| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 2 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 5 | | tagDensity | 0.4 | | leniency | 0.8 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1055 | | 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) | |
| 33.65% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1055 | | totalAiIsms | 14 | | found | | | highlights | | 0 | "rhythmic" | | 1 | "familiar" | | 2 | "efficient" | | 3 | "dancing" | | 4 | "footsteps" | | 5 | "echoing" | | 6 | "hulking" | | 7 | "weight" | | 8 | "intricate" | | 9 | "echoed" | | 10 | "cacophony" | | 11 | "echo" | | 12 | "chilling" | | 13 | "pulsed" |
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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 | 82 | | matches | (empty) | |
| 73.17% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 3 | | narrationSentences | 82 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 85 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 29 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1051 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 0 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 26 | | wordCount | 1023 | | uniqueNames | 13 | | maxNameDensity | 0.68 | | worstName | "Quinn" | | maxWindowNameDensity | 1 | | worstWindowName | "Quinn" | | discoveredNames | | Soho | 1 | | Harlow | 1 | | Quinn | 7 | | Tomás | 1 | | Herrera | 6 | | Saint | 1 | | Christopher | 1 | | Camden | 1 | | Underground | 1 | | English | 1 | | Veil | 2 | | Market | 2 | | Morris | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Tomás" | | 3 | "Herrera" | | 4 | "Saint" | | 5 | "Christopher" | | 6 | "English" | | 7 | "Morris" |
| | places | | 0 | "Soho" | | 1 | "Camden" | | 2 | "Market" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 70 | | glossingSentenceCount | 1 | | matches | | 0 | "symbols that seemed to writhe in the poor light" |
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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 | 1051 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 85 | | matches | (empty) | |
| 76.61% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 21 | | mean | 50.05 | | std | 20.93 | | cv | 0.418 | | sampleLengths | | 0 | 62 | | 1 | 72 | | 2 | 75 | | 3 | 19 | | 4 | 85 | | 5 | 55 | | 6 | 47 | | 7 | 50 | | 8 | 35 | | 9 | 31 | | 10 | 12 | | 11 | 52 | | 12 | 62 | | 13 | 59 | | 14 | 43 | | 15 | 6 | | 16 | 82 | | 17 | 68 | | 18 | 52 | | 19 | 42 | | 20 | 42 |
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| 96.71% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 82 | | matches | | 0 | "were covered" | | 1 | "was gone" |
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| 61.11% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 3 | | totalVerbs | 144 | | matches | | 0 | "was flagging" | | 1 | "was reaching" | | 2 | "was vanishing" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 1 | | flaggedSentences | 1 | | totalSentences | 85 | | ratio | 0.012 | | matches | | 0 | "It wasn't a ticket reader; it was older, a solid block of iron and brass that shouldn't have been there." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1027 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 13 | | adverbRatio | 0.012658227848101266 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.004868549172346641 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 85 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 85 | | mean | 12.36 | | std | 5.93 | | cv | 0.48 | | sampleLengths | | 0 | 16 | | 1 | 22 | | 2 | 13 | | 3 | 11 | | 4 | 14 | | 5 | 16 | | 6 | 13 | | 7 | 15 | | 8 | 14 | | 9 | 11 | | 10 | 8 | | 11 | 13 | | 12 | 24 | | 13 | 19 | | 14 | 19 | | 15 | 3 | | 16 | 3 | | 17 | 22 | | 18 | 15 | | 19 | 14 | | 20 | 19 | | 21 | 9 | | 22 | 11 | | 23 | 14 | | 24 | 24 | | 25 | 3 | | 26 | 3 | | 27 | 12 | | 28 | 14 | | 29 | 10 | | 30 | 11 | | 31 | 21 | | 32 | 15 | | 33 | 11 | | 34 | 3 | | 35 | 13 | | 36 | 14 | | 37 | 8 | | 38 | 11 | | 39 | 12 | | 40 | 8 | | 41 | 12 | | 42 | 18 | | 43 | 8 | | 44 | 8 | | 45 | 16 | | 46 | 2 | | 47 | 12 | | 48 | 20 | | 49 | 19 |
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| 49.41% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 8 | | diversityRatio | 0.35294117647058826 | | totalSentences | 85 | | uniqueOpeners | 30 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 81 | | matches | (empty) | | ratio | 0 | |
| 61.98% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 32 | | totalSentences | 81 | | matches | | 0 | "He landed without a sound," | | 1 | "She ignored the stitch tightening" | | 2 | "She rounded the corner, her" | | 3 | "He glanced back, his warm" | | 4 | "Her voice was a raw" | | 5 | "He didn't listen." | | 6 | "He never did." | | 7 | "He pushed through a rusted" | | 8 | "She burst through the gate" | | 9 | "She saw him again, a" | | 10 | "Her boots hit the top" | | 11 | "Her pursuit had led her" | | 12 | "He was flagging." | | 13 | "He turned, his back pressed" | | 14 | "His olive skin was pallid" | | 15 | "She moved forward, keeping her" | | 16 | "He fumbled inside his jacket," | | 17 | "Her own hand instinctively dropped" | | 18 | "He shoved the bone token" | | 19 | "It wasn't a ticket reader;" |
| | ratio | 0.395 | |
| 21.73% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 71 | | totalSentences | 81 | | matches | | 0 | "The rain fell in sheets," | | 1 | "Detective Harlow Quinn’s breath rasped" | | 2 | "Water streamed from her closely" | | 3 | "Each lungful of air was" | | 4 | "He landed without a sound," | | 5 | "Quinn followed, her body aching" | | 6 | "She ignored the stitch tightening" | | 7 | "She rounded the corner, her" | | 8 | "The alley stank of stale" | | 9 | "Herrera was a dozen yards" | | 10 | "He glanced back, his warm" | | 11 | "A glimmer of silver at" | | 12 | "Her voice was a raw" | | 13 | "He didn't listen." | | 14 | "He never did." | | 15 | "He pushed through a rusted" | | 16 | "Quinn pushed harder, her strides" | | 17 | "The worn leather of her" | | 18 | "She burst through the gate" | | 19 | "Tourists huddled under awnings, their" |
| | ratio | 0.877 | |
| 61.73% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 81 | | matches | | 0 | "Before her, the Veil Market" |
| | ratio | 0.012 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 55 | | technicalSentenceCount | 3 | | matches | | 0 | "He glanced back, his warm brown eyes wide with a fear that seemed too big for a simple medic caught with an unlicensed practice." | | 1 | "She had felt the cold in that room, a wrongness that had settled deep in her bones and never left." | | 2 | "Before her, the Veil Market pulsed with a life that defied all reason." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 2 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |