I bought TextFocus to solve a specific problem: I want to validate my pages against criteria my other tools simply don't measure. After working with it on real production pages, it earned a permanent place in my workflow.

What TextFocus does that nothing else does well

**JSON-LD extraction and structural display.** This alone justifies the purchase for me. Most tools either ignore schema markup or give you a binary "valid / invalid" verdict. TextFocus pulls the full JSON-LD structure of a page and lays it out as a readable table — every property, every nested object, every reference. When I'm working with an AI assistant on schema audits, the assistant cannot see schema markup at all in normal page fetches (it gets stripped during HTML conversion). The google URL testing tool needs some time each time you check a page, and then you can't copy the result from there. With TextFocus, I can hand the entire structure over (copy+paste) and discuss it with Claude. That changes the workflow completely. *Sentence added 260507* This is awesome since the MCP connector got added today, so I can let Claude send the page to MCP for checking and get back the results with no copy-pasting.

It also revealed inconsistencies I had no idea about. My Person schema description still said "19+ years of experience" — outdated, the right number is 23. Customer count was wrong by an order of magnitude. These are small data points that propagate into every LLM crawl and quietly undermine credibility. Without TextFocus, I would have continued shipping that for months.

Relative semantic score per keyword. TextFocus tells you not just whether a keyword is present, but how dominant it is relative to the content. On my homepage, my brand name scored 100 (perfect). My target keyword scored 76 (good). One legacy keyword I am explicitly trying to deprecate scored 47 — way too high. That number is invisible from the inside; you feel that the page is "still too focused on the old topic", but you cannot prove it without a measurement. TextFocus makes it concrete and actionable.

Readability with multiple formulas. Flesch-Kincaid, ARI, Coleman-Liau, Dale-Chall, plus a list of all long sentences and complex words. The list is what I actually use — it tells me exactly which sentences to rewrite. The per-element diagnostics are where the value is.

Competitor analysis on the target phrase. TextFocus pulls the top-ranking competitors for your chosen keyword and shows their word counts, semantic scores, and SEO scores side by side. This is not unique among SEO tools, but the integration with semantic scoring is. You can see at a glance whether your underperformance is because you have less content, less semantic coverage, or both.

What I really appreciate

The tool surfaces problems other tools either miss or bury under noise. The summary view at the top — five core scores, then categorical breakdowns — is well designed. Issues are flagged in plain language with actionable suggestions, not just numerical warnings. The PDF export is clean enough that I share it with clients as a deliverable.

What is genuinely missing — but the developer is responsive

A few items I am currently missing

1. German readability formulas. Flesch-Kincaid and friends are calibrated for English. For German-language SEO/GEO work — a meaningful market — the established formulas are Wiener Sachtextformel, LIX, and Hohenheimer Verständlichkeitsindex. Adding these would make TextFocus a serious option for German-speaking professionals.

2. **Schema.org spec validation,** not just "valid JSON-LD" but "required properties missing" or "deprecated properties used". Would prevent issues like outdated Course schema usage that broke after Google's June 2025 deprecation.

** Updated 260507 ** Awesome update: an MCP connector got added, so AI assistants can pull TextFocus data directly during analysis sessions. This is the feature that makes TextFocus indispensable, because the JSON-LD extraction and consistency scores are exactly what an AI workflow needs as a feedback signal.

If you already have an SEO suite that handles keyword research, backlinks, and rank tracking — and you want to add the layer of analysis that those suites typically gloss over (schema structure, semantic consistency, readability, AI agent accessibility) — TextFocus is the right tool. It is not a replacement for general-purpose SEO platforms. It is the precise, surgical complement that turns vague "this page underperforms" intuitions into concrete numbers you can act on.

If you produce content for AI search visibility, schema and consistency are no longer optional. TextFocus is one of the few tools that takes them seriously enough to actually measure them.

Verdict
A focused, technically substantial tool with an MCP connector from a developer who clearly knows what matters. Recommended without reservation for SEO professionals and content creators who care about the deeper layers of on-page optimization.