| 57.14% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 7 | | adverbTagCount | 1 | | adverbTags | | 0 | "Herrera said quietly [quietly]" |
| | dialogueSentences | 11 | | tagDensity | 0.636 | | leniency | 1 | | rawRatio | 0.143 | | effectiveRatio | 0.143 | |
| 93.42% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1520 | | totalAiIsmAdverbs | 2 | | found | | | highlights | | |
| 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) | |
| 73.68% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1520 | | totalAiIsms | 8 | | found | | | highlights | | 0 | "stomach" | | 1 | "streaming" | | 2 | "pulse" | | 3 | "footsteps" | | 4 | "echoed" | | 5 | "unraveling" | | 6 | "hulking" | | 7 | "loomed" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "blood ran cold" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 1 | | narrationSentences | 106 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 1 | | narrationSentences | 106 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 110 | | 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 | 1542 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 9 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 50 | | wordCount | 1439 | | uniqueNames | 14 | | maxNameDensity | 0.97 | | worstName | "Quinn" | | maxWindowNameDensity | 2 | | worstWindowName | "Quinn" | | discoveredNames | | Soho | 1 | | Detective | 1 | | Harlow | 1 | | Quinn | 14 | | Herrera | 12 | | Brewer | 1 | | Street | 1 | | Raven | 2 | | Nest | 3 | | Morris | 8 | | Camden | 1 | | Tube | 1 | | London | 1 | | Three | 3 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Herrera" | | 3 | "Raven" | | 4 | "Morris" |
| | places | | 0 | "Soho" | | 1 | "Brewer" | | 2 | "Street" | | 3 | "Camden" | | 4 | "London" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 68 | | glossingSentenceCount | 1 | | matches | | 0 | "sounded like gravel in a drum" |
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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 | 1542 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 110 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 40 | | mean | 38.55 | | std | 29.99 | | cv | 0.778 | | sampleLengths | | 0 | 35 | | 1 | 83 | | 2 | 17 | | 3 | 6 | | 4 | 88 | | 5 | 5 | | 6 | 64 | | 7 | 30 | | 8 | 63 | | 9 | 32 | | 10 | 7 | | 11 | 55 | | 12 | 64 | | 13 | 6 | | 14 | 5 | | 15 | 49 | | 16 | 62 | | 17 | 13 | | 18 | 10 | | 19 | 4 | | 20 | 129 | | 21 | 75 | | 22 | 71 | | 23 | 65 | | 24 | 68 | | 25 | 19 | | 26 | 10 | | 27 | 61 | | 28 | 35 | | 29 | 11 | | 30 | 20 | | 31 | 14 | | 32 | 71 | | 33 | 26 | | 34 | 17 | | 35 | 67 | | 36 | 31 | | 37 | 40 | | 38 | 4 | | 39 | 10 |
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| 88.71% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 5 | | totalSentences | 106 | | matches | | 0 | "been peeled" | | 1 | "been trained" | | 2 | "been found" | | 3 | "been trained" | | 4 | "was made" |
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| 0.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 10 | | totalVerbs | 237 | | matches | | 0 | "was looking" | | 1 | "was gaining " | | 2 | "was measuring" | | 3 | "was heading" | | 4 | "was seeing" | | 5 | "was selling" | | 6 | "was arguing" | | 7 | "was protecting " | | 8 | "was waiting" | | 9 | "was sitting" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 22 | | semicolonCount | 0 | | flaggedSentences | 15 | | totalSentences | 110 | | ratio | 0.136 | | matches | | 0 | "Tomás Herrera — former paramedic, struck off, associated with every name on the whiteboard in her incident room — cut left off Brewer Street and into an alley barely wide enough for his shoulders." | | 1 | "And tonight, finally, movement — Herrera slipping out the side door with a canvas bag clutched to his chest like a newborn, and the moment his warm brown eyes had found her across the street, he'd run." | | 2 | "Quinn was gaining — she had eighteen years of service in her legs and the sharp, punishing discipline of a woman who ran five miles every morning before the city woke — but he had desperation, and desperation was worth ten yards." | | 3 | "Three years and the official story still read like a lie, all those careful phrases — unexplained circumstances, case unresolved — covering something her superiors wouldn't say aloud." | | 4 | "The construction fencing around the old station entrance had been peeled back at one corner — freshly, she noted, the wire still bright at the tear." | | 5 | "Stairs went down into blackness, and from somewhere below came a sound that did not belong in an abandoned station — a low murmur, layered, almost like a crowd." | | 6 | "Torchlight caught old posters peeling from the walls — a smiling woman advertising tea, decades dead — and then the tunnel bent and the light changed." | | 7 | "Stalls lined the old platform edge and filled the track bed below, dozens of them, lit by lanterns that burned with flames the wrong color — green, violet, a white so pure it hurt." | | 8 | "Something at a far stall unfolded wings — actual wings, leathery and vast — and folded them again as casually as a shopper shifting a coat." | | 9 | "But Morris had written things in his last notebook, things she'd read a hundred times and dismissed a hundred times — they aren't hiding from us, they never needed to — and standing here with the wrong-colored firelight on her face, those words stopped sounding like a traumatized man's unraveling and started sounding like a report." | | 10 | "He was moving fast down the platform, the canvas bag still clutched to him, and he was arguing with a hulking figure blocking a gated archway — arguing and producing something from his pocket." | | 11 | "Behind that gate, she was certain, was the thing Herrera was protecting — the bag, the clique, the thread she'd been pulling for three years." | | 12 | "They smelled it on her, maybe — law, daylight, the ordinary world." | | 13 | "That this — the fence, the stairs, the long walk through the impossible market — had been a test she hadn't known she was sitting." | | 14 | "Quinn reached into her coat and pulled out the only thing she had that might pass for currency in a place like this — Morris's old warrant card, the one she'd carried for three years without ever once admitting why." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1422 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 46 | | adverbRatio | 0.03234880450070324 | | lyAdverbCount | 13 | | lyAdverbRatio | 0.009142053445850914 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 110 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 110 | | mean | 14.02 | | std | 12.05 | | cv | 0.86 | | sampleLengths | | 0 | 35 | | 1 | 7 | | 2 | 15 | | 3 | 34 | | 4 | 16 | | 5 | 2 | | 6 | 9 | | 7 | 7 | | 8 | 10 | | 9 | 3 | | 10 | 3 | | 11 | 8 | | 12 | 43 | | 13 | 37 | | 14 | 5 | | 15 | 16 | | 16 | 6 | | 17 | 42 | | 18 | 3 | | 19 | 10 | | 20 | 1 | | 21 | 16 | | 22 | 1 | | 23 | 14 | | 24 | 28 | | 25 | 20 | | 26 | 11 | | 27 | 4 | | 28 | 17 | | 29 | 7 | | 30 | 26 | | 31 | 5 | | 32 | 17 | | 33 | 7 | | 34 | 4 | | 35 | 19 | | 36 | 3 | | 37 | 3 | | 38 | 35 | | 39 | 6 | | 40 | 5 | | 41 | 17 | | 42 | 29 | | 43 | 3 | | 44 | 6 | | 45 | 24 | | 46 | 3 | | 47 | 3 | | 48 | 26 | | 49 | 3 |
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| 71.21% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 10 | | diversityRatio | 0.4818181818181818 | | totalSentences | 110 | | uniqueOpeners | 53 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 98 | | matches | | 0 | "Almost like music." | | 1 | "Then she thought of Morris's" | | 2 | "Somewhere behind her the market" |
| | ratio | 0.031 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 25 | | totalSentences | 98 | | matches | | 0 | "Her voice carried over the" | | 1 | "He didn't stop." | | 2 | "They never did." | | 3 | "He glanced back." | | 4 | "He was measuring her, the" | | 5 | "She'd pulled threads ever since," | | 6 | "He veered right, down toward" | | 7 | "She knew this geography." | | 8 | "Her hand went to the" | | 9 | "She knew it the way" | | 10 | "She ducked through the fence." | | 11 | "Her mind offered explanations the" | | 12 | "She spotted Herrera." | | 13 | "He was moving fast down" | | 14 | "She had no jurisdiction over" | | 15 | "She was forty-one years old," | | 16 | "She thought about turning around." | | 17 | "She genuinely considered it, weighed" | | 18 | "They smelled it on her," | | 19 | "She reached the archway." |
| | ratio | 0.255 | |
| 82.45% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 74 | | totalSentences | 98 | | matches | | 0 | "The rain came down in" | | 1 | "The man ahead of her" | | 2 | "Tomás Herrera — former paramedic," | | 3 | "Quinn followed without breaking stride," | | 4 | "Her voice carried over the" | | 5 | "He didn't stop." | | 6 | "They never did." | | 7 | "Men who run know something." | | 8 | "The alley spat them out" | | 9 | "Herrera's boots hammered the wet" | | 10 | "Quinn was gaining — she" | | 11 | "He glanced back." | | 12 | "He was measuring her, the" | | 13 | "The thought landed the way" | | 14 | "She'd pulled threads ever since," | | 15 | "He veered right, down toward" | | 16 | "She knew this geography." | | 17 | "The construction fencing around the" | | 18 | "Herrera ducked through without slowing." | | 19 | "Quinn stopped at the gap," |
| | ratio | 0.755 | |
| 51.02% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 98 | | matches | | 0 | "Even through the rain she" |
| | ratio | 0.01 | |
| 58.82% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 51 | | technicalSentenceCount | 6 | | matches | | 0 | "Three weeks of license plates and faces, of people who went into that dim little bar and sometimes didn't come out until the sky went grey, of a bookshelf that …" | | 1 | "Quinn was gaining — she had eighteen years of service in her legs and the sharp, punishing discipline of a woman who ran five miles every morning before the cit…" | | 2 | "Stairs went down into blackness, and from somewhere below came a sound that did not belong in an abandoned station — a low murmur, layered, almost like a crowd." | | 3 | "Stalls lined the old platform edge and filled the track bed below, dozens of them, lit by lanterns that burned with flames the wrong color — green, violet, a wh…" | | 4 | "People moved between them, and Quinn's trained eye, the eye that catalogued faces and threats in a single sweep, stumbled over what it was seeing." | | 5 | "The gatekeeper loomed over her, easily six and a half feet, his skin greyish in the lantern light, his mouth set in a line that suggested the conversation was a…" |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 7 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 59.09% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 4 | | fancyCount | 1 | | fancyTags | | 0 | "the gatekeeper repeated (repeat)" |
| | dialogueSentences | 11 | | tagDensity | 0.364 | | leniency | 0.727 | | rawRatio | 0.25 | | effectiveRatio | 0.182 | |