| 0.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 7 | | adverbTagCount | 2 | | adverbTags | | 0 | "the man gestured vaguely [vaguely]" | | 1 | "The man leaned back [back]" |
| | dialogueSentences | 19 | | tagDensity | 0.368 | | leniency | 0.737 | | rawRatio | 0.286 | | effectiveRatio | 0.211 | |
| 84.92% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1326 | | totalAiIsmAdverbs | 4 | | found | | | highlights | | 0 | "quickly" | | 1 | "carefully" | | 2 | "slightly" |
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| 80.00% | AI-ism character names | Target: 0 AI-default names (17 tracked, −20% each) | | codexExemptions | (empty) | | found | | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 73.60% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1326 | | totalAiIsms | 7 | | found | | | highlights | | 0 | "navigated" | | 1 | "efficient" | | 2 | "echoed" | | 3 | "wavering" | | 4 | "resolved" | | 5 | "unsettled" | | 6 | "jaw clenched" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "jaw/fists clenched" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 104 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 1 | | narrationSentences | 104 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 116 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 34 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1313 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 7 | | unquotedAttributions | 0 | | matches | (empty) | |
| 50.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 55 | | wordCount | 1106 | | uniqueNames | 17 | | maxNameDensity | 1.99 | | worstName | "Quinn" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Quinn" | | discoveredNames | | London | 1 | | Harlow | 1 | | Quinn | 22 | | Old | 1 | | Compton | 1 | | Street | 3 | | Marcus | 1 | | Webb | 13 | | Whitechapel | 1 | | Morris | 3 | | Friday | 1 | | Soho | 2 | | Raven | 1 | | Nest | 1 | | New | 1 | | Scotland | 1 | | Yard | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Marcus" | | 3 | "Webb" | | 4 | "Morris" | | 5 | "Raven" | | 6 | "Nest" | | 7 | "Yard" |
| | places | | 0 | "London" | | 1 | "Old" | | 2 | "Compton" | | 3 | "Street" | | 4 | "Whitechapel" | | 5 | "Soho" | | 6 | "New" | | 7 | "Scotland" |
| | globalScore | 0.505 | | windowScore | 0.5 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 74 | | glossingSentenceCount | 1 | | matches | | 0 | "looked like from the outside—a private sp" |
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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 | 1313 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 2 | | totalSentences | 116 | | matches | | 0 | "screamed that Webb" | | 1 | "had that bar" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 40 | | mean | 32.83 | | std | 22.63 | | cv | 0.689 | | sampleLengths | | 0 | 59 | | 1 | 74 | | 2 | 7 | | 3 | 64 | | 4 | 16 | | 5 | 67 | | 6 | 45 | | 7 | 41 | | 8 | 74 | | 9 | 8 | | 10 | 59 | | 11 | 12 | | 12 | 47 | | 13 | 47 | | 14 | 2 | | 15 | 50 | | 16 | 39 | | 17 | 42 | | 18 | 20 | | 19 | 9 | | 20 | 65 | | 21 | 56 | | 22 | 17 | | 23 | 9 | | 24 | 41 | | 25 | 29 | | 26 | 14 | | 27 | 34 | | 28 | 10 | | 29 | 14 | | 30 | 26 | | 31 | 56 | | 32 | 11 | | 33 | 1 | | 34 | 4 | | 35 | 60 | | 36 | 46 | | 37 | 22 | | 38 | 7 | | 39 | 9 |
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| 91.77% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 4 | | totalSentences | 104 | | matches | | 0 | "get uniformed" | | 1 | "were lined" | | 2 | "was drawn" | | 3 | "been trained" |
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| 22.70% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 5 | | totalVerbs | 188 | | matches | | 0 | "was building" | | 1 | "was heading" | | 2 | "were thinning" | | 3 | "was going" | | 4 | "was obsessing" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 13 | | semicolonCount | 0 | | flaggedSentences | 11 | | totalSentences | 116 | | ratio | 0.095 | | matches | | 0 | "She'd been tracking Marcus Webb for three weeks—ever since the tip came in about unusual activity at a warehouse in Whitechapel." | | 1 | "Soho was a mess of humanity on good nights—tourists, clubbers, sex workers, dealers." | | 2 | "The alley was tight enough that the rain barely reached the ground—instead it pooled between the buildings, creating a dark tunnel lit only by the reflected glow from the street beyond." | | 3 | "Quinn's worn leather watch—its strap soft from years of wear against her left wrist—caught a flash of streetlight as she checked the time." | | 4 | "Nothing concrete—no arrests, no obvious criminal activity—but it had a reputation." | | 5 | "Of the look on his face the last time she'd seen him—confused, afraid, something other than human in his eyes before the darkness took him." | | 6 | "The passage smelled of stale beer and something else—something organic and wrong that made her nose wrinkle." | | 7 | "Music drifted through—something jazzy and low." | | 8 | "The room was exactly what it looked like from the outside—a private space, carefully curated." | | 9 | "Behind him, a bookshelf seemed to shift in the low light—or maybe that was just Quinn's mind, exhausted and wired on adrenaline." | | 10 | "\"Gone. You missed him by about thirty seconds. He went through to the back room, and from there—\" the man gestured vaguely toward the bookshelf, \"—somewhere you're not ready to follow.\"" |
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| 92.80% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1099 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 53 | | adverbRatio | 0.048225659690627844 | | lyAdverbCount | 16 | | lyAdverbRatio | 0.014558689717925387 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 116 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 116 | | mean | 11.32 | | std | 8.12 | | cv | 0.717 | | sampleLengths | | 0 | 21 | | 1 | 34 | | 2 | 2 | | 3 | 2 | | 4 | 21 | | 5 | 22 | | 6 | 25 | | 7 | 6 | | 8 | 7 | | 9 | 6 | | 10 | 13 | | 11 | 13 | | 12 | 20 | | 13 | 4 | | 14 | 8 | | 15 | 10 | | 16 | 3 | | 17 | 3 | | 18 | 16 | | 19 | 6 | | 20 | 31 | | 21 | 6 | | 22 | 8 | | 23 | 18 | | 24 | 4 | | 25 | 15 | | 26 | 4 | | 27 | 4 | | 28 | 23 | | 29 | 1 | | 30 | 17 | | 31 | 9 | | 32 | 6 | | 33 | 2 | | 34 | 20 | | 35 | 11 | | 36 | 11 | | 37 | 15 | | 38 | 8 | | 39 | 7 | | 40 | 7 | | 41 | 16 | | 42 | 5 | | 43 | 19 | | 44 | 5 | | 45 | 2 | | 46 | 2 | | 47 | 1 | | 48 | 2 | | 49 | 5 |
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| 53.04% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 9 | | diversityRatio | 0.3652173913043478 | | totalSentences | 115 | | uniqueOpeners | 42 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 93 | | matches | | 0 | "Somewhere he felt safe." | | 1 | "Instead, he moved past it," | | 2 | "Instead, Quinn pushed the door" |
| | ratio | 0.032 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 26 | | totalSentences | 93 | | matches | | 0 | "She'd been tracking Marcus Webb" | | 1 | "She pushed harder, her legs" | | 2 | "He knew these corners better" | | 3 | "She had speed." | | 4 | "She had will." | | 5 | "Her shoes echoed off the" | | 6 | "She emerged onto a side" | | 7 | "He was heading somewhere." | | 8 | "She recognized where he was" | | 9 | "She'd had that bar on" | | 10 | "He didn't go through the" | | 11 | "She moved to the opposite" | | 12 | "He was inside the building." | | 13 | "She thought of Morris." | | 14 | "She crossed the street in" | | 15 | "Her shoes stuck slightly to" | | 16 | "She should call it in." | | 17 | "He looked up at her" | | 18 | "It wasn't a question." | | 19 | "It was not a kind" |
| | ratio | 0.28 | |
| 62.15% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 74 | | totalSentences | 93 | | matches | | 0 | "The rain hammered the London" | | 1 | "Detective Harlow Quinn's shoes splashed" | | 2 | "She'd been tracking Marcus Webb" | | 3 | "Webb was small-time, or at" | | 4 | "The operation that involved the" | | 5 | "The same operation that had" | | 6 | "Quinn's jaw tightened at the" | | 7 | "She pushed harder, her legs" | | 8 | "Soho was a mess of" | | 9 | "Webb had an advantage." | | 10 | "He knew these corners better" | | 11 | "She had speed." | | 12 | "She had will." | | 13 | "Webb cut right down a" | | 14 | "Quinn followed, her breathing controlled," | | 15 | "The alley was tight enough" | | 16 | "Her shoes echoed off the" | | 17 | "Webb's were somewhere ahead, distorted" | | 18 | "She emerged onto a side" | | 19 | "Wardour Street, heading south." |
| | ratio | 0.796 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 93 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 49 | | technicalSentenceCount | 2 | | matches | | 0 | "Webb was small-time, or at least that's what his file suggested: petty theft, some dealing, nothing that warranted this kind of obsession." | | 1 | "There was something about the images that unsettled her, something in the angles and shadows that suggested they were older than they should be." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 7 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 3 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 19 | | tagDensity | 0.158 | | leniency | 0.316 | | rawRatio | 0 | | effectiveRatio | 0 | |