ShellNewHandler VS GeoSkoru

GeoSkoru's answer:

Most GEO tools do one of two things: run a checklist of technical rules, or ask a language model what it thinks of a page. GeoSkoru does both and keeps the layers separate. Deterministic checks handle what can be verified outright, such as crawler and AI agent access, structured data, and recency signals. An LLM pass handles what needs judgment, such as whether a passage still answers a question when lifted out of its page, and whether the content reads as authoritative on its topic.

The two layers are combined and weighted against domain authority, and the scoring curve is calibrated per site type, so a local service page is not judged against the same expectations as a documentation site.

The report also ends with something you can use immediately: a generated llms.txt file for your site, rather than a reading list of things to go fix.

GeoSkoru's answer:

Three reasons.

It is free and ungated. No account, no trial countdown, no credit card. A full analysis takes about 20-30 seconds. Most comparable tools put the score behind a signup or a monthly plan.

It is more than one score. The same site gives you an AI visibility test that runs real queries on ChatGPT, Claude, Gemini and Perplexity to see whether you are cited as a source, a technical SEO audit, a Google rank finder, and a content extractability analysis. All free.

It gives you something to publish. Sites scoring 70 or above can embed a verified GEO Certificate badge, in four styles with light and dark variants. The badge is checked against the live page, so it is a claim a visitor can verify rather than a graphic anyone can copy.

GeoSkoru's answer:

Site owners, SEO consultants and content teams who already watch their Google rankings and now want to know whether AI assistants can see and cite them.

In practice it splits three ways:

• Small publishers and tool site operators checking their own properties
• Agencies running a quick audit on a prospect's site before a pitch, or on a client's site before a content sprint
• Developers who want concrete fixes (crawler rules, schema, llms.txt, page structure) rather than strategy advice

Reading the report needs no technical background. Acting on parts of it sometimes does, which is why each finding names the specific thing to change.

GeoSkoru's answer:

Node.js and Express on the back end, a Vite-built single-page front end, and PostgreSQL for audit storage and domain caching.

The LLM layer of the scoring engine runs on Gemini 2.5 Flash Lite. Analyses stream their progress to the browser over server-sent events, so the page fills in as each criterion is evaluated instead of waiting on one long request.

Hosting is on Google Cloud Run behind Cloudflare, which also serves the GEO Certificate badge SVGs.