Search "best GEO tools" and you'll get a dozen near-identical listicles, most written by the tools they're ranking, all treating "generative engine optimization tool" as one category. It isn't. We looked at what these products actually do, not just what their landing pages claim, and they split cleanly into three jobs that solve different problems.
Confusing the three is the most common mistake we see. A visibility tracker will happily report "zero citations this month" forever without ever telling you that the reason is a stray Disallow: / under GPTBot in your robots.txt. A content-optimization tool will rewrite your homepage copy for AI readability while the page underneath is still rendered client-side and invisible to the crawlers that would read it. Buying the wrong tool first, or buying one tool and expecting it to cover all three jobs, is how teams end up with a GEO budget and no measurable change.
Visibility tracking: are you being mentioned at all
This is the category most GEO tools fall into, and the one that gets the most marketing attention because it produces a dashboard people like screenshotting. These tools run a set of prompts against ChatGPT, Perplexity, Gemini, and Google AI Overviews on a schedule, then report whether your brand got mentioned, cited, or linked, and how that compares to competitors.
- Profound positions itself as a full "GenAI marketing intelligence platform," tracking brand visibility, sentiment, and competitive share of voice across AI answer engines, aimed at enterprise marketing teams who want the AI-search equivalent of a rank tracker.
- Peec AI does a narrower version of the same thing: track brand performance across ChatGPT, Perplexity, and Gemini with benchmarking against named competitors, aimed at marketing teams that want something lighter than an enterprise platform.
- Otterly.ai monitors brand mentions and citations specifically across ChatGPT, Perplexity, and Google AI Overviews, and publishes a set of free GEO tools and benchmarks alongside its paid tracking product.
- AthenaHQ and Scrunch round out the category with similar multi-engine monitoring, and both have started layering auditing and content-delivery features on top, which is where the category boundaries get blurry (more on that below).
What all of these share: they answer "how visible am I right now" but they don't fix the underlying reason you aren't visible. If GPTBot is blocked in your robots.txt, a visibility tracker will faithfully report zero citations forever, without ever telling you why. They're also all built around sampling: a fixed list of prompts run on a schedule, extrapolated into a visibility score. That's a reasonable proxy, but it means the number moves for reasons that have nothing to do with your site, like the model provider changing how it phrases citations, or your competitor's PR landing in enough training data to shift the sample.
Pricing in this category runs from free tiers with a handful of tracked prompts up to several hundred dollars a month for enterprise seat counts and larger prompt volumes, roughly in line with what a mid-tier rank tracker costs in classic SEO. Worth trying the free tier before committing, since the prompt sets and reporting depth vary more between these tools than the marketing pages suggest.
Content optimization: rewriting for AI answers
A second category focuses on the content itself, generating or scoring copy against the patterns that seem to get cited more often: direct-answer openings, structured comparisons, conversational phrasing that mirrors how people prompt AI assistants.
Writesonic's GEO tool is the most visible player here, combining prompt-level tracking with content generation aimed at closing citation gaps, plus outreach features for getting mentioned on third-party sites AI engines already trust. Several established SEO content platforms have bolted similar "AI readability" scoring onto their existing content-optimization products, treating GEO as a new grading rubric on top of the same content workflow.
This category earns its keep if your bottleneck is genuinely the writing: content that's accurate but poorly structured, missing direct answers, or written for search-engine keyword matching instead of conversational queries. It's a different story if AI crawlers can't reach the content to begin with, which is more common than the marketing for these tools suggests. Before paying for a content rewrite, it's worth confirming the content is even fetchable and renders as HTML an agent can parse, since no amount of rewriting fixes a page that never gets crawled.
Technical and agent experience auditing: can an agent reach and parse you at all
The third category is thinner, and mostly made up of single-purpose free checkers: a robots.txt validator here, an llms.txt generator there, a JS-rendering checker somewhere else. Useful, narrow, and none of them roll the full picture into one report.
This is the bucket we're honestly in, and we built squirrelscan because we wanted the full picture in one place, not five browser tabs of single-purpose checkers. It's a CLI (squirrel) plus a hosted MCP server, running 249+ rules that cover the technical prerequisites this whole roundup keeps circling back to: AI crawler access per named bot, llms.txt presence and format, whether main content survives without JavaScript, schema validity, and LLM parsability, alongside the broader SEO, performance, security, and accessibility rules a site needs regardless of which answer engine is reading it.
Unlike a single-purpose checker, it's a full crawl, not a one-page spot check: it walks the site the way a real crawler does, so a stray Disallow rule that only shows up two directories deep, or a template-level JavaScript-rendering problem that affects every product page, doesn't slip through because you only tested the homepage.
The practical difference from the other two categories: squirrelscan doesn't tell you how often ChatGPT mentioned your brand last week, and it doesn't rewrite your copy. It tells you, deterministically and repeatably, whether the technical and structural preconditions for AI visibility are met right now, the same way it would for a page that only cares about classic Google ranking. If you're already using a visibility tracker and citations aren't moving, this is the layer that tells you why.
curl -fsSL https://install.squirrelscan.com | sh
squirrel audit https://example.com --format llmIt also runs inside a coding agent. Point Claude Code at your repo with the squirrelscan skill or MCP server installed, and it can audit a site, read the report, and go fix the flagged issues in the same session, without you copying results between tools.
Which one do you actually need
If you're a small team shipping a marketing site, start with the technical audit: it's free to run locally, and it catches the crawler-access and schema gaps that make every other GEO effort moot. Add a visibility tracker once you've fixed the fundamentals and want to measure whether citations actually move. Reach for a content-optimization tool only once you've confirmed, with evidence rather than a hunch, that the writing itself is the bottleneck, not the plumbing underneath it.
For a larger team already running a visibility tracker with flat or falling citation numbers, the order flips: run the technical audit first as a diagnostic before assuming the content needs a rewrite. It's a five-minute check against a recurring subscription, and crawler-access or JavaScript-rendering gaps are common enough on real sites that it's worth ruling them out before touching a single sentence of copy.
For the plumbing specifically, run our free llms.txt validator, or read the full generative engine optimization guide for the complete checklist this roundup keeps referencing. For MCP setup details and what an agent can do with squirrelscan's tools once connected, see squirrelscan as an SEO MCP server.