| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 6 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 13 | | tagDensity | 0.462 | | leniency | 0.923 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1562 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 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) | |
| 80.79% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1562 | | totalAiIsms | 6 | | found | | | highlights | | 0 | "clandestine" | | 1 | "flickered" | | 2 | "electric" | | 3 | "silence" | | 4 | "pulsed" | | 5 | "etched" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "air was thick with" | | count | 1 |
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| | highlights | | 0 | "The air was thick with" |
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| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 1 | | narrationSentences | 119 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 3 | | hedgeCount | 0 | | narrationSentences | 119 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 127 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 45 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 1 | | markdownWords | 2 | | totalWords | 1577 | | ratio | 0.001 | | matches | | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 8 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 62 | | wordCount | 1449 | | uniqueNames | 30 | | maxNameDensity | 0.76 | | worstName | "Quinn" | | maxWindowNameDensity | 2 | | worstWindowName | "Quinn" | | discoveredNames | | Soho | 3 | | Quinn | 11 | | Greek | 1 | | Street | 2 | | Met | 1 | | Herrera | 5 | | Raven | 1 | | Nest | 1 | | Saint | 2 | | Christopher | 2 | | Silas | 2 | | Bateman | 1 | | Charing | 1 | | Cross | 1 | | Road | 1 | | Morris | 5 | | Deptford | 1 | | Independent | 1 | | Office | 1 | | Police | 1 | | Conduct | 1 | | Underground | 1 | | Seville | 1 | | London | 1 | | Tube | 2 | | Camden | 1 | | Veil | 1 | | Market | 1 | | Tomás | 5 | | Procedure | 4 |
| | persons | | 0 | "Quinn" | | 1 | "Herrera" | | 2 | "Raven" | | 3 | "Saint" | | 4 | "Christopher" | | 5 | "Silas" | | 6 | "Morris" | | 7 | "Tube" | | 8 | "Market" | | 9 | "Tomás" | | 10 | "Procedure" |
| | places | | 0 | "Soho" | | 1 | "Greek" | | 2 | "Street" | | 3 | "Bateman" | | 4 | "Charing" | | 5 | "Cross" | | 6 | "Road" | | 7 | "Deptford" | | 8 | "Seville" | | 9 | "London" |
| | globalScore | 1 | | windowScore | 1 | |
| 95.65% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 92 | | glossingSentenceCount | 2 | | matches | | 0 | "smelled like incense and iron and fried fo" | | 1 | "looked like bottled shadows" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.634 | | wordCount | 1577 | | matches | | 0 | "not to a service tunnel but to a decommissioned platform" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 127 | | matches | | 0 | "underlined that phrase" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 49 | | mean | 32.18 | | std | 27.38 | | cv | 0.851 | | sampleLengths | | 0 | 9 | | 1 | 71 | | 2 | 4 | | 3 | 64 | | 4 | 9 | | 5 | 72 | | 6 | 52 | | 7 | 20 | | 8 | 15 | | 9 | 10 | | 10 | 87 | | 11 | 7 | | 12 | 37 | | 13 | 3 | | 14 | 63 | | 15 | 46 | | 16 | 118 | | 17 | 20 | | 18 | 15 | | 19 | 59 | | 20 | 21 | | 21 | 18 | | 22 | 23 | | 23 | 53 | | 24 | 5 | | 25 | 25 | | 26 | 7 | | 27 | 39 | | 28 | 6 | | 29 | 40 | | 30 | 3 | | 31 | 6 | | 32 | 86 | | 33 | 3 | | 34 | 49 | | 35 | 67 | | 36 | 31 | | 37 | 21 | | 38 | 27 | | 39 | 46 | | 40 | 72 | | 41 | 14 | | 42 | 32 | | 43 | 2 | | 44 | 29 | | 45 | 10 | | 46 | 50 | | 47 | 7 | | 48 | 4 |
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| 84.62% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 7 | | totalSentences | 119 | | matches | | 0 | "been knocked" | | 1 | "been used" | | 2 | "been locked" | | 3 | "been boarded" | | 4 | "been used" | | 5 | "being logged" | | 6 | "been bricked" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 3 | | totalVerbs | 240 | | matches | | 0 | "was standing" | | 1 | "was pushing" | | 2 | "was still running" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 13 | | semicolonCount | 0 | | flaggedSentences | 8 | | totalSentences | 127 | | ratio | 0.063 | | matches | | 0 | "The window - a narrow hopper that shouldn't have existed, given the building's footprint - was open to the rain." | | 1 | "The worn leather watch on her left wrist ticked loud against her skin - she never could stand a smartwatch, never trusted anything that needed charging to tell you the time." | | 2 | "A rusted gate that should have been locked was standing open, its padlock melted - not cut, melted - into a slug of metal on the ground." | | 3 | "He turned the bone token over in his fingers - she hadn't seen him pick it up - and pressed it against the dark." | | 4 | "An abandoned Tube station beneath Camden - except this was still Soho, she had not run four kilometers north, not in three minutes." | | 5 | "People - not all people - haggled over jars that moved on their own, over bundles of herbs that smoked without heat, over blades etched with script." | | 6 | "If Herrera disappeared in there, she lost her only thread to the clique she'd been chasing for six months - the neat, pretty kids in good coats who never got sick, never got hurt, and left ash and bitemarks and missing persons around them like litter." | | 7 | "She checked her watch by habit - 22:17 - and then took her hand off the rusted doorframe and stepped fully onto the boards." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 209 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 2 | | adverbRatio | 0.009569377990430622 | | lyAdverbCount | 1 | | lyAdverbRatio | 0.004784688995215311 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 127 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 127 | | mean | 12.42 | | std | 8.95 | | cv | 0.721 | | sampleLengths | | 0 | 9 | | 1 | 25 | | 2 | 24 | | 3 | 8 | | 4 | 14 | | 5 | 4 | | 6 | 3 | | 7 | 17 | | 8 | 2 | | 9 | 34 | | 10 | 6 | | 11 | 2 | | 12 | 9 | | 13 | 27 | | 14 | 11 | | 15 | 28 | | 16 | 6 | | 17 | 10 | | 18 | 9 | | 19 | 15 | | 20 | 6 | | 21 | 12 | | 22 | 12 | | 23 | 8 | | 24 | 9 | | 25 | 6 | | 26 | 7 | | 27 | 3 | | 28 | 5 | | 29 | 19 | | 30 | 12 | | 31 | 25 | | 32 | 6 | | 33 | 20 | | 34 | 7 | | 35 | 20 | | 36 | 17 | | 37 | 3 | | 38 | 3 | | 39 | 22 | | 40 | 4 | | 41 | 3 | | 42 | 31 | | 43 | 22 | | 44 | 14 | | 45 | 10 | | 46 | 9 | | 47 | 26 | | 48 | 10 | | 49 | 42 |
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| 67.98% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 12 | | diversityRatio | 0.4645669291338583 | | totalSentences | 127 | | uniqueOpeners | 59 | |
| 90.91% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 110 | | matches | | 0 | "Dimly lit, smelling of old" | | 1 | "Once from a fourteen-year-old pickpocket" | | 2 | "Once from Morris, drunk on" |
| | ratio | 0.027 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 27 | | totalSentences | 110 | | matches | | 0 | "Her boots cut through it" | | 1 | "He'd been clean since, off-the-books," | | 2 | "She'd been watching The Raven's" | | 3 | "He hadn't come out the" | | 4 | "She'd given it ten minutes," | | 5 | "She'd pushed the shelf herself." | | 6 | "It swung inward on silent" | | 7 | "He ran when he saw" | | 8 | "He didn't stop." | | 9 | "He cut left into Bateman" | | 10 | "Her breath sawed." | | 11 | "He hit Charing Cross Road" | | 12 | "She had never forgotten the" | | 13 | "He was at the bottom," | | 14 | "he gasped, his accent thicker" | | 15 | "she said, keeping her voice" | | 16 | "Her bearing held, military precision" | | 17 | "It was warm, and it" | | 18 | "It smelled like incense and" | | 19 | "He turned the bone token" |
| | ratio | 0.245 | |
| 100.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 77 | | totalSentences | 110 | | matches | | 0 | "The rain had turned Soho" | | 1 | "Harlow Quinn kept her head" | | 2 | "Water sheeted off the awnings" | | 3 | "Her boots cut through it" | | 4 | "He'd been clean since, off-the-books," | | 5 | "She'd been watching The Raven's" | | 6 | "The bar sat low between" | | 7 | "RAVEN'S NEST, the N half" | | 8 | "He hadn't come out the" | | 9 | "She'd given it ten minutes," | | 10 | "Walls covered with old maps" | | 11 | "The barman, Silas, hadn't looked" | | 12 | "A line of damp footprints" | | 13 | "Quinn had drawn her warrant" | | 14 | "Silas had finally looked at" | | 15 | "She'd pushed the shelf herself." | | 16 | "It swung inward on silent" | | 17 | "Herrera's chair had been knocked" | | 18 | "The window - a narrow" | | 19 | "He ran when he saw" |
| | ratio | 0.7 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 4 | | totalSentences | 110 | | matches | | 0 | "Now he was thirty meters" | | 1 | "If she went in there," | | 2 | "If Herrera disappeared in there," | | 3 | "If she didn't go in," |
| | ratio | 0.036 | |
| 81.28% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 58 | | technicalSentenceCount | 5 | | matches | | 0 | "Harlow Quinn kept her head down and her eyes up, the way they taught you when you walked a beat that didn't want you there." | | 1 | "Walls covered with old maps and black-and-white photographs that had nothing to do with Soho." | | 2 | "The window - a narrow hopper that shouldn't have existed, given the building's footprint - was open to the rain." | | 3 | "A service stair, almost invisible behind a pile of black bin bags, leading down to a maintenance door for the Underground that hadn't been used since the 80s." | | 4 | "Once from a fourteen-year-old pickpocket who had sworn he sold a tooth there that whispered." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 6 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 4 | | fancyCount | 3 | | fancyTags | | 0 | "Responding to a call in Deptford (respond)" | | 1 | "he gasped (gasp)" | | 2 | "last birthday saying (last birthday saying)" |
| | dialogueSentences | 13 | | tagDensity | 0.308 | | leniency | 0.615 | | rawRatio | 0.75 | | effectiveRatio | 0.462 | |