What Your Score Means

Score Bands

Every piece of content scored on Will AI Find It receives a score from 0 to 100 based on 11 writing-quality dimensions. The score reflects how the writing performed against that rubric, which is drawn from published GEO research where it exists and from editorial judgment about what makes prose quotable. It is not a citation probability. Will AI Find It has not validated its scores against actual citation outcomes, and no band on this page predicts one.

What to Expect

Scoring is calibrated to be honest, not encouraging. The rubric asks for things most drafts do not have on the first pass: numbers behind the claims, a voice behind the byline, the point stated before it is argued. A first score in the middle of the range is a diagnosis, not a failure.

We do not publish a score distribution. The scans collected so far are mostly our own content and our early users', and a distribution drawn from that would describe us, not the internet. When enough scans from unrelated sources exist to say something defensible, this section will say it, with the method.

If your first score is lower than expected, that's the tool working as designed. The dimensional breakdown shows exactly where the weaknesses are, and the priority fixes show exactly what to change.

How Iterative Scoring Works

Will AI Find It is built for iteration. Score, fix, rescore. Each round surfaces different problems.

Round 1. The first round catches what a good editor would catch in a single read-through: claims with no numbers behind them, corporate filler where a specific fact should be, and the complete absence of the author's own experience. On our own ForgeWorkflows post, described below, fixing these produced a 36-point improvement in one pass.

Round 2. Once the obvious gaps are closed, the diagnosis shifts. Now it's finding the paragraph that starts the same way as the one before it, the transition that says “Furthermore” instead of making an actual connection, the key finding buried in paragraph six that should be in paragraph one.

Round 3 and beyond. By the third round, the tool is reading like an editor who has already approved the structure and the argument. What's left is rhythm — a run of same-length sentences, a section that lacks any acknowledgment of tradeoffs, a piece that could have been written in any year because it never references the current moment. These are smaller fixes, but they're the difference between content that is merely competent and content that is worth quoting.

We scored one of our own posts — from ForgeWorkflows, a sister brand run by the same team — at 49. The diagnosis was specific and uncomfortable: the byline said “founder” but nothing in the article sounded like one. A paragraph about API configuration had been pasted from a different draft and never caught in review. Every improvement claim said “measurably” without providing a single measure. We implemented the priority fixes — added the founder's actual perspective, replaced vague claims with real numbers, cut the orphaned paragraph — and rescored: 85. One more round of structural refinements brought it to 90. Three rounds, about 40 minutes of editing. The diagnosis was different every time. I expected the third round to recycle the same feedback. It didn't — it found structural patterns I hadn't noticed because I was focused on the words, not the shape of the paragraphs.

Diminishing returns are what to expect. On that same post, round one moved the score 36 points and round three moved it 5. Early rounds fix what's broken. Later rounds polish what's already working.

Stop chasing the score once the diagnosis feels recycled. If the priority fixes start repeating themes you've already addressed, your content is where it needs to be. Past that point, protecting your voice matters more than polishing every pattern the rubric can flag.

Worked Example: Our Own Post

This is our own content — a blog post from ForgeWorkflows, a sister brand run by the same team — scored and revised across three rounds. It illustrates the score, fix, rescore workflow. It does not validate the scale: one post, edited by the people who built the tool, is an example, not evidence.

Total improvement

+41pts

Rounds

3

Total time

~40min

Band progression

Weak→Comp.→Ready

Why Scores Differ from Other Tools

If you've run your content through an AI detector or an SEO tool, your Will AI Find It score may look different. That's because these tools answer different questions.

AI detectors and SEO tools answer questions Will AI Find It doesn't ask. A detector tells you whether your writing patterns resemble machine output — useful for compliance, but not for citability. An SEO tool scores keyword density, backlink authority, and topical coverage — factors built for Google ranking, which is a different question from whether a passage is worth quoting.

Will AI Find It sits in the gap between them. It scores the writing itself — personal voice, concrete data, structural clarity, emotional nuance, generic phrasing — the qualities the research on our methodology page associates with content an LLM quotes. Reading as human and being worth citing are different problems entirely.

Imagine a piece that scores 88% human on an AI detector and 37 on Will AI Find It. Neither tool is wrong. The content reads as human-written, but it lacks the authority, specificity, and voice that would give an AI search engine a reason to choose it over alternatives.

These tools are complementary. Use an AI detector to check if your content reads as human. Use an SEO tool to check if it's optimized for Google. Use Will AI Find It to check whether the writing gives an AI search engine a reason to quote it.