| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 8 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 47 | | tagDensity | 0.17 | | leniency | 0.34 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 86.16% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1807 | | totalAiIsmAdverbs | 5 | | found | | | highlights | | 0 | "slowly" | | 1 | "really" | | 2 | "slightly" | | 3 | "carefully" |
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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) | |
| 66.80% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1807 | | totalAiIsms | 12 | | found | | | highlights | | 0 | "unsettled" | | 1 | "velvet" | | 2 | "shattered" | | 3 | "etched" | | 4 | "quivered" | | 5 | "trembled" | | 6 | "perfect" | | 7 | "structure" | | 8 | "magnetic" | | 9 | "silence" | | 10 | "warmth" |
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| 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 | 135 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 1 | | narrationSentences | 135 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 174 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 41 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1812 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 8 | | unquotedAttributions | 0 | | matches | (empty) | |
| 50.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 50 | | wordCount | 1373 | | uniqueNames | 17 | | maxNameDensity | 1.53 | | worstName | "Quinn" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Quinn" | | discoveredNames | | Camden | 2 | | Town | 1 | | Detective | 1 | | Harlow | 1 | | Quinn | 21 | | Transport | 1 | | London | 1 | | Victorian | 2 | | Amara | 1 | | Osei | 7 | | Morris | 4 | | Rephrased | 1 | | Kowalski | 1 | | British | 1 | | Museum | 1 | | Eva | 3 | | Whitechapel | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Osei" | | 3 | "Morris" | | 4 | "Kowalski" | | 5 | "Eva" |
| | places | | 0 | "Camden" | | 1 | "Town" | | 2 | "London" | | 3 | "British" | | 4 | "Whitechapel" |
| | globalScore | 0.735 | | windowScore | 0.5 | |
| 94.44% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 90 | | glossingSentenceCount | 2 | | matches | | 0 | "competent, and visibly unsettled by the lo" | | 1 | "something like it once before" |
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| 89.62% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 2 | | per1kWords | 1.104 | | wordCount | 1812 | | matches | | 0 | "not cardinal directions, not any navigational system she recognized, but symbols" | | 1 | "not any navigational system she recognized, but symbols" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 174 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 69 | | mean | 26.26 | | std | 23.27 | | cv | 0.886 | | sampleLengths | | 0 | 74 | | 1 | 52 | | 2 | 52 | | 3 | 40 | | 4 | 53 | | 5 | 9 | | 6 | 3 | | 7 | 38 | | 8 | 69 | | 9 | 5 | | 10 | 19 | | 11 | 57 | | 12 | 4 | | 13 | 54 | | 14 | 8 | | 15 | 33 | | 16 | 2 | | 17 | 24 | | 18 | 63 | | 19 | 5 | | 20 | 1 | | 21 | 18 | | 22 | 17 | | 23 | 24 | | 24 | 15 | | 25 | 73 | | 26 | 32 | | 27 | 4 | | 28 | 12 | | 29 | 2 | | 30 | 72 | | 31 | 63 | | 32 | 19 | | 33 | 27 | | 34 | 15 | | 35 | 5 | | 36 | 4 | | 37 | 74 | | 38 | 37 | | 39 | 6 | | 40 | 5 | | 41 | 38 | | 42 | 6 | | 43 | 39 | | 44 | 12 | | 45 | 3 | | 46 | 59 | | 47 | 67 | | 48 | 3 | | 49 | 12 |
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| 84.47% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 8 | | totalSentences | 135 | | matches | | 0 | "been closed" | | 1 | "been upended" | | 2 | "were shattered" | | 3 | "was lined" | | 4 | "were curled" | | 5 | "was etched" | | 6 | "being shifted" | | 7 | "was sized" |
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| 81.48% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 4 | | totalVerbs | 225 | | matches | | 0 | "wasn't standing" | | 1 | "was writing" | | 2 | "was looking" | | 3 | "was watching" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 13 | | semicolonCount | 0 | | flaggedSentences | 11 | | totalSentences | 174 | | ratio | 0.063 | | matches | | 0 | "Eighteen years on the job had worn grooves in her joints the way water wears grooves in limestone — slowly, invisibly, until one day the whole thing threatens to give." | | 1 | "A length of velvet — deep burgundy, eaten by moths — hung from a brass rod." | | 2 | "Someone had swept them recently — within the last week, she'd guess, based on the thin film of dust that had accumulated since." | | 3 | "She moved past the body — noting the way the dead man's coat had ridden up, revealing a belt with an empty leather pouch on the hip — and followed the far wall." | | 4 | "She circled it the way she circled every scene — methodically, widening her orbit each time, letting the room speak before she started asking questions." | | 5 | "Its casing was etched with markings — not cardinal directions, not any navigational system she recognized, but symbols that matched the ones carved into the shelving." | | 6 | "They were too high — nearly eight feet up." | | 7 | "His hands were clean — preternaturally so, given the filth of the surrounding environment." | | 8 | "A research assistant at the British Museum — someone Morris had introduced her to, back when Morris was alive and working angles Quinn hadn't understood at the time." | | 9 | "Osei was watching her with an expression Quinn recognized from every junior officer she'd ever partnered with — the look that said the case had just crossed a line they hadn't known existed." | | 10 | "Something else had caught her eye — on the dead man's belt, the empty leather pouch." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1365 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 46 | | adverbRatio | 0.0336996336996337 | | lyAdverbCount | 18 | | lyAdverbRatio | 0.013186813186813187 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 174 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 174 | | mean | 10.41 | | std | 8.19 | | cv | 0.786 | | sampleLengths | | 0 | 15 | | 1 | 6 | | 2 | 10 | | 3 | 12 | | 4 | 31 | | 5 | 11 | | 6 | 12 | | 7 | 9 | | 8 | 20 | | 9 | 2 | | 10 | 17 | | 11 | 3 | | 12 | 30 | | 13 | 26 | | 14 | 10 | | 15 | 4 | | 16 | 11 | | 17 | 8 | | 18 | 4 | | 19 | 2 | | 20 | 14 | | 21 | 7 | | 22 | 3 | | 23 | 4 | | 24 | 9 | | 25 | 3 | | 26 | 38 | | 27 | 9 | | 28 | 6 | | 29 | 4 | | 30 | 17 | | 31 | 13 | | 32 | 6 | | 33 | 14 | | 34 | 5 | | 35 | 19 | | 36 | 6 | | 37 | 16 | | 38 | 8 | | 39 | 11 | | 40 | 3 | | 41 | 13 | | 42 | 4 | | 43 | 8 | | 44 | 30 | | 45 | 16 | | 46 | 8 | | 47 | 12 | | 48 | 21 | | 49 | 2 |
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| 76.25% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 4 | | diversityRatio | 0.47126436781609193 | | totalSentences | 174 | | uniqueOpeners | 82 | |
| 84.03% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 119 | | matches | | 0 | "Just a pair of scorched" | | 1 | "Almost like a heartbeat." | | 2 | "Then Eva's voice came back," |
| | ratio | 0.025 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 34 | | totalSentences | 119 | | matches | | 0 | "She was three levels beneath" | | 1 | "Her knees complained." | | 2 | "She was young, competent, and" | | 3 | "She leaned closer to the" | | 4 | "His fingernails were black." | | 5 | "She'd seen something like it" | | 6 | "She sealed that thought behind" | | 7 | "It wasn't a tunnel, not" | | 8 | "It was a room." | | 9 | "She didn't touch it." | | 10 | "She walked to the center" | | 11 | "She moved past the body" | | 12 | "She nudged the door wider" | | 13 | "She circled it the way" | | 14 | "His fingers were curled around" | | 15 | "She knelt, tilted her head," | | 16 | "She photographed it in situ," | | 17 | "Its casing was etched with" | | 18 | "It tracked something else entirely." | | 19 | "She slipped it into an" |
| | ratio | 0.286 | |
| 94.45% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 87 | | totalSentences | 119 | | matches | | 0 | "The platform at Camden Town" | | 1 | "She was three levels beneath" | | 2 | "The body lay face-down on" | | 3 | "The worn leather of her" | | 4 | "Her knees complained." | | 5 | "DC Amara Osei stood a" | | 6 | "She was young, competent, and" | | 7 | "Quinn turned the words over" | | 8 | "She leaned closer to the" | | 9 | "His fingernails were black." | | 10 | "She'd seen something like it" | | 11 | "The night Morris died." | | 12 | "She sealed that thought behind" | | 13 | "Quinn stood and swept her" | | 14 | "It wasn't a tunnel, not" | | 15 | "It was a room." | | 16 | "Alcoves lined the walls, each" | | 17 | "Some still held fragments of" | | 18 | "Others contained smashed glass, scattered" | | 19 | "Quinn studied one of the" |
| | ratio | 0.731 | |
| 42.02% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 119 | | matches | | 0 | "As if someone had pressed" |
| | ratio | 0.008 | |
| 61.99% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 53 | | technicalSentenceCount | 6 | | matches | | 0 | "She was three levels beneath it, at the bottom of a service stairwell that shouldn't have existed, in a tunnel that appeared on no Transport for London schemati…" | | 1 | "Male, mid-thirties, dressed in a long coat that had seen better decades." | | 2 | "Just a pair of scorched handprints on the wall above him and a smell that reminded Quinn of burnt copper." | | 3 | "Its casing was etched with markings — not cardinal directions, not any navigational system she recognized, but symbols that matched the ones carved into the she…" | | 4 | "Osei was watching her with an expression Quinn recognized from every junior officer she'd ever partnered with — the look that said the case had just crossed a l…" | | 5 | "A ticket to a place that shouldn't exist, run by people who shouldn't be possible, selling things that didn't obey the laws Quinn had built her entire career ar…" |
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| 62.50% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 8 | | uselessAdditionCount | 1 | | matches | | 0 | "She held, not touching" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 1 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 47 | | tagDensity | 0.021 | | leniency | 0.043 | | rawRatio | 0 | | effectiveRatio | 0 | |