Pseolint Reviews — Discover what people think of this product.

If you've ever built a programmatic SEO site, you know the gap between "1,000 indexed pages" and "1,000 pages that survive a Google SpamBrain pass" is where most projects actually die.

I was tired of finding out about missing variables, broken canonicals, and near-duplicate clusters after deploying. Existing SEO tools like Screaming Frog or Sitebulb are built for editorially-curated sites, they check pages one at a time. But pSEO risks happen between pages.

So, I built pseolint and pseolint.dev. It's an audit engine purpose-built for programmatic SEO architectures.

Here is how it's different:

Template-first, not URL-first: It clusters your sitemap (e.g., /listing/:slug), samples pages from each, and produces a per-template verdict. Fix one broken template, fix 10,000 pages at once.

Graph-level detection: It catches the structural issues per-page tools can't see, like entity-swap doorways, boilerplate-ratios, and thin-content propagation across your site.

Calibrated, not arbitrary: Verdicts are calibrated against a public corpus of reputable production pSEO sites (Zapier, G2, Wise, NerdWallet) — full methodology and known blind spots published at pseolint.dev/methodology.

Built for the developer workflow: Run npx pseolint http://localhost:3000 right against your local dev server (perfect for Next.js/Tailwind stacks) to catch errors before you push. Or drop it in your CI to gate PRs if the risk score spikes.

I don't believe in gatekeeping technical infrastructure, so the core engine is completely open-source under the ouranos-labs GitHub organization. You can use the hosted UI at https://pseolint.dev if you prefer a dashboard, or just grab the CLI and run it locally.

I'd love to hear how you currently handle your pSEO QA, answer any technical questions, or take a solid roasting on the codebase.

Cheers!