# Paired-phrase coordination 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: phrasal-coordination-habit - Category: Structural and syntactic (structural) - Subcategory: coordination - Also known as: noun-pair habit, relentless X and Y pairing - Status: Active. Currently signals low-effort writing. - Severity: low - Evidence grade: peer-reviewed (a published study measures the pattern) - Languages: en - Added: 2026-08-15 - Updated: 2026-08-17 - Page: https://feedsquad.com/ai-tells/phrasal-coordination-habit ## Description Nouns and adjectives arrive in pairs where one member would carry the whole meaning. Reinhart and colleagues measure phrasal coordination at 1.9 times the human rate in GPT-4o output, with a Cohen's d of 0.81, again a body-level table value. Pairs are two members. The three-member version belongs to the rule-of-three entry, and the two patterns do not overlap. ## Why it reads as machine-written A pair looks like care and costs nothing to produce. The second member is usually a near-synonym of the first, so the sentence lengthens without becoming more exact. Read a paragraph back and count how many pairs survive the deletion of one member with no loss of meaning. In most low-effort drafts the answer is none. ## Detection Type: statistical (a measured metric against a threshold with a stated basis) Metric: coordinated-noun-or-adjective-pairs-per-1000-words Threshold basis: > No threshold ships. The 1.9 times ratio is a body-level comparison between corpora, and legal and ceremonial registers sit far above any line that could be drawn from it. The count is a FeedSquad review trigger for a reread, not a measurement with a published human baseline behind it. ## Examples Constructed specimens. Written for this index. Never quoted from anyone's posts. ### Specimen 1 Before, exhibiting the tell: > The platform provides clarity and insight into your data, and gives teams the tools and resources they need for informed and confident decisions. It is designed to be simple and intuitive, so that everyday users and seasoned analysts alike can find what they need. The result is a smoother and more consistent workflow, and a team that feels supported and equipped at every stage. Adoption is quick and low-risk, and the value shows up early and keeps showing up. After, repaired: > The platform shows which of your posts drew replies from accounts you do not already follow. It ranks them by reply count and exports the list as a CSV. Note: Seven pairs went out and one checkable behaviour came in. Delete the second member of every pair and the passage says exactly what it said before, which is nothing that could be tested against the product. ## False positives Who legitimately writes this way. Legal drafting runs on doublets, and aid and abet, terms and conditions, null and void are fixed pairs that a lawyer cannot unpick without changing what the clause does. Liturgy, ceremonial writing and older English pair by convention. The check is deletion: remove one member and see whether any meaning goes with it. If meaning is lost, the writer is using a term of art. If nothing is lost, the pair is decoration, and a page full of decoration is the signal. ## Model attribution Measured in GPT-4o output. No vendor documentation names the habit, and no study attributes it to a specific model family. ## Sources 1. Reinhart et al., Do LLMs write like humans? PNAS 122(8) (arXiv:2410.16107) https://arxiv.org/abs/2410.16107 (tier: peer-reviewed; accessed 2026-08-14) 2. vale-ai-tells, 111 machine-checkable rules https://github.com/tbhb/vale-ai-tells (tier: community; accessed 2026-08-14) ## Status history Ids are permanent. A retired tell keeps its id and its page. - 2026-08-15, Active: Measured at 1.9 times the human rate in 2024-era model output and carried by vale-ai-tells as a checkable rule. No published work reports the habit fading. ## 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.