| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 5 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 10 | | tagDensity | 0.5 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1520 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 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) | |
| 34.21% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1520 | | totalAiIsms | 20 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | | | 13 | | | 14 | | | 15 | | | 16 | | | 17 | |
| | highlights | | 0 | "weight" | | 1 | "glint" | | 2 | "fractured" | | 3 | "familiar" | | 4 | "structure" | | 5 | "throb" | | 6 | "pulse" | | 7 | "looming" | | 8 | "maw" | | 9 | "shattered" | | 10 | "gloom" | | 11 | "depths" | | 12 | "stomach" | | 13 | "velvet" | | 14 | "scanned" | | 15 | "silence" | | 16 | "echoed" | | 17 | "glistening" |
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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 | 1 | | narrationSentences | 125 | | matches | | |
| 97.14% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 3 | | narrationSentences | 125 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 130 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 32 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1519 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 2 | | unquotedAttributions | 1 | | matches | | 0 | "A former paramedic, they said." |
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| 98.24% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 46 | | wordCount | 1449 | | uniqueNames | 13 | | maxNameDensity | 1.04 | | worstName | "Quinn" | | maxWindowNameDensity | 2 | | worstWindowName | "Quinn" | | discoveredNames | | Soho | 1 | | Harlow | 2 | | Quinn | 15 | | Herrera | 12 | | Morris | 4 | | Camden | 2 | | Raven | 1 | | Nest | 2 | | Tube | 1 | | Christopher | 1 | | Seville | 1 | | Veil | 2 | | Market | 2 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Herrera" | | 3 | "Morris" | | 4 | "Raven" | | 5 | "Christopher" | | 6 | "Market" |
| | places | | 0 | "Soho" | | 1 | "Camden" | | 2 | "Seville" | | 3 | "Veil" |
| | globalScore | 0.982 | | windowScore | 1 | |
| 95.65% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 92 | | glossingSentenceCount | 2 | | matches | | 0 | "runes that seemed to squirm in the peripheral vision" | | 1 | "felt like" |
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| 68.33% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 2 | | per1kWords | 1.317 | | wordCount | 1519 | | matches | | 0 | "not in surrender, but in warning" | | 1 | "not for him, but for the opening" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 130 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 27 | | mean | 56.26 | | std | 28.75 | | cv | 0.511 | | sampleLengths | | 0 | 84 | | 1 | 49 | | 2 | 27 | | 3 | 98 | | 4 | 106 | | 5 | 72 | | 6 | 72 | | 7 | 118 | | 8 | 50 | | 9 | 50 | | 10 | 18 | | 11 | 67 | | 12 | 26 | | 13 | 31 | | 14 | 53 | | 15 | 91 | | 16 | 11 | | 17 | 43 | | 18 | 4 | | 19 | 82 | | 20 | 39 | | 21 | 45 | | 22 | 85 | | 23 | 51 | | 24 | 52 | | 25 | 65 | | 26 | 30 |
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| 94.04% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 4 | | totalSentences | 125 | | matches | | 0 | "was buried" | | 1 | "was swallowed" | | 2 | "been torn" | | 3 | "were lined" |
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| 0.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 9 | | totalVerbs | 238 | | matches | | 0 | "was hunting" | | 1 | "was scaling" | | 2 | "was moving" | | 3 | "was heading" | | 4 | "wasn't running" | | 5 | "were trading" | | 6 | "wasn't just moving" | | 7 | "was feeding" | | 8 | "was already moving" |
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| 32.97% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 1 | | semicolonCount | 4 | | flaggedSentences | 5 | | totalSentences | 130 | | ratio | 0.038 | | matches | | 0 | "The rain did not fall; it drove, needling the pavement with a violence that turned the Soho gutters into rushing black streams." | | 1 | "Rain blurred her vision; salt-and-pepper strands of hair stuck to her sharp cheekbones, stinging her brown eyes." | | 2 | "A rush of air blasted up from the depths, carrying a smell that made Quinn's stomach turn—ozone, old copper, and rotting flowers." | | 3 | "The clique wasn't just moving drugs; they were trading in the impossible." | | 4 | "The rain above was a distant memory; here, the air tasted of secrets and blood." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1458 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 26 | | adverbRatio | 0.01783264746227709 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.003429355281207133 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 130 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 130 | | mean | 11.68 | | std | 7.54 | | cv | 0.645 | | sampleLengths | | 0 | 22 | | 1 | 6 | | 2 | 23 | | 3 | 24 | | 4 | 5 | | 5 | 4 | | 6 | 17 | | 7 | 11 | | 8 | 21 | | 9 | 24 | | 10 | 3 | | 11 | 11 | | 12 | 18 | | 13 | 2 | | 14 | 31 | | 15 | 20 | | 16 | 2 | | 17 | 3 | | 18 | 11 | | 19 | 3 | | 20 | 3 | | 21 | 18 | | 22 | 8 | | 23 | 18 | | 24 | 2 | | 25 | 2 | | 26 | 15 | | 27 | 7 | | 28 | 13 | | 29 | 17 | | 30 | 5 | | 31 | 16 | | 32 | 5 | | 33 | 14 | | 34 | 32 | | 35 | 3 | | 36 | 20 | | 37 | 17 | | 38 | 16 | | 39 | 16 | | 40 | 7 | | 41 | 14 | | 42 | 5 | | 43 | 17 | | 44 | 16 | | 45 | 1 | | 46 | 1 | | 47 | 9 | | 48 | 18 | | 49 | 16 |
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| 47.18% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 17 | | diversityRatio | 0.36153846153846153 | | totalSentences | 130 | | uniqueOpeners | 47 | |
| 59.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 113 | | matches | | 0 | "More than fast." | | 1 | "Just a stain on the" |
| | ratio | 0.018 | |
| 71.33% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 42 | | totalSentences | 113 | | matches | | 0 | "Her boots hammered asphalt, splashing" | | 1 | "She didn't check the time." | | 2 | "She checked the gap." | | 3 | "He knew the geography of" | | 4 | "He hit a fire escape" | | 5 | "It swung free of a" | | 6 | "She recognized the profile now:" | | 7 | "He was fast." | | 8 | "She suspected the clique had" | | 9 | "She burst into the alley." | | 10 | "He reached the top, vanished" | | 11 | "She hit the scaling ladder" | | 12 | "She hauled herself up, muscles" | | 13 | "She followed, her descent rough" | | 14 | "Her left knee protested, a" | | 15 | "He was heading to the" | | 16 | "He wasn't running anymore." | | 17 | "He had stopped, his body" | | 18 | "She stepped through the broken" | | 19 | "His olive skin was pale," |
| | ratio | 0.372 | |
| 35.22% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 96 | | totalSentences | 113 | | matches | | 0 | "The rain did not fall;" | | 1 | "Detective Harlow Quinn did not" | | 2 | "Her boots hammered asphalt, splashing" | | 3 | "The leather strap of her" | | 4 | "She didn't check the time." | | 5 | "She checked the gap." | | 6 | "He knew the geography of" | | 7 | "He hit a fire escape" | | 8 | "Quinn's voice tore through the" | | 9 | "The figure glanced back over" | | 10 | "It swung free of a" | | 11 | "She recognized the profile now:" | | 12 | "The clique's doctor." | | 13 | "The man who stitched up" | | 14 | "He was fast." | | 15 | "Quinn felt the familiar burn" | | 16 | "Military precision demanded efficiency, and" | | 17 | "The paperwork said Morris had" | | 18 | "Quinn's gut knew the truth" | | 19 | "She suspected the clique had" |
| | ratio | 0.85 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 3 | | totalSentences | 113 | | matches | | 0 | "Even at fifty yards, through" | | 1 | "Even from three paces, Quinn" | | 2 | "If she closed this gate" |
| | ratio | 0.027 | |
| 43.96% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 65 | | technicalSentenceCount | 9 | | matches | | 0 | "He hit a fire escape with practiced grace, vaulting a rusted dumpster without breaking stride, his coat flapping like broken wings." | | 1 | "The entrance was a gaping maw of concrete and graffiti, blocked by a chain-link fence that had been cut and bent back repeatedly." | | 2 | "Quinn slowed, her hand dropping to the grip of her service weapon, her thumb clicking the safety off with a tactile click that was swallowed by the thunder." | | 3 | "A rush of air blasted up from the depths, carrying a smell that made Quinn's stomach turn—ozone, old copper, and rotting flowers." | | 4 | "The metal was ice-cold, vibrating with a low hum that rattled her bones." | | 5 | "Enchanted goods, banned alchemical substances, the refuse of a world that pretended not to exist." | | 6 | "They scanned it, nodded, and ushered him toward a hidden stairwell that descended even deeper, into the black heart beneath the earth." | | 7 | "Wait for the specialized unit that didn't exist on any organizational chart." | | 8 | "Harlow Quinn drew her weapon, checked the chamber one last time, and descended into the market, leaving the world of laws and lights behind for the only truth t…" |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 5 | | uselessAdditionCount | 2 | | matches | | 0 | "She stepped, boots crunching on shattered glass" | | 1 | "He cut, his gaze darting past her, down the platform" |
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| 50.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 1 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 10 | | tagDensity | 0.1 | | leniency | 0.2 | | rawRatio | 1 | | effectiveRatio | 0.2 | |