| 88.89% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 9 | | adverbTagCount | 1 | | adverbTags | | 0 | "Wills shaking like [like]" |
| | dialogueSentences | 0 | | tagDensity | 1 | | leniency | 1 | | rawRatio | 0.111 | | effectiveRatio | 0.111 | |
| 88.18% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1692 | | totalAiIsmAdverbs | 4 | | found | | | highlights | | 0 | "quickly" | | 1 | "very" | | 2 | "slowly" | | 3 | "gently" |
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| 100.00% | AI-ism character names | Target: 0 AI-default names (17 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 100.00% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1692 | | totalAiIsms | 0 | | found | (empty) | | highlights | (empty) | |
| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 0 | | maxInWindow | 0 | | found | (empty) | | highlights | (empty) | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 119 | | matches | (empty) | |
| 82.83% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 3 | | hedgeCount | 2 | | narrationSentences | 119 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 161 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 55 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1717 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 19 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 26 | | wordCount | 1412 | | uniqueNames | 13 | | maxNameDensity | 0.57 | | worstName | "Quinn" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Quinn" | | discoveredNames | | Harlow | 1 | | Quinn | 8 | | Mondays | 1 | | Wills | 1 | | Kowalski | 1 | | Adeyemi | 1 | | Eva | 3 | | Market | 2 | | Detective | 2 | | Ferris | 3 | | Bishopsgarth | 1 | | Camden | 1 | | Peckham | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Wills" | | 3 | "Kowalski" | | 4 | "Adeyemi" | | 5 | "Eva" | | 6 | "Ferris" |
| | places | | 0 | "Mondays" | | 1 | "Market" | | 2 | "Bishopsgarth" | | 3 | "Camden" | | 4 | "Peckham" |
| | globalScore | 1 | | windowScore | 1 | |
| 0.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 76 | | glossingSentenceCount | 5 | | matches | | 0 | "something like grease" | | 1 | "quite spit" | | 2 | "something like chalk, a pale grey circle abo" | | 3 | "looked like they had been rescued from a" | | 4 | "not quite a question" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1717 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 161 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 55 | | mean | 31.22 | | std | 33.46 | | cv | 1.072 | | sampleLengths | | 0 | 102 | | 1 | 36 | | 2 | 2 | | 3 | 3 | | 4 | 61 | | 5 | 61 | | 6 | 3 | | 7 | 25 | | 8 | 86 | | 9 | 3 | | 10 | 13 | | 11 | 3 | | 12 | 27 | | 13 | 54 | | 14 | 9 | | 15 | 3 | | 16 | 44 | | 17 | 8 | | 18 | 17 | | 19 | 90 | | 20 | 4 | | 21 | 1 | | 22 | 7 | | 23 | 47 | | 24 | 6 | | 25 | 24 | | 26 | 9 | | 27 | 73 | | 28 | 51 | | 29 | 2 | | 30 | 131 | | 31 | 13 | | 32 | 17 | | 33 | 3 | | 34 | 49 | | 35 | 1 | | 36 | 27 | | 37 | 14 | | 38 | 3 | | 39 | 23 | | 40 | 4 | | 41 | 22 | | 42 | 63 | | 43 | 2 | | 44 | 111 | | 45 | 10 | | 46 | 74 | | 47 | 91 | | 48 | 76 | | 49 | 6 |
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| 90.52% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 5 | | totalSentences | 119 | | matches | | 0 | "been smeared" | | 1 | "been marked " | | 2 | "being heard" | | 3 | "been rescued" | | 4 | "was notched" | | 5 | "been wrapped" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 3 | | totalVerbs | 239 | | matches | | 0 | "was already tucking" | | 1 | "was deciding" | | 2 | "was twitching" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 22 | | semicolonCount | 0 | | flaggedSentences | 20 | | totalSentences | 161 | | ratio | 0.124 | | matches | | 0 | "Detective Harlow Quinn counted them as she descended — forty-two, same as the station’s age — one hand on the black iron rail, her other resting flat against the tiled wall where a century’s worth of grime had been smeared into something like grease." | | 1 | "The air was cold in a way that had nothing to do with the weather above ground — a cellar cold, a stone cold that got into the lungs." | | 2 | "Not close — she had learned the worth of patience." | | 3 | "A man of his age and coat dying in a place like this should have brought some mess with him — belongings, litter, the usual archaeology of an end." | | 4 | "The tiles there had been marked — chalk, or something like chalk, a pale grey circle about a metre across, and inside it, faint now, a spiral." | | 5 | "There’s kids come down here sometimes, for the — you know." | | 6 | "And then she heard it — the small particular sound of a book being closed." | | 7 | "He knew I — he knew I’d know what some of this was.’" | | 8 | "She had seen it — a flat disc, dull as old pewter, lying in the cup of the dead man’s palm, half-hidden by the fold of his fingers." | | 9 | "That’s the — that’s the rule." | | 10 | "Which means the night before the move — that’s when they close the doors and count the stock and settle the debts." | | 11 | "So it’s — I know how it sounds." | | 12 | "PC Ferris, I’d like the platform photographed from the east stair — the whole run, not just the immediate scene." | | 13 | "I — no." | | 14 | "In between — three hours of a dead man in the dark." | | 15 | "Along the east stair the SOCOs had left their prints, and she had left hers, and Ferris had left his, and behind the body there was a single trail of prints coming in from the tunnel — not from the stair." | | 16 | "Not boots — a soft sole, a wrap of some kind, or a foot that had been wrapped." | | 17 | "And then she thought of the east stair, which she had come down with one hand on the wall because the iron was wet — forty-two steps of wet, and a landing, and a maintenance door that let in the Camden rain." | | 18 | "She stood, and took from her coat pocket the small brass compass she had bought — she would not say from whom, she would not say for how much — and held it flat on her palm." | | 19 | "And bring me the cleaner again — not to shake." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 103 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 2 | | adverbRatio | 0.019417475728155338 | | lyAdverbCount | 1 | | lyAdverbRatio | 0.009708737864077669 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 161 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 161 | | mean | 10.66 | | std | 10.25 | | cv | 0.961 | | sampleLengths | | 0 | 19 | | 1 | 44 | | 2 | 12 | | 3 | 27 | | 4 | 23 | | 5 | 2 | | 6 | 4 | | 7 | 7 | | 8 | 2 | | 9 | 3 | | 10 | 7 | | 11 | 4 | | 12 | 21 | | 13 | 29 | | 14 | 27 | | 15 | 12 | | 16 | 4 | | 17 | 18 | | 18 | 3 | | 19 | 2 | | 20 | 8 | | 21 | 7 | | 22 | 8 | | 23 | 2 | | 24 | 10 | | 25 | 7 | | 26 | 2 | | 27 | 5 | | 28 | 8 | | 29 | 29 | | 30 | 16 | | 31 | 7 | | 32 | 3 | | 33 | 9 | | 34 | 4 | | 35 | 3 | | 36 | 4 | | 37 | 11 | | 38 | 8 | | 39 | 4 | | 40 | 11 | | 41 | 27 | | 42 | 16 | | 43 | 9 | | 44 | 3 | | 45 | 10 | | 46 | 5 | | 47 | 11 | | 48 | 18 | | 49 | 2 |
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| 59.83% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 17 | | diversityRatio | 0.422360248447205 | | totalSentences | 161 | | uniqueOpeners | 68 | |
| 64.72% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 103 | | matches | | 0 | "Somewhere ahead, a scene-of-crime lamp" | | 1 | "Only one key, signed out" |
| | ratio | 0.019 | |
| 72.43% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 38 | | totalSentences | 103 | | matches | | 0 | "We’ve kept it tight." | | 1 | "His mouth was open." | | 2 | "He’s upstairs with Wills, shaking" | | 3 | "She looked first at what" | | 4 | "It’s in the" | | 5 | "We came in through the" | | 6 | "She let her eyes travel" | | 7 | "Her knees complained." | | 8 | "She had her satchel strap" | | 9 | "He’s a friend of a" | | 10 | "He knew I — he" | | 11 | "She didn’t touch." | | 12 | "She had seen it —" | | 13 | "She had put it down" | | 14 | "You need one to get" | | 15 | "They give you a token" | | 16 | "He didn’t give it" | | 17 | "He was here last night," | | 18 | "It’s their law, not" | | 19 | "She tucked her hair again." |
| | ratio | 0.369 | |
| 100.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 69 | | totalSentences | 103 | | matches | | 0 | "The stairs down to the" | | 1 | "Detective Harlow Quinn counted them" | | 2 | "The tiles were a sickly" | | 3 | "We’ve kept it tight." | | 4 | "Quinn stepped past him onto" | | 5 | "The ceiling pressed low." | | 6 | "A dead train line ran" | | 7 | "The air was cold in" | | 8 | "The body lay on its" | | 9 | "His mouth was open." | | 10 | "He’s upstairs with Wills, shaking" | | 11 | "She looked first at what" | | 12 | "A man of his age" | | 13 | "The floor around him was" | | 14 | "It’s in the" | | 15 | "We came in through the" | | 16 | "She let her eyes travel" | | 17 | "The tiles there had been" | | 18 | "Someone had scrubbed at it" | | 19 | "Her knees complained." |
| | ratio | 0.67 | |
| 48.54% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 103 | | matches | | 0 | "Now it went still, and" |
| | ratio | 0.01 | |
| 77.92% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 44 | | technicalSentenceCount | 4 | | matches | | 0 | "The air was cold in a way that had nothing to do with the weather above ground — a cellar cold, a stone cold that got into the lungs." | | 1 | "Eva Kowalski had come up the east stair without being heard, which was a trick she seemed to manage by being small and apologetic and wearing rubber-soled boots…" | | 2 | "Eva came forward, skirting the SOCO tape, and crouched where Quinn had crouched, her satchel swinging against her hip." | | 3 | "And then she thought of the east stair, which she had come down with one hand on the wall because the iron was wet — forty-two steps of wet, and a landing, and …" |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 9 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |