| 75.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 22 | | adverbTagCount | 4 | | adverbTags | | 0 | "Quinn turned back [back]" | | 1 | "Quinn walked back [back]" | | 2 | "Quinn said slowly [slowly]" | | 3 | "She turned back [back]" |
| | dialogueSentences | 64 | | tagDensity | 0.344 | | leniency | 0.688 | | rawRatio | 0.182 | | effectiveRatio | 0.125 | |
| 90.94% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1656 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | 0 | "carefully" | | 1 | "slowly" | | 2 | "really" |
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| 60.00% | 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) | |
| 69.81% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1656 | | totalAiIsms | 10 | | found | | | highlights | | 0 | "stomach" | | 1 | "could feel" | | 2 | "etched" | | 3 | "silence" | | 4 | "unwavering" | | 5 | "pulse" | | 6 | "whisper" | | 7 | "flickered" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 98 | | matches | (empty) | |
| 99.13% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 3 | | narrationSentences | 98 | | filterMatches | (empty) | | hedgeMatches | | 0 | "seemed to" | | 1 | "started to" |
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| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 139 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 44 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1638 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 17 | | unquotedAttributions | 0 | | matches | (empty) | |
| 2.63% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 63 | | wordCount | 950 | | uniqueNames | 14 | | maxNameDensity | 2.95 | | worstName | "Quinn" | | maxWindowNameDensity | 4.5 | | worstWindowName | "Quinn" | | discoveredNames | | Tube | 1 | | London | 1 | | Underground | 1 | | Harlow | 1 | | Quinn | 28 | | Victorian | 1 | | Camden | 2 | | Kowalski | 1 | | Eva | 20 | | Italian | 1 | | Rolex | 1 | | Chen | 2 | | Morris | 2 | | Whitechapel | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Kowalski" | | 3 | "Eva" | | 4 | "Rolex" | | 5 | "Chen" | | 6 | "Morris" |
| | places | | | globalScore | 0.026 | | windowScore | 0.167 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 72 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1638 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 139 | | matches | | 0 | "lettering that spelled" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 61 | | mean | 26.85 | | std | 17.08 | | cv | 0.636 | | sampleLengths | | 0 | 62 | | 1 | 17 | | 2 | 50 | | 3 | 60 | | 4 | 40 | | 5 | 5 | | 6 | 35 | | 7 | 34 | | 8 | 2 | | 9 | 11 | | 10 | 39 | | 11 | 11 | | 12 | 38 | | 13 | 21 | | 14 | 11 | | 15 | 44 | | 16 | 9 | | 17 | 63 | | 18 | 33 | | 19 | 5 | | 20 | 15 | | 21 | 30 | | 22 | 25 | | 23 | 8 | | 24 | 33 | | 25 | 21 | | 26 | 8 | | 27 | 12 | | 28 | 42 | | 29 | 38 | | 30 | 11 | | 31 | 41 | | 32 | 14 | | 33 | 56 | | 34 | 24 | | 35 | 40 | | 36 | 47 | | 37 | 12 | | 38 | 13 | | 39 | 9 | | 40 | 10 | | 41 | 29 | | 42 | 44 | | 43 | 10 | | 44 | 28 | | 45 | 6 | | 46 | 56 | | 47 | 47 | | 48 | 35 | | 49 | 1 |
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| 98.10% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 98 | | matches | | 0 | "were redrawn" | | 1 | "were crossed" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 179 | | matches | (empty) | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 9 | | semicolonCount | 0 | | flaggedSentences | 8 | | totalSentences | 139 | | ratio | 0.058 | | matches | | 0 | "The uniforms had done a number getting through the wall—chunks of Victorian masonry scattered across the platform like broken teeth." | | 1 | "Except for the expression frozen on his face—mouth stretched wide, eyes rolled back to show the whites." | | 2 | "The victim's suit showed no signs of struggle—no tears, no defensive wounds on the hands." | | 3 | "Chalk marks on the platform floor, faded but deliberate—geometric patterns that spiraled outward from where Chen lay." | | 4 | "But there—on the left palm, barely visible in the torchlight—a small symbol drawn in something dark and flaking." | | 5 | "She thought again of Morris—his face, his silence, the questions that had gnawed at her for three years." | | 6 | "The professional mask cracked, revealing something rawer beneath—fear, certainly, but also recognition." | | 7 | "In the silence that followed, Quinn heard something from deep in the tunnel—a sound like grinding stone, like something massive shifting in its sleep." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 961 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 28 | | adverbRatio | 0.029136316337148804 | | lyAdverbCount | 7 | | lyAdverbRatio | 0.007284079084287201 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 139 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 139 | | mean | 11.78 | | std | 8.14 | | cv | 0.691 | | sampleLengths | | 0 | 20 | | 1 | 22 | | 2 | 20 | | 3 | 17 | | 4 | 11 | | 5 | 26 | | 6 | 3 | | 7 | 10 | | 8 | 18 | | 9 | 14 | | 10 | 9 | | 11 | 2 | | 12 | 17 | | 13 | 23 | | 14 | 17 | | 15 | 4 | | 16 | 1 | | 17 | 19 | | 18 | 16 | | 19 | 24 | | 20 | 10 | | 21 | 2 | | 22 | 9 | | 23 | 2 | | 24 | 9 | | 25 | 15 | | 26 | 7 | | 27 | 8 | | 28 | 4 | | 29 | 7 | | 30 | 16 | | 31 | 22 | | 32 | 3 | | 33 | 18 | | 34 | 11 | | 35 | 11 | | 36 | 33 | | 37 | 3 | | 38 | 6 | | 39 | 21 | | 40 | 2 | | 41 | 17 | | 42 | 9 | | 43 | 14 | | 44 | 7 | | 45 | 16 | | 46 | 10 | | 47 | 5 | | 48 | 10 | | 49 | 5 |
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| 64.27% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 4 | | diversityRatio | 0.4028776978417266 | | totalSentences | 139 | | uniqueOpeners | 56 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 91 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 13 | | totalSentences | 91 | | matches | | 0 | "His arms were crossed over" | | 1 | "She clutched her worn leather" | | 2 | "His shoes were Italian leather," | | 3 | "Her hand retreated to her" | | 4 | "She moved to the edge" | | 5 | "She angled the torch." | | 6 | "Her partner's body found in" | | 7 | "She'd never believed it." | | 8 | "She swept her torch once" | | 9 | "It pointed now toward the" | | 10 | "She thought again of Morris—his" | | 11 | "She turned back to Eva" | | 12 | "She didn't need light to" |
| | ratio | 0.143 | |
| 20.44% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 80 | | totalSentences | 91 | | matches | | 0 | "The abandoned Tube station smelled" | | 1 | "Detective Harlow Quinn ducked under" | | 2 | "The uniforms had done a" | | 3 | "Quinn nodded at the constable" | | 4 | "The beam of her torch" | | 5 | "Camden, she thought." | | 6 | "The body lay at the" | | 7 | "His arms were crossed over" | | 8 | "The voice came from behind" | | 9 | "Quinn didn't turn around." | | 10 | "Eva Kowalski emerged from the" | | 11 | "She clutched her worn leather" | | 12 | "Eva tucked a strand of" | | 13 | "Eva's pause told Quinn everything" | | 14 | "Quinn crouched beside the body," | | 15 | "The victim's suit showed no" | | 16 | "His shoes were Italian leather," | | 17 | "A Rolex hung loose on" | | 18 | "Eva moved closer, her satchel" | | 19 | "Quinn's jaw tightened." |
| | ratio | 0.879 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 91 | | matches | | 0 | "Now she had a name" | | 1 | "Before Eva could answer, Quinn's" |
| | ratio | 0.022 | |
| 16.81% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 34 | | technicalSentenceCount | 6 | | matches | | 0 | "The abandoned Tube station smelled of rust and old water, that particular London Underground musk that clung to forgotten places." | | 1 | "Male, mid-thirties, dressed in a tailored suit that cost more than her monthly rent." | | 2 | "Chalk marks on the platform floor, faded but deliberate—geometric patterns that spiraled outward from where Chen lay." | | 3 | "And there, scattered in the dust near the victim's head, something that glinted brass." | | 4 | "She thought again of Morris—his face, his silence, the questions that had gnawed at her for three years." | | 5 | "In the silence that followed, Quinn heard something from deep in the tunnel—a sound like grinding stone, like something massive shifting in its sleep." |
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| 79.55% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 22 | | uselessAdditionCount | 2 | | matches | | 0 | "Eva moved, her satchel bumping against a support column" | | 1 | "Eva's hand drifted, fingers brushing the worn leather like a talisman" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 3 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 64 | | tagDensity | 0.047 | | leniency | 0.094 | | rawRatio | 0.333 | | effectiveRatio | 0.031 | |