| 94.74% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 19 | | adverbTagCount | 2 | | adverbTags | | 0 | "Eva offered carefully [carefully]" | | 1 | "Quinn said coldly [coldly]" |
| | dialogueSentences | 38 | | tagDensity | 0.5 | | leniency | 1 | | rawRatio | 0.105 | | effectiveRatio | 0.105 | |
| 67.91% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1558 | | totalAiIsmAdverbs | 10 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | adverb | "deliberately" | | count | 1 |
| | 8 | |
| | highlights | | 0 | "softly" | | 1 | "nervously" | | 2 | "gently" | | 3 | "slightly" | | 4 | "carefully" | | 5 | "coldly" | | 6 | "slowly" | | 7 | "deliberately" | | 8 | "suddenly" |
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| 80.00% | AI-ism character names | Target: 0 AI-default names (17 tracked, −20% each) | | codexExemptions | (empty) | | found | | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 35.82% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1558 | | totalAiIsms | 20 | | found | | | highlights | | 0 | "chill" | | 1 | "stark" | | 2 | "weight" | | 3 | "echoing" | | 4 | "standard" | | 5 | "pristine" | | 6 | "intricate" | | 7 | "flicker" | | 8 | "stomach" | | 9 | "etched" | | 10 | "etching" | | 11 | "magnetic" | | 12 | "mechanical" | | 13 | "navigating" | | 14 | "unspoken" |
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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 | 87 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 0 | | narrationSentences | 87 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 105 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 44 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1555 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 16 | | unquotedAttributions | 0 | | matches | (empty) | |
| 41.30% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 47 | | wordCount | 1104 | | uniqueNames | 9 | | maxNameDensity | 2.17 | | worstName | "Quinn" | | maxWindowNameDensity | 3 | | worstWindowName | "Quinn" | | discoveredNames | | Harlow | 1 | | Quinn | 24 | | Camden | 2 | | Victorian | 1 | | Eva | 15 | | Kowalski | 1 | | Morris | 1 | | High | 1 | | Street | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Eva" | | 3 | "Kowalski" | | 4 | "Morris" |
| | places | | 0 | "Camden" | | 1 | "High" | | 2 | "Street" |
| | globalScore | 0.413 | | windowScore | 0.667 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 70 | | 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 | 1555 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 105 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 50 | | mean | 31.1 | | std | 19.1 | | cv | 0.614 | | sampleLengths | | 0 | 18 | | 1 | 81 | | 2 | 30 | | 3 | 14 | | 4 | 74 | | 5 | 39 | | 6 | 56 | | 7 | 32 | | 8 | 40 | | 9 | 54 | | 10 | 14 | | 11 | 74 | | 12 | 30 | | 13 | 22 | | 14 | 9 | | 15 | 43 | | 16 | 44 | | 17 | 33 | | 18 | 30 | | 19 | 27 | | 20 | 8 | | 21 | 46 | | 22 | 7 | | 23 | 43 | | 24 | 17 | | 25 | 81 | | 26 | 14 | | 27 | 32 | | 28 | 33 | | 29 | 10 | | 30 | 18 | | 31 | 48 | | 32 | 5 | | 33 | 27 | | 34 | 16 | | 35 | 28 | | 36 | 15 | | 37 | 47 | | 38 | 20 | | 39 | 21 | | 40 | 10 | | 41 | 24 | | 42 | 50 | | 43 | 25 | | 44 | 43 | | 45 | 34 | | 46 | 9 | | 47 | 30 | | 48 | 19 | | 49 | 11 |
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| 81.06% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 6 | | totalSentences | 87 | | matches | | 0 | "being dragged" | | 1 | "was singed" | | 2 | "were carbonized" | | 3 | "been found" | | 4 | "was coated" | | 5 | "were etched" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 185 | | matches | | |
| 61.22% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 3 | | semicolonCount | 0 | | flaggedSentences | 3 | | totalSentences | 105 | | ratio | 0.029 | | matches | | 0 | "Eva swallowed, her fingers again reaching to tuck her red hair behind her left ear—a tell Quinn had noted the first time they’d crossed paths during an artifact recovery inquiry six months ago." | | 1 | "Three years ago, DS Morris had been found in a locked cellar near the docks—no trauma, no poison, just a heart that had stopped beating and eyes filled with impossible terror." | | 2 | "The ballast between the ties was undisturbed, covered in a uniform blanket of gray grime—except for a distinct disturbance three yards further down the dark tunnel, away from where the platform ended." |
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| 98.83% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1121 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 38 | | adverbRatio | 0.03389830508474576 | | lyAdverbCount | 24 | | lyAdverbRatio | 0.021409455842997322 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 105 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 105 | | mean | 14.81 | | std | 8.45 | | cv | 0.57 | | sampleLengths | | 0 | 18 | | 1 | 19 | | 2 | 32 | | 3 | 30 | | 4 | 11 | | 5 | 19 | | 6 | 14 | | 7 | 11 | | 8 | 23 | | 9 | 40 | | 10 | 11 | | 11 | 28 | | 12 | 20 | | 13 | 11 | | 14 | 25 | | 15 | 14 | | 16 | 8 | | 17 | 10 | | 18 | 19 | | 19 | 21 | | 20 | 29 | | 21 | 25 | | 22 | 14 | | 23 | 11 | | 24 | 44 | | 25 | 19 | | 26 | 13 | | 27 | 10 | | 28 | 7 | | 29 | 14 | | 30 | 8 | | 31 | 9 | | 32 | 16 | | 33 | 16 | | 34 | 11 | | 35 | 12 | | 36 | 32 | | 37 | 33 | | 38 | 10 | | 39 | 20 | | 40 | 27 | | 41 | 4 | | 42 | 2 | | 43 | 2 | | 44 | 7 | | 45 | 11 | | 46 | 10 | | 47 | 18 | | 48 | 4 | | 49 | 3 |
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| 49.84% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 11 | | diversityRatio | 0.3619047619047619 | | totalSentences | 105 | | uniqueOpeners | 38 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 78 | | matches | (empty) | | ratio | 0 | |
| 91.79% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 25 | | totalSentences | 78 | | matches | | 0 | "She adjusted the collar of" | | 1 | "She glanced at the worn" | | 2 | "She approached the corpse, crouching" | | 3 | "Her sharp jaw tightened as" | | 4 | "His eyes were wide, the" | | 5 | "She pulled on a pair" | | 6 | "She gently turned the dead" | | 7 | "She adjusted her satchel, fingers" | | 8 | "Her fingers brushed something hard" | | 9 | "She drew it out into" | | 10 | "It was a coin-sized token" | | 11 | "It bore no denomination, only" | | 12 | "She set the token into" | | 13 | "She walked toward it, her" | | 14 | "She stopped beside a depression" | | 15 | "It was a small brass" | | 16 | "Its casing was coated in" | | 17 | "She stepped close, her breath" | | 18 | "It did not point north" | | 19 | "It spun slowly, deliberately, and" |
| | ratio | 0.321 | |
| 24.10% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 68 | | totalSentences | 78 | | matches | | 0 | "The subterranean air smelled of" | | 1 | "Detective Harlow Quinn ducked beneath" | | 2 | "She adjusted the collar of" | | 3 | "The light flattened the soot" | | 4 | "A body lay fifty yards" | | 5 | "The archivist was shivering inside" | | 6 | "Eva said, her voice echoing" | | 7 | "Quinn said, her voice low" | | 8 | "She glanced at the worn" | | 9 | "Quinn stepped down from the" | | 10 | "She approached the corpse, crouching" | | 11 | "Her sharp jaw tightened as" | | 12 | "The victim was male, thirty-something," | | 13 | "His eyes were wide, the" | | 14 | "Eva noted, lingering at the" | | 15 | "She pulled on a pair" | | 16 | "She gently turned the dead" | | 17 | "Eva ventured, her tone tight" | | 18 | "She adjusted her satchel, fingers" | | 19 | "Quinn replied, running her gloved" |
| | ratio | 0.872 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 78 | | matches | (empty) | | ratio | 0 | |
| 85.71% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 50 | | technicalSentenceCount | 4 | | matches | | 0 | "The victim was male, thirty-something, dressed in tailored wool that had no business being dragged through century-old coal dust." | | 1 | "Something was deeply, fundamentally wrong with the scene, tugging at a cold knot that had lived in the pit of her stomach for three years." | | 2 | "Three years ago, DS Morris had been found in a locked cellar near the docks—no trauma, no poison, just a heart that had stopped beating and eyes filled with imp…" | | 3 | "The cold of the tunnel was damp and heavy, but right before the brickwork, the air felt thin, vibrating with a high, faint pressure that made the fillings in he…" |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 19 | | uselessAdditionCount | 5 | | matches | | 0 | "Eva said, her voice echoing strangely in the tube" | | 1 | "Quinn said, her voice low and even" | | 2 | "Eva ventured, her tone tight" | | 3 | "Eva said, though her voice lacked conviction" | | 4 | "Quinn said, her voice dropping into the quiet cadence of certainty" |
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| 97.37% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 15 | | fancyCount | 2 | | fancyTags | | 0 | "Eva noted (note)" | | 1 | "Quinn murmured (murmur)" |
| | dialogueSentences | 38 | | tagDensity | 0.395 | | leniency | 0.789 | | rawRatio | 0.133 | | effectiveRatio | 0.105 | |