| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 1 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 4 | | tagDensity | 0.25 | | leniency | 0.5 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 617 | | 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) | |
| 10.86% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 617 | | totalAiIsms | 11 | | found | | | highlights | | 0 | "echoed" | | 1 | "familiar" | | 2 | "standard" | | 3 | "glinting" | | 4 | "loomed" | | 5 | "gleaming" | | 6 | "pulse" | | 7 | "quickened" | | 8 | "weight" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 0 | | maxInWindow | 0 | | found | (empty) | | highlights | (empty) | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 50 | | matches | (empty) | |
| 85.71% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 1 | | narrationSentences | 50 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 52 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 31 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 623 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 3 | | unquotedAttributions | 0 | | matches | (empty) | |
| 57.41% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 28 | | wordCount | 594 | | uniqueNames | 11 | | maxNameDensity | 1.85 | | worstName | "Quinn" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Quinn" | | discoveredNames | | Detective | 1 | | Quinn | 11 | | Chalk | 1 | | Farm | 1 | | Road | 1 | | Tomás | 1 | | Herrera | 6 | | Morris | 2 | | Underground | 2 | | Saint | 1 | | Christopher | 1 |
| | persons | | 0 | "Detective" | | 1 | "Quinn" | | 2 | "Tomás" | | 3 | "Herrera" | | 4 | "Morris" | | 5 | "Saint" | | 6 | "Christopher" |
| | places | | | globalScore | 0.574 | | windowScore | 0.833 | |
| 38.89% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 45 | | glossingSentenceCount | 2 | | matches | | 0 | "looked like dried blood" | | 1 | "weapons that seemed to drink in what little light reached them" |
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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 | 623 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 52 | | matches | (empty) | |
| 59.11% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 17 | | mean | 36.65 | | std | 13.08 | | cv | 0.357 | | sampleLengths | | 0 | 53 | | 1 | 42 | | 2 | 51 | | 3 | 11 | | 4 | 47 | | 5 | 45 | | 6 | 41 | | 7 | 35 | | 8 | 37 | | 9 | 55 | | 10 | 24 | | 11 | 26 | | 12 | 17 | | 13 | 23 | | 14 | 32 | | 15 | 54 | | 16 | 30 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 50 | | matches | (empty) | |
| 74.21% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 106 | | matches | | 0 | "was heading" | | 1 | "was going" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 6 | | semicolonCount | 0 | | flaggedSentences | 6 | | totalSentences | 52 | | ratio | 0.115 | | matches | | 0 | "Three blocks of pursuit had led nowhere - every time she closed the gap, her target slipped away like smoke." | | 1 | "A flash of movement - the figure emerged from behind the bin and bolted toward a rusty maintenance door set into the brick wall." | | 2 | "Stale air wafted up from below, carrying traces of incense and something else - something that made her nose itch." | | 3 | "But Herrera knew something about Morris's disappearance - she was certain of it." | | 4 | "Stalls lined the curved walls, selling items that defied explanation - bottles of swirling mist, jewelry that moved on its own, weapons that seemed to drink in what little light reached them." | | 5 | "The crowd parted around her - whether responding to her military bearing or sensing she didn't belong, she couldn't tell." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 589 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 12 | | adverbRatio | 0.02037351443123939 | | lyAdverbCount | 4 | | lyAdverbRatio | 0.006791171477079796 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 52 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 52 | | mean | 11.98 | | std | 5.84 | | cv | 0.487 | | sampleLengths | | 0 | 17 | | 1 | 16 | | 2 | 20 | | 3 | 7 | | 4 | 14 | | 5 | 1 | | 6 | 10 | | 7 | 10 | | 8 | 24 | | 9 | 19 | | 10 | 8 | | 11 | 11 | | 12 | 8 | | 13 | 8 | | 14 | 11 | | 15 | 20 | | 16 | 5 | | 17 | 13 | | 18 | 4 | | 19 | 13 | | 20 | 10 | | 21 | 10 | | 22 | 20 | | 23 | 11 | | 24 | 8 | | 25 | 11 | | 26 | 11 | | 27 | 5 | | 28 | 7 | | 29 | 16 | | 30 | 14 | | 31 | 32 | | 32 | 10 | | 33 | 13 | | 34 | 14 | | 35 | 10 | | 36 | 14 | | 37 | 12 | | 38 | 12 | | 39 | 5 | | 40 | 8 | | 41 | 15 | | 42 | 3 | | 43 | 8 | | 44 | 7 | | 45 | 14 | | 46 | 9 | | 47 | 20 | | 48 | 25 | | 49 | 6 |
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| 71.79% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 1 | | diversityRatio | 0.4423076923076923 | | totalSentences | 52 | | uniqueOpeners | 23 | |
| 68.03% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 49 | | matches | | 0 | "Just her own judgment and" |
| | ratio | 0.02 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 10 | | totalSentences | 49 | | matches | | 0 | "Her shoes splashed through puddles," | | 1 | "She edged forward, water dripping" | | 2 | "Her watch showed 11:47 PM." | | 3 | "She'd radioed her position twenty" | | 4 | "Her training screamed at her" | | 5 | "She pocketed it without thinking." | | 6 | "She spotted Herrera's familiar Saint" | | 7 | "He was heading toward another" | | 8 | "Her pulse quickened." | | 9 | "She had crossed some invisible" |
| | ratio | 0.204 | |
| 41.63% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 41 | | totalSentences | 49 | | matches | | 0 | "Rain pelted Detective Quinn's face" | | 1 | "Her shoes splashed through puddles," | | 2 | "The figure darted down a" | | 3 | "Quinn's hand brushed the grip" | | 4 | "She edged forward, water dripping" | | 5 | "A flash of movement -" | | 6 | "Quinn recognized the familiar olive" | | 7 | "The former paramedic she'd been" | | 8 | "Quinn's voice carried over the" | | 9 | "Herrera yanked the door open" | | 10 | "Quinn reached the entrance seconds" | | 11 | "The door opened to a" | | 12 | "Her watch showed 11:47 PM." | | 13 | "She'd radioed her position twenty" | | 14 | "Quinn pulled out her torch" | | 15 | "The beam cut through darkness," | | 16 | "Her training screamed at her" | | 17 | "The stairs ended at a" | | 18 | "Quinn swept her light across" | | 19 | "A bone-white token lay on" |
| | ratio | 0.837 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 49 | | matches | (empty) | | ratio | 0 | |
| 53.57% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 32 | | technicalSentenceCount | 4 | | matches | | 0 | "Stale air wafted up from below, carrying traces of incense and something else - something that made her nose itch." | | 1 | "Stalls lined the curved walls, selling items that defied explanation - bottles of swirling mist, jewelry that moved on its own, weapons that seemed to drink in …" | | 2 | "The crowd parted around her - whether responding to her military bearing or sensing she didn't belong, she couldn't tell." | | 3 | "The weight of her gun was reassuring against her hip as she followed Herrera's trail, trying to look like she knew where she was going." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 1 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |