| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 5 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 22 | | tagDensity | 0.227 | | leniency | 0.455 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 94.30% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 877 | | totalAiIsmAdverbs | 1 | | 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) | |
| 65.79% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 877 | | totalAiIsms | 6 | | found | | | highlights | | 0 | "echo" | | 1 | "footsteps" | | 2 | "weight" | | 3 | "dancing" | | 4 | "tinged" | | 5 | "raced" |
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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 | 67 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 67 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 84 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 45 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 865 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 5 | | unquotedAttributions | 0 | | matches | (empty) | |
| 42.31% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 25 | | wordCount | 650 | | uniqueNames | 10 | | maxNameDensity | 2.15 | | worstName | "Quinn" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Quinn" | | discoveredNames | | Camden | 1 | | High | 1 | | Street | 1 | | Harlow | 1 | | Quinn | 14 | | Morris | 3 | | Tube | 1 | | Metropolitan | 1 | | Police | 1 | | Spain | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Morris" | | 3 | "Police" |
| | places | | 0 | "Camden" | | 1 | "High" | | 2 | "Street" | | 3 | "Spain" |
| | globalScore | 0.423 | | windowScore | 0.833 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 46 | | 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 | 865 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 84 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 37 | | mean | 23.38 | | std | 14.42 | | cv | 0.617 | | sampleLengths | | 0 | 38 | | 1 | 3 | | 2 | 37 | | 3 | 49 | | 4 | 29 | | 5 | 34 | | 6 | 22 | | 7 | 11 | | 8 | 27 | | 9 | 5 | | 10 | 40 | | 11 | 41 | | 12 | 35 | | 13 | 14 | | 14 | 46 | | 15 | 20 | | 16 | 28 | | 17 | 3 | | 18 | 28 | | 19 | 13 | | 20 | 22 | | 21 | 5 | | 22 | 18 | | 23 | 21 | | 24 | 19 | | 25 | 7 | | 26 | 64 | | 27 | 5 | | 28 | 29 | | 29 | 23 | | 30 | 13 | | 31 | 30 | | 32 | 20 | | 33 | 23 | | 34 | 34 | | 35 | 5 | | 36 | 4 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 67 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 116 | | matches | (empty) | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 6 | | semicolonCount | 0 | | flaggedSentences | 6 | | totalSentences | 84 | | ratio | 0.071 | | matches | | 0 | "Detective Harlow Quinn's boots splashed through puddles as she pursued the figure ahead—a blur of dark clothing weaving between late-night pedestrians." | | 1 | "There—movement near a boarded-up shop entrance." | | 2 | "Construction equipment littered the space—this had been part of the Tube expansion project, abandoned when funding dried up." | | 3 | "A faint glow appeared around a bend—candlelight flickering through a doorway." | | 4 | "The suspect stood at the platform edge, pulling something from their pocket—a small white object." | | 5 | "Quinn thought of Morris—his laugh, his terrible jokes, the way his eyes had widened in those final moments as something impossible tore through reality." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 660 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 14 | | adverbRatio | 0.021212121212121213 | | lyAdverbCount | 2 | | lyAdverbRatio | 0.0030303030303030303 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 84 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 84 | | mean | 10.3 | | std | 6.67 | | cv | 0.647 | | sampleLengths | | 0 | 17 | | 1 | 21 | | 2 | 3 | | 3 | 15 | | 4 | 11 | | 5 | 11 | | 6 | 5 | | 7 | 16 | | 8 | 16 | | 9 | 12 | | 10 | 6 | | 11 | 15 | | 12 | 8 | | 13 | 12 | | 14 | 12 | | 15 | 10 | | 16 | 4 | | 17 | 18 | | 18 | 2 | | 19 | 9 | | 20 | 2 | | 21 | 2 | | 22 | 23 | | 23 | 5 | | 24 | 5 | | 25 | 17 | | 26 | 18 | | 27 | 6 | | 28 | 10 | | 29 | 5 | | 30 | 10 | | 31 | 10 | | 32 | 4 | | 33 | 5 | | 34 | 15 | | 35 | 11 | | 36 | 5 | | 37 | 9 | | 38 | 3 | | 39 | 12 | | 40 | 17 | | 41 | 14 | | 42 | 15 | | 43 | 5 | | 44 | 3 | | 45 | 11 | | 46 | 14 | | 47 | 3 | | 48 | 2 | | 49 | 12 |
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| 96.03% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 1 | | diversityRatio | 0.5833333333333334 | | totalSentences | 84 | | uniqueOpeners | 49 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 63 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 12 | | totalSentences | 63 | | matches | | 0 | "She yanked it free and" | | 1 | "She hauled herself over scaffolding" | | 2 | "She pressed her back against" | | 3 | "She pulled out her torch," | | 4 | "She peered around the corner." | | 5 | "She reached for her warrant" | | 6 | "He gestured at the market" | | 7 | "Her jaw tightened." | | 8 | "His hand went to the" | | 9 | "They handed over the bone" | | 10 | "She had to decide." | | 11 | "She clicked off her radio." |
| | ratio | 0.19 | |
| 39.37% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 53 | | totalSentences | 63 | | matches | | 0 | "The rain hammered down on" | | 1 | "Detective Harlow Quinn's boots splashed" | | 2 | "The suspect glanced back, face" | | 3 | "Quinn followed, her worn leather" | | 4 | "She yanked it free and" | | 5 | "Mud sucked at her shoes." | | 6 | "The suspect was already scrambling" | | 7 | "Quinn's lungs burned, but eighteen" | | 8 | "She hauled herself over scaffolding" | | 9 | "There—movement near a boarded-up shop" | | 10 | "The suspect pried at loose" | | 11 | "Quinn sprinted forward, but they'd" | | 12 | "She pressed her back against" | | 13 | "Rain dripped from her salt-and-pepper" | | 14 | "Quinn clicked her radio." | | 15 | "The suspect would be gone" | | 16 | "Quinn ducked through the gap." | | 17 | "The darkness inside was absolute." | | 18 | "She pulled out her torch," | | 19 | "Construction equipment littered the space—this" |
| | ratio | 0.841 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 63 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 37 | | technicalSentenceCount | 2 | | matches | | 0 | "She pulled out her torch, its beam cutting through dust motes and revealing a staircase leading down." | | 1 | "Dozens of stalls filled the station, their wares illuminated by floating orbs of light that defied explanation." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 5 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |