
Trawl
Version autocomplete and outdated warnings inside VS Code
What it does
Trawl connects VS Code directly to the npm registry. Open any package.json and it silently surfaces outdated dependencies as native diagnostics — red/yellow/blue underlines, just like TypeScript type errors. No commands, no terminal needed. • Semver-aware severity (major = error, minor = warning, patch = info) • Rich hover cards with live registry data • Version autocomplete with latest stable & dist-tags • One-click quick fixes to update or pin • Monorepo support with smart caching
Does the same job
all alternatives →- COContinue – Open-source coding autopilot2023 · github.com · ▲298
Hi HN, we’re Nate and Ty, co-founders of Continue, an open-source autopilot for software development built to be deeply customizable and continuously learn from development data. It consists of an extended language server and (to start) a VS Code extension. Our GitHub is https://github.com/continuedev/continue. You can watch a demo of Continue and download the extension at https://continue.dev — — — A growing number of developers are replacing Google + Stack Overflow with Large Language Models (LLMs) as their primary approach to get help, similar to how…

- SNSafe-NPM – only install packages that are +90 days oldNov 2025 · github.com · ▲90
This past quarter has been awash with sophisticated npm supply chain attacks like [Shai-Hulud](https://www.cisa.gov/news-events/alerts/2025/09/23/widesprea...() 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…

- NInpm install actual-malware2022 · github.com · ▲55
Our package registry ecosystem has a serious problem... and not just npm. People are aware of this but maybe this will make them a bit more aware
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We've been building data pipelines that scrape websites and extract structured data for a while now. If you've done this, you know the drill: you write CSS selectors, the site changes its layout, everything breaks at 2am, and you spend your morning rewriting parsers. LLMs seemed like the obvious fix — just throw the HTML at GPT and ask for JSON. Except in practice, it's more painful than that: - Raw HTML is full of nav bars, footers, and tracking junk that eats your token budget. A typical product page is 80% noise. - LLMs return malformed JSON more often than you'd expect, especially with…
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