| 0.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 4 | | adverbTagCount | 2 | | adverbTags | | 0 | "he said softly [softly]" | | 1 | "she said flatly [flatly]" |
| | dialogueSentences | 10 | | tagDensity | 0.4 | | leniency | 0.8 | | rawRatio | 0.5 | | effectiveRatio | 0.4 | |
| 90.33% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1034 | | 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) | |
| 41.97% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1034 | | totalAiIsms | 12 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | word | "down her spine" | | count | 1 |
| | 9 | |
| | highlights | | 0 | "flicker" | | 1 | "scanning" | | 2 | "measured" | | 3 | "weight" | | 4 | "flickered" | | 5 | "pulse" | | 6 | "eyebrow" | | 7 | "flicked" | | 8 | "down her spine" | | 9 | "pulsed" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "shiver down spine" | | count | 1 |
|
| | highlights | | 0 | "A shiver ran down her spine" |
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| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 118 | | matches | (empty) | |
| 94.43% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 3 | | hedgeCount | 1 | | narrationSentences | 118 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 124 | | 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 | 1 | | markdownWords | 1 | | totalWords | 1020 | | ratio | 0.001 | | matches | | |
| 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 | 48 | | wordCount | 980 | | uniqueNames | 15 | | maxNameDensity | 1.63 | | worstName | "Herrera" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Herrera" | | discoveredNames | | Soho | 2 | | Harlow | 1 | | Quinn | 14 | | Herrera | 16 | | Old | 1 | | Compton | 1 | | Street | 1 | | Morris | 1 | | Raven | 1 | | Nest | 1 | | Saint | 1 | | Christopher | 1 | | Veil | 2 | | Market | 2 | | Didn | 3 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Herrera" | | 3 | "Morris" | | 4 | "Raven" | | 5 | "Saint" | | 6 | "Christopher" | | 7 | "Market" |
| | places | | 0 | "Soho" | | 1 | "Old" | | 2 | "Compton" | | 3 | "Street" |
| | globalScore | 0.684 | | windowScore | 0.5 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 64 | | glossingSentenceCount | 1 | | matches | | 0 | "looked like they belonged to sailors from" |
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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 | 1020 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 124 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 48 | | mean | 21.25 | | std | 20.98 | | cv | 0.987 | | sampleLengths | | 0 | 67 | | 1 | 79 | | 2 | 4 | | 3 | 22 | | 4 | 52 | | 5 | 45 | | 6 | 3 | | 7 | 56 | | 8 | 44 | | 9 | 46 | | 10 | 6 | | 11 | 18 | | 12 | 41 | | 13 | 43 | | 14 | 36 | | 15 | 3 | | 16 | 82 | | 17 | 40 | | 18 | 36 | | 19 | 22 | | 20 | 9 | | 21 | 5 | | 22 | 9 | | 23 | 19 | | 24 | 7 | | 25 | 37 | | 26 | 4 | | 27 | 1 | | 28 | 15 | | 29 | 7 | | 30 | 6 | | 31 | 6 | | 32 | 12 | | 33 | 5 | | 34 | 6 | | 35 | 28 | | 36 | 10 | | 37 | 8 | | 38 | 3 | | 39 | 3 | | 40 | 5 | | 41 | 12 | | 42 | 16 | | 43 | 12 | | 44 | 10 | | 45 | 3 | | 46 | 12 | | 47 | 5 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 118 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 172 | | matches | (empty) | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 15 | | semicolonCount | 0 | | flaggedSentences | 13 | | totalSentences | 124 | | ratio | 0.105 | | matches | | 0 | "Not asking questions, not making notes—just standing there under the flicker of a faulty streetlamp, rain dripping from the brim of her hat." | | 1 | "Not with a start—with a tilt of the head, quick eyes scanning the street like a man who knew the eyes of the law would follow." | | 2 | "Bypassers got out of her way—shoulders tensed, hands clutching umbrellas like shields." | | 3 | "No surprise in his gaze—only calculation, like a chess player sizing up her opponent." | | 4 | "Quinn pulled herself up just in time to see him sprint across the gravel-strewn rooftop toward the opposite edge—the one overlooking a narrow service alley where a green neon sign flickered like a dying pulse." | | 5 | "Her knee twinged—old injury from the Morris debacle—but she gritted her teeth and pushed through." | | 6 | "She pushed through the door of The Raven’s Nest, shoulders brushing past a man in a long coat who smelled faintly of cigarette smoke and something older—damp earth and iron." | | 7 | "Herrera stood at the far end of the bar, exchanging words with the bartender—a wiry man with a scar through one eyebrow and sleeves rolled up to reveal tattoos that looked like they belonged to sailors from the last century." | | 8 | "It had been half-filled with amber liquid—whiskey, maybe." | | 9 | "The patrons—men, women, a few who didn’t look quite human—all seemed to lean in." | | 10 | "Rosemary and myrrh—something protective." | | 11 | "At the far end, a sliver of darkness—like a gap in the wall." | | 12 | "Somewhere beneath the city, the Veil Market pulsed—alive, hidden, dangerous." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1001 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 35 | | adverbRatio | 0.03496503496503497 | | lyAdverbCount | 10 | | lyAdverbRatio | 0.00999000999000999 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 124 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 124 | | mean | 8.23 | | std | 6.64 | | cv | 0.807 | | sampleLengths | | 0 | 17 | | 1 | 15 | | 2 | 16 | | 3 | 3 | | 4 | 6 | | 5 | 10 | | 6 | 7 | | 7 | 15 | | 8 | 23 | | 9 | 2 | | 10 | 26 | | 11 | 4 | | 12 | 2 | | 13 | 4 | | 14 | 7 | | 15 | 9 | | 16 | 3 | | 17 | 3 | | 18 | 20 | | 19 | 8 | | 20 | 12 | | 21 | 4 | | 22 | 5 | | 23 | 3 | | 24 | 4 | | 25 | 9 | | 26 | 14 | | 27 | 3 | | 28 | 3 | | 29 | 3 | | 30 | 3 | | 31 | 6 | | 32 | 3 | | 33 | 15 | | 34 | 9 | | 35 | 10 | | 36 | 11 | | 37 | 6 | | 38 | 5 | | 39 | 18 | | 40 | 7 | | 41 | 6 | | 42 | 13 | | 43 | 11 | | 44 | 35 | | 45 | 6 | | 46 | 3 | | 47 | 4 | | 48 | 3 | | 49 | 8 |
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| 53.76% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 5 | | diversityRatio | 0.3467741935483871 | | totalSentences | 124 | | uniqueOpeners | 43 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 4 | | totalSentences | 109 | | matches | | 0 | "Just kept walking." | | 1 | "Then he ducked down an" | | 2 | "Then she smelled it." | | 3 | "Somewhere beneath the city, the" |
| | ratio | 0.037 | |
| 98.90% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 33 | | totalSentences | 109 | | matches | | 0 | "She adjusted the cuff of" | | 1 | "She’d been tailing Herrera for" | | 2 | "She expected it soon." | | 3 | "She didn’t flinch." | | 4 | "She didn’t acknowledge them." | | 5 | "Her focus was narrow, tunnel-like." | | 6 | "He glanced back once." | | 7 | "Their eyes met across thirty" | | 8 | "She didn’t slow." | | 9 | "His jaw tightened." | | 10 | "She lunged into the darkness" | | 11 | "She skidded on a soggy" | | 12 | "Her breath came controlled, measured." | | 13 | "She followed, boots clanging on" | | 14 | "Her gloved fingers dug into" | | 15 | "He reached the roof first," | | 16 | "She knew the place." | | 17 | "She leapt, caught the railing," | | 18 | "Her knee twinged—old injury from" | | 19 | "Her watch read 10:42." |
| | ratio | 0.303 | |
| 83.85% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 82 | | totalSentences | 109 | | matches | | 0 | "The rain came down in" | | 1 | "Detective Harlow Quinn kept her" | | 2 | "She adjusted the cuff of" | | 3 | "She’d been tailing Herrera for" | | 4 | "She expected it soon." | | 5 | "A black cab swerved past," | | 6 | "Water sprayed up, drenching her" | | 7 | "She didn’t flinch." | | 8 | "Herrera turned the corner onto" | | 9 | "Quinn crossed the road without" | | 10 | "Bypassers got out of her" | | 11 | "She didn’t acknowledge them." | | 12 | "Her focus was narrow, tunnel-like." | | 13 | "He glanced back once." | | 14 | "Their eyes met across thirty" | | 15 | "She didn’t slow." | | 16 | "His jaw tightened." | | 17 | "Quinn didn’t hesitate." | | 18 | "She lunged into the darkness" | | 19 | "The alley reeked of spilled" |
| | ratio | 0.752 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 109 | | matches | (empty) | | ratio | 0 | |
| 69.60% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 39 | | technicalSentenceCount | 4 | | matches | | 0 | "Detective Harlow Quinn kept her stride steady, boots splashing through puddles that reflected flickering signs." | | 1 | "She pushed through the door of The Raven’s Nest, shoulders brushing past a man in a long coat who smelled faintly of cigarette smoke and something older—damp ea…" | | 2 | "Herrera stood at the far end of the bar, exchanging words with the bartender—a wiry man with a scar through one eyebrow and sleeves rolled up to reveal tattoos …" | | 3 | "Quinn moved forward, rainwater dripping from her coat, forming a dark pool at her feet." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 4 | | uselessAdditionCount | 1 | | matches | | 0 | "she asked, chin tilting toward it" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 4 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 10 | | tagDensity | 0.4 | | leniency | 0.8 | | rawRatio | 0 | | effectiveRatio | 0 | |