchecker with merge support https://ift.tt/mA61XgC

Show HN: Secure private diffchecker with merge support Built a minimal diff checker with merge feature. 1. Supports 25K+ lines. 2. Character level instant diff. 3. Diff merge feature. 4. Share able links. 5. 100% secure, all diff computation happens in browser. No other website offering high quality diff checker and merge feature with just browser only implementation. Please review the website in detail and share feedback. https://diffchecker.dev November 26, 2025 at 12:30AM

Show HN: Superglue – OSS integration tool that understands your legacy systems https://ift.tt/W0gEUSY

Show HN: Superglue – OSS integration tool that understands your legacy systems If you've ever worked in a large company, you've probably encountered "shadow infrastructure": scripts nobody understands or custom connectors written once and never touched again. This glue layer isn't documented, isn't owned by anyone, and tends to break when systems are upgraded or someone leaves. It's also the part everybody dreads working on, because it's hard to understand, painful to work with, and full of unknown unknowns. We built superglue so that engineers stop wasting time on deciphering legacy APIs and documentation. superglue ingests existing glue code, SQL, configs, docs, OpenAPI specs and reverse-engineers what the system is actually doing. It then maps dependencies and regenerates everything as clean javascript code that can run directly or be exposed via MCP or SDK. It also monitors API changes and schema drift, and automatically repairs integrations when upstream systems change. In short: It turns legacy integrations into code you can easily understand, test, and update. So that engineers can do more exciting feature work, and companies can migrate and upgrade systems faster. Think of it as: a context engine + code generator + integration runtime for legacy glue. What we'd love feedback on - How do you deal with "nobody knows what this script does" situations? - What would you want to know about your legacy systems? OSS/community version: https://ift.tt/SulCXoR More info: https://superglue.ai Happy to go deeper on the technical details. https://superglue.ai November 25, 2025 at 09:58PM

Show HN: I built an interactive HN Simulator https://ift.tt/0shvW83

Show HN: I built an interactive HN Simulator Hey HN! Just for fun, I built an interactive Hacker News Simulator. You can submit text posts and links, just like the real HN. But on HN Simulator, all of the comments are generated by LLMs + generate instantly. The best way to use it (IMHO) is to submit a text post or a curl-able URL here: https://news.ysimulator.run/submit . You don't need an account to post. When you do that, various prompts will be built from a library of commenter archetypes, moods, and shapes. The AI commenters will actually respond to your text post and/or submitted link. I really wanted it to feel real, and I think the project mostly delivers on that. When I was developing it, I kept getting confused between which tab was the "real" HN and which was the simulator, and accidentally submitted some junk to HN. (Sorry dang and team – I did clean up after myself). The app itself is built with Node + Express + Postgres, and all of the inference runs on Replicate. Speaking of Replicate, they generously loaded me up with some free credits for the inference – so shoutout to the team there. The most technically interesting part of the app is how the comments work. You can read more about it here, as well as explore all of the available archetypes, moods, and shapes that get combined into prompts: https://news.ysimulator.run/comments.html I hope you all have as much fun playing with it as I did making it! https://news.ysimulator.run/news November 24, 2025 at 11:22PM

Show HN: Runbooks – Shareable Claude Code Sessions https://ift.tt/81GBrUg

Show HN: Runbooks – Shareable Claude Code Sessions When we asked developers from large engineering teams, almost everyone is using Claude Code, Cursor, or Copilot. But adoption is still inconsistent. Some of us would have 15 agents running in Claude Code at the same time; some would still refuse to use any of them and write code manually. There's a fragmented AI development problem: - Five developers building similar features, and all of them start from scratch - No way to share "here's how we prompt AI to follow our architecture" - No trail of how the AI changes were generated - People leave the company, so does the their knowledge Aviator is a developer productivity platform with tools like MergeQueue, Stacked PRs, Releases ( https://ift.tt/Ozf9xGQ ). Runbooks came from watching our own team and our customers struggle with fragmented AI adoption. With Runbooks 1. Create executable specs - Plan (with AI) that captures intent, constraints, and steps before AI touches code 2. Version control everything - Specs, AI conversations, and generated changes are all versioned. Fork, improve, roll back 3. Make it multiplayer - Multiple engineers collaborate in the same AI coding session. 4. Build a template library - Migrate one test from Enzyme to React Testing library → use that Runbook to batch migrate the entire test suite. We're not replacing Claude Code or Cursor. Runbooks is powered by Claude Code. We’re just making it work at team scale. -- Explore our prebuilt template from our open-source library: https://ift.tt/S03nh9N Templates cover migrations, refactoring, and modernization. They're code-agnostic starting points that generate Runbooks using your code context. Docs and quickstart: https://ift.tt/Mv5eHDE -- About the name: Yes, we know "runbooks" makes you think incident management. But technically a runbook is just a documented, step-by-step procedure—which is exactly what these are for AI agents. We're keeping it! Happy to get feedback, answer questions about architecture, context management, sandboxes. https://ift.tt/8yRl4PJ November 25, 2025 at 12:09AM

Show HN: I built an interactive map of jobs at top AI companies https://ift.tt/xBIrzgi

Show HN: I built an interactive map of jobs at top AI companies I built a live interactive map that shows where top AI companies hire around the world. I collected this data for a hackathon project. Many ATS providers have a public API that you can hit with the slug of the companies to get open jobs. The hardest part was finding the companies. I tried Firecrawl but it returned around 200 companies per provider which wasn’t enough for me. Then, I tried SERPAPI but it was expensive. I ended up using SearXNG to discover companies by ATS type and fetch their job postings. This produced a large dataset of 200k+ jobs (I only use a subset as it would have taken too much time processing). A few days ago, I decided to build a visualization of the data as I didn’t know what to do with it and wanted people to benefit. I kept catching myself wanting to ask simple questions like “show only research roles in Europe” or “filter for remote SWE positions” (and had plenty of free ai credits) so I added a small LLM interface that translates natural language into filters on the map. The map is built with Vite + React + Mapbox. Live demo: https://map.stapply.ai GitHub (data): https://ift.tt/EQhyitR Would love feedback, ideas for improvement, or contributions. https://map.stapply.ai November 24, 2025 at 11:38PM