# Uniform sentence cadence Part of [The AI Tells Index](https://feedsquad.com/ai-tells). A tell signals low effort. It does not identify an author. Skilled writers produce every shape listed here, some of them daily, and automated detectors misread those writers for it at rates measured above 60 percent on non-native English prose. Nothing in this index proves that a machine wrote anything. Read an entry as one piece of evidence to weigh against the false-positive notes printed beside it. ## Facts - Id: sentence-cadence-uniformity - Category: Structural and syntactic (structural) - Subcategory: cadence - Also known as: isocolon cadence, metronome prose, sentence-length CV - Status: Contested. Credible people dispute that this signals anything at all. - Severity: medium - Evidence grade: corroborated (named independently by multiple credible secondary sources) - Languages: en - Added: 2026-08-15 - Updated: 2026-08-15 - Page: https://feedsquad.com/ai-tells/sentence-cadence-uniformity ## Description Sentence lengths sit in a narrow band and the prose keeps time. This entry reports a coefficient of variation over sentence word counts, calls it that, and stops. The widely repeated claim that human writing scores between 0.65 and 0.85 on burstiness is arithmetically impossible under the Goh and Barabasi formula it cites. Solving that formula for those values needs a sentence-length standard deviation between 4.7 and 12.3 times the mean; at a mean of 18 words that is a standard deviation of 85 to 222 words. Real English prose runs a coefficient of variation of roughly 0.4 to 0.8, which gives a negative value under the same formula. The circulated numbers are coefficients of variation wearing the wrong name. ## Why it reads as machine-written Even cadence is what comes out when nothing in the draft pushes back. Human paragraphs tend to carry one sentence that ran long because the thought did, and one that stopped early because the writer lost patience with it. The measurement is worth reporting and worthless as a verdict, which is why this entry ships contested and with no number attached. ## Detection Type: statistical (a measured metric against a threshold with a stated basis) Metric: sentence-length-coefficient-of-variation Threshold basis: > No threshold ships, and that is the finding. No published corpus baseline for human sentence-length coefficient of variation exists to anchor one. Munoz-Ortiz and colleagues report that human texts exhibit more scattered sentence length distributions than the output of six models, and publish no mean, no standard deviation and no coefficient for either side. Any figure quoted as burstiness in the range 0.65 to 0.85 is incoherent under the formula it cites, so this entry publishes the arithmetic instead of a cutoff. Report the coefficient, label it a coefficient, and use a low value as a prompt to read the draft aloud. That is a FeedSquad review trigger. ## Examples Constructed specimens. Written for this index. Never quoted from anyone's posts. ### Specimen 1 Before, exhibiting the tell: > The team reviewed the numbers on Monday. The results were better than the previous quarter. The marketing spend stayed flat across every channel. The new pricing page brought in more signups than before. After, repaired: > The team read the numbers on Monday. Signups were up 14 percent on the previous quarter with marketing spend flat, and almost all of the lift traced back to one change: the pricing page now shows the annual price first. Nobody had expected that. Note: Four sentences of near-identical length became three of very different lengths, and the repair adds the figure and the cause. Figures in this repair are invented for the specimen. ## False positives Who legitimately writes this way. Plain-language mandates produce short even sentences on purpose, and any writer working to a government or medical readability standard will land in a narrow band by policy rather than by habit. Second-language writers drawing on a narrow set of lexical bundles produce the same shape, and so does anyone composing on a phone. A low coefficient is a fact about the sentences and says nothing about who assembled them. Read the draft aloud before drawing any conclusion from the number. ## Model attribution No study reports a per-model coefficient of variation. Published work on stylistic homogeneity compares populations of texts rather than single documents, and the homogeneity finding does not convert into a per-document statistic. ## Sources 1. El Attar et al., lexical richness robustness across 27 models (arXiv:2606.04177) https://arxiv.org/abs/2606.04177 (tier: primary-doc; accessed 2026-08-14) 2. Pudasaini et al., Why AI-Generated Text Detection Fails: Evidence from Explainable AI Beyond Benchmark Accuracy (arXiv:2603.23146) https://arxiv.org/abs/2603.23146 (tier: primary-doc; accessed 2026-08-14) 3. vale-ai-tells, 111 machine-checkable rules https://github.com/tbhb/vale-ai-tells (tier: community; accessed 2026-08-14) 4. Munoz-Ortiz, Gomez-Rodriguez, Vilares: Contrasting Linguistic Patterns in Human and LLM-Generated News Text (arXiv:2308.09067) https://arxiv.org/abs/2308.09067 (tier: peer-reviewed; accessed 2026-08-15) 5. Russell, Karpinska, Iyyer: People who frequently use ChatGPT for writing tasks are accurate and robust detectors of AI-generated text (ACL 2025) https://aclanthology.org/2025.acl-long.267/ (tier: peer-reviewed; accessed 2026-08-14) ## Status history Ids are permanent. A retired tell keeps its id and its page. - 2026-08-15, Contested: Ships contested. The direction of effect has published support, no human baseline exists to set a line, and the number most often attached to this measurement is arithmetically impossible under the formula it is credited to. Detector work also shows structural features of this kind carrying corpus artifacts rather than authorship. ## License CC BY 4.0. https://creativecommons.org/licenses/by/4.0/ Attribution: The AI Tells Index, feedsquad.com/ai-tells Reuse the data, including commercially. Keep the attribution line. --- Dataset version 1.0.0. Schema version 1. Part of [FeedSquad](https://feedsquad.com). Built by [Herman Foundry](https://hermanfoundry.com) from Levi, Finnish Lapland.