# Manufactured aphorism molds 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: aphorism-molds - Category: Rhetorical and discourse (rhetorical) - Subcategory: reply-register - Also known as: X is what keeps A from becoming B, is measured by how, as a hypothesis, not a promise - Status: Active. Currently signals low-effort writing. - Severity: high - Evidence grade: community-observed (named by practitioners, no formal measurement exists) - Languages: en - Added: 2026-08-15 - Updated: 2026-08-17 - Page: https://feedsquad.com/ai-tells/aphorism-molds ## Description Reply-sized wisdom cast from a small set of reusable frames. slop-lint catalogues the molds by surface string and states its method: each one was screened against roughly 60,000 words of human baseline for zero false positives, and required two independent sightings before it shipped. That method is the entire basis for the grade here, and it is one repository, so the entry stays community-observed. The frames produce sentences with the shape of earned insight that can be filled with any two nouns. ## Why it reads as machine-written A reply that has to sound wise in twenty words has two options. Say a specific thing, which requires knowing one, or reach for a frame that always produces a finished sentence. Frames win on cost every time. Recurrence is the signal: one aphorism is a writer having a line, the same mold three times in a month is a generator running. ## Detection Type: deterministic (a regular expression, run as written) Scope: sentence ECMAScript regular expression. The build validator compiles it and tests it against this entry's own specimens. ```regex \b(?:is\s+what\s+keeps\s+[^.;!?\n]{1,40}\s+from\s+becoming\b|is\s+measured\s+by\s+how\s+(?:well|quickly|fast|often|much|little|far)\b|as\s+a\s+hypothesis,\s+not\s+a\s+promise\b|lowers?\s+[^.;!?\n]{1,30}\s+without\s+lowering\b) ``` Flags: gi ## Examples Constructed specimens. Written for this index. Never quoted from anyone's posts. ### Specimen 1 Before, exhibiting the tell: > Trust is what keeps a team from becoming a queue. Every company says it values trust, and almost none of them can point to something they did last quarter to earn any. The teams that get this right rarely talk about it. The ones that talk about it constantly are usually the ones who lost it a while ago. After, repaired: > We stopped writing tickets for anything under ten minutes in March. Queue time halved, and two people said they finally knew what everyone else was working on. Note: Figures in this repair are invented for the specimen. ### Specimen 2 Before, exhibiting the tell: > Culture is measured by how quickly bad news travels. Every leadership team believes its own culture is open, and most of them have never once tested the claim. Organisations that handle bad news well tend to handle everything else well too. It is a simple idea and a hard one to live with. After, repaired: > The outage on 12 May reached the whole company in nineteen minutes because the on-call channel is public. The one in January took two days and three forwarded emails. Note: Figures in this repair are invented for the specimen. ## False positives Who legitimately writes this way. Professional aphorists exist, and so do quote-card writers, keynote speakers, copywriters and the authors of management books, all of whom are paid to produce exactly these sentences. Proverbs in every language use the same frames, and a writer raised on them will reach for one without thinking. The discriminator is recurrence rather than presence: check whether the same mold appears across a body of posts from one account, and whether the two nouns in the frame could be swapped for any other pair without changing what the sentence claims. A line that only works with its own nouns was written by someone who meant it. ## Model attribution Unattributed by family. slop-lint records the molds as assistant reply-register output and names no product, and its README documents the discovery method rather than a per-model rate. ## Platform notes - x: The reply register is where slop-lint found these. X routes reply spam and its llm_slop_post label to the same handling, and reply-guy behaviour is the archetypal target named in the public algorithm repository. - linkedin: Quote-card posts and comment replies are the native home of the molds on that surface. LinkedIn shipped a user-facing report control for suspected slop in July 2026 whose signal feeds ranking, and no LinkedIn document names any sentence shape. ## Sources 1. slop-lint, social-reply-register molds https://github.com/eric-sabe/slop-lint (tier: community; accessed 2026-08-14) ## Status history Ids are permanent. A retired tell keeps its id and its page. - 2026-08-15, Active: Opened as active at high severity. slop-lint screened each mold against roughly 60,000 words of human baseline and required two independent sightings before shipping it, which is a stronger method than any other list in this category offers. It is still a single repository, so the grade stays community-observed. ## 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.