| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 7 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 15 | | tagDensity | 0.467 | | leniency | 0.933 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1227 | | 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) | |
| 42.95% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1227 | | totalAiIsms | 14 | | found | | | highlights | | 0 | "flickered" | | 1 | "glinting" | | 2 | "echoing" | | 3 | "echoes" | | 4 | "pulse" | | 5 | "quickened" | | 6 | "reminder" | | 7 | "traced" | | 8 | "flicked" | | 9 | "trembled" | | 10 | "pawn" |
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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 | 2 | | narrationSentences | 80 | | matches | | 0 | "d with unease" | | 1 | "n in terror" |
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| 89.29% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 2 | | narrationSentences | 80 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 87 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 43 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1205 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 6 | | unquotedAttributions | 0 | | matches | (empty) | |
| 95.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 44 | | wordCount | 1091 | | uniqueNames | 14 | | maxNameDensity | 1.1 | | worstName | "Herrera" | | maxWindowNameDensity | 2 | | worstWindowName | "Herrera" | | discoveredNames | | Dean | 1 | | Street | 1 | | Harlow | 10 | | Quinn | 1 | | Herrera | 12 | | Raven | 2 | | Nest | 2 | | Veil | 4 | | Market | 4 | | London | 1 | | Seville | 1 | | Saint | 1 | | Christopher | 1 | | Morris | 3 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Herrera" | | 3 | "Market" | | 4 | "Saint" | | 5 | "Christopher" | | 6 | "Morris" |
| | places | | 0 | "Dean" | | 1 | "Street" | | 2 | "Raven" | | 3 | "London" | | 4 | "Seville" |
| | globalScore | 0.95 | | windowScore | 1 | |
| 2.94% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 68 | | glossingSentenceCount | 4 | | matches | | 0 | "coins that seemed to shift in the torchlight" | | 1 | "looked like bottled lightning, stood Herr" | | 2 | "quite make out, its contents swirling with an unnatural hue" | | 3 | "seemed closer" |
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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 | 1205 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 87 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 27 | | mean | 44.63 | | std | 27.5 | | cv | 0.616 | | sampleLengths | | 0 | 54 | | 1 | 92 | | 2 | 28 | | 3 | 73 | | 4 | 85 | | 5 | 76 | | 6 | 53 | | 7 | 96 | | 8 | 80 | | 9 | 87 | | 10 | 40 | | 11 | 11 | | 12 | 33 | | 13 | 18 | | 14 | 29 | | 15 | 19 | | 16 | 19 | | 17 | 69 | | 18 | 50 | | 19 | 16 | | 20 | 23 | | 21 | 44 | | 22 | 28 | | 23 | 4 | | 24 | 35 | | 25 | 28 | | 26 | 15 |
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| 92.11% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 80 | | matches | | 0 | "was gone" | | 1 | "were written" | | 2 | "been found" |
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| 92.47% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 3 | | totalVerbs | 186 | | matches | | 0 | "was darting" | | 1 | "was pointing" | | 2 | "was, hanging" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 20 | | semicolonCount | 0 | | flaggedSentences | 12 | | totalSentences | 87 | | ratio | 0.138 | | matches | | 0 | "The neon sign of the bar—green, menacing—flickered above them, casting an eerie glow on the wet walls." | | 1 | "At the top, the city sprawled below—luminous, indifferent." | | 2 | "At the base, a grate in the pavement—half-hidden by a pile of wet newspapers—caught her eye." | | 3 | "The air rising from the opening smelled of damp earth and something else—ozone, maybe, or the metallic tang of old blood." | | 4 | "Harlow’s flashlight cut through the darkness, its beam landing on a carved symbol—a serpent coiled around a bone—scrawled into the stone." | | 5 | "He was pointing at something in the vendor’s display—a vial Harlow couldn’t quite make out, its contents swirling with an unnatural hue." | | 6 | "Morris’s case—the one that had haunted her for three years—had ties to this place." | | 7 | "His eyes—warm brown, like polished amber—flickered with something she couldn’t name." | | 8 | "She’d heard the rumors—whispers of a substance extracted from the bodies of the dead, a poison that bypassed the heart and found its way to the brain in a matter of minutes." | | 9 | "And Herrera—bright-eyed, scarred, meddling in affairs beyond his station—was their willing pawn." | | 10 | "But she’d also seen what it could do to people like Herrera—people who thought they were in control, who believed their medallions and their scars could protect them." | | 11 | "And somewhere in the distance, a bell rang—a sound that didn’t belong to this world." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1115 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 28 | | adverbRatio | 0.025112107623318385 | | lyAdverbCount | 2 | | lyAdverbRatio | 0.0017937219730941704 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 87 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 87 | | mean | 13.85 | | std | 7.25 | | cv | 0.524 | | sampleLengths | | 0 | 17 | | 1 | 19 | | 2 | 16 | | 3 | 2 | | 4 | 25 | | 5 | 24 | | 6 | 17 | | 7 | 4 | | 8 | 22 | | 9 | 9 | | 10 | 19 | | 11 | 3 | | 12 | 17 | | 13 | 9 | | 14 | 14 | | 15 | 13 | | 16 | 8 | | 17 | 9 | | 18 | 17 | | 19 | 14 | | 20 | 25 | | 21 | 16 | | 22 | 13 | | 23 | 12 | | 24 | 16 | | 25 | 11 | | 26 | 21 | | 27 | 16 | | 28 | 22 | | 29 | 21 | | 30 | 3 | | 31 | 3 | | 32 | 4 | | 33 | 12 | | 34 | 26 | | 35 | 16 | | 36 | 42 | | 37 | 20 | | 38 | 22 | | 39 | 22 | | 40 | 16 | | 41 | 8 | | 42 | 7 | | 43 | 11 | | 44 | 22 | | 45 | 14 | | 46 | 25 | | 47 | 11 | | 48 | 18 | | 49 | 11 |
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| 50.96% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 4 | | diversityRatio | 0.3333333333333333 | | totalSentences | 87 | | uniqueOpeners | 29 | |
| 85.47% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 78 | | matches | | 0 | "Somewhere in that maze of" | | 1 | "Too late for the full" |
| | ratio | 0.026 | |
| 61.03% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 31 | | totalSentences | 78 | | matches | | 0 | "She’d seen him at The" | | 1 | "She’d followed Herrera too many" | | 2 | "she called, her voice cutting" | | 3 | "Her polished shoes slapped against" | | 4 | "He vaulted over a dumpster," | | 5 | "She hauled herself up, her" | | 6 | "She gripped the railing, her" | | 7 | "She’d seen the maps in" | | 8 | "She descended the fire escape," | | 9 | "She kicked it aside, revealing" | | 10 | "Her hand hovered over the" | | 11 | "Her pulse quickened." | | 12 | "She reached the bottom, where" | | 13 | "He was pointing at something" | | 14 | "His scarred forearm was exposed" | | 15 | "She’d seen the files on" | | 16 | "She’d traced the investigation to" | | 17 | "She stepped forward, boots crunching" | | 18 | "she said, her voice low" | | 19 | "He turned, and for a" |
| | ratio | 0.397 | |
| 43.33% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 65 | | totalSentences | 78 | | matches | | 0 | "The rain fell in sheets," | | 1 | "Detective Harlow Quinn pulled her" | | 2 | "The figure ahead moved with" | | 3 | "She’d seen him at The" | | 4 | "The neon sign of the" | | 5 | "Harlow’s brown eyes narrowed." | | 6 | "She’d followed Herrera too many" | | 7 | "she called, her voice cutting" | | 8 | "Her polished shoes slapped against" | | 9 | "Herrera didn’t slow." | | 10 | "He vaulted over a dumpster," | | 11 | "Harlow cursed under her breath," | | 12 | "The alley ended in a" | | 13 | "She hauled herself up, her" | | 14 | "A gust of wind dislodged" | | 15 | "She gripped the railing, her" | | 16 | "She’d seen the maps in" | | 17 | "She descended the fire escape," | | 18 | "She kicked it aside, revealing" | | 19 | "The air rising from the" |
| | ratio | 0.833 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 3 | | totalSentences | 78 | | matches | | 0 | "Now, he was darting into" | | 1 | "If Herrera was here, if" | | 2 | "Now, standing in this hellish" |
| | ratio | 0.038 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 53 | | technicalSentenceCount | 3 | | matches | | 0 | "Now, he was darting into an alley that narrowed between two brick buildings, their fire escapes twisted like the entrails of some great beast." | | 1 | "The market sprawled before her like a fever dream: hooded figures trading vials of glowing liquid, a woman in a moth-eaten coat haggling over a silver amulet, a…" | | 2 | "He was pointing at something in the vendor’s display—a vial Harlow couldn’t quite make out, its contents swirling with an unnatural hue." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 7 | | uselessAdditionCount | 4 | | matches | | 0 | "she called, her voice cutting through the storm" | | 1 | "she said, her voice low" | | 2 | "She took, her hand inching toward her holster" | | 3 | "she said, her voice steady despite the tremor in her chest" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 4 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 15 | | tagDensity | 0.267 | | leniency | 0.533 | | rawRatio | 0 | | effectiveRatio | 0 | |