| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 20 | | adverbTagCount | 2 | | adverbTags | | 0 | "hand waved dismissively [dismissively]" | | 1 | "The vial disappeared back [back]" |
| | dialogueSentences | 74 | | tagDensity | 0.27 | | leniency | 0.541 | | rawRatio | 0.1 | | effectiveRatio | 0.054 | |
| 93.69% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1584 | | totalAiIsmAdverbs | 2 | | 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) | |
| 43.18% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1584 | | totalAiIsms | 18 | | found | | | highlights | | 0 | "familiar" | | 1 | "weight" | | 2 | "oppressive" | | 3 | "flickered" | | 4 | "gloom" | | 5 | "silence" | | 6 | "flicked" | | 7 | "etched" | | 8 | "standard" | | 9 | "glint" | | 10 | "pulsed" | | 11 | "could feel" | | 12 | "whisper" |
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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 | 0 | | narrationSentences | 152 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 1 | | narrationSentences | 152 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 203 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 29 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 1 | | markdownWords | 1 | | totalWords | 1579 | | ratio | 0.001 | | matches | | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 13 | | unquotedAttributions | 0 | | matches | (empty) | |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 68 | | wordCount | 1170 | | uniqueNames | 9 | | maxNameDensity | 2.14 | | worstName | "Quinn" | | maxWindowNameDensity | 5 | | worstWindowName | "Eva" | | discoveredNames | | Tube | 2 | | Camden | 2 | | Harlow | 1 | | Quinn | 25 | | Italian | 1 | | Carter | 15 | | Eva | 18 | | Kowalski | 1 | | Market | 3 |
| | persons | | 0 | "Camden" | | 1 | "Harlow" | | 2 | "Quinn" | | 3 | "Carter" | | 4 | "Eva" | | 5 | "Kowalski" |
| | places | | | globalScore | 0.432 | | windowScore | 0 | |
| 44.74% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 95 | | glossingSentenceCount | 4 | | matches | | 0 | "quite believe" | | 1 | "looked like human skin" | | 2 | "cloak that seemed to drink the light" | | 3 | "seemed longer than she remembered, the air thicker" |
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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 | 1579 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 203 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 80 | | mean | 19.74 | | std | 12.99 | | cv | 0.658 | | sampleLengths | | 0 | 62 | | 1 | 23 | | 2 | 56 | | 3 | 27 | | 4 | 26 | | 5 | 19 | | 6 | 9 | | 7 | 48 | | 8 | 19 | | 9 | 9 | | 10 | 47 | | 11 | 5 | | 12 | 30 | | 13 | 12 | | 14 | 41 | | 15 | 19 | | 16 | 7 | | 17 | 7 | | 18 | 21 | | 19 | 9 | | 20 | 36 | | 21 | 10 | | 22 | 5 | | 23 | 37 | | 24 | 3 | | 25 | 9 | | 26 | 9 | | 27 | 47 | | 28 | 15 | | 29 | 32 | | 30 | 3 | | 31 | 37 | | 32 | 10 | | 33 | 27 | | 34 | 9 | | 35 | 16 | | 36 | 10 | | 37 | 31 | | 38 | 13 | | 39 | 11 | | 40 | 6 | | 41 | 19 | | 42 | 14 | | 43 | 2 | | 44 | 24 | | 45 | 26 | | 46 | 30 | | 47 | 9 | | 48 | 40 | | 49 | 27 |
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| 91.41% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 6 | | totalSentences | 152 | | matches | | 0 | "been dropped" | | 1 | "was frozen" | | 2 | "was clenched" | | 3 | "was fixed" | | 4 | "was used" | | 5 | "was obscured" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 219 | | matches | | 0 | "were watching" | | 1 | "was holding" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 4 | | semicolonCount | 0 | | flaggedSentences | 3 | | totalSentences | 203 | | ratio | 0.015 | | matches | | 0 | "His suit was too fine for this place—charcoal wool, Italian cut." | | 1 | "The beam caught something—a glint of metal, half-buried in the dirt." | | 2 | "The woman—Eva Kowalski—froze." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1176 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 38 | | adverbRatio | 0.03231292517006803 | | lyAdverbCount | 7 | | lyAdverbRatio | 0.005952380952380952 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 203 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 203 | | mean | 7.78 | | std | 5.05 | | cv | 0.649 | | sampleLengths | | 0 | 11 | | 1 | 17 | | 2 | 14 | | 3 | 20 | | 4 | 11 | | 5 | 12 | | 6 | 16 | | 7 | 11 | | 8 | 6 | | 9 | 23 | | 10 | 8 | | 11 | 3 | | 12 | 2 | | 13 | 4 | | 14 | 10 | | 15 | 11 | | 16 | 3 | | 17 | 3 | | 18 | 9 | | 19 | 8 | | 20 | 4 | | 21 | 7 | | 22 | 5 | | 23 | 4 | | 24 | 15 | | 25 | 17 | | 26 | 8 | | 27 | 8 | | 28 | 8 | | 29 | 8 | | 30 | 3 | | 31 | 2 | | 32 | 7 | | 33 | 3 | | 34 | 6 | | 35 | 6 | | 36 | 5 | | 37 | 16 | | 38 | 11 | | 39 | 3 | | 40 | 2 | | 41 | 7 | | 42 | 17 | | 43 | 6 | | 44 | 4 | | 45 | 8 | | 46 | 9 | | 47 | 12 | | 48 | 9 | | 49 | 11 |
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| 46.06% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 8 | | diversityRatio | 0.270935960591133 | | totalSentences | 203 | | uniqueOpeners | 55 | |
| 49.02% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 136 | | matches | | 0 | "Just the faintest scent of" | | 1 | "Just a look of sheer," |
| | ratio | 0.015 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 31 | | totalSentences | 136 | | matches | | 0 | "She adjusted the worn leather" | | 1 | "His suit was too fine" | | 2 | "His face was frozen in" | | 3 | "She didn’t turn." | | 4 | "He was younger, eager in" | | 5 | "His tie was already loosened," | | 6 | "She ignored that." | | 7 | "She pried the fingers open." | | 8 | "She turned it over" | | 9 | "He shook his head." | | 10 | "She followed its pull, torchlight" | | 11 | "She knelt, brushing away the" | | 12 | "She pocketed both items" | | 13 | "he muttered, stepping closer" | | 14 | "She didn’t answer." | | 15 | "Her gaze was fixed on" | | 16 | "She pressed her palm against" | | 17 | "She shook him off" | | 18 | "She glanced their way, then" | | 19 | "Her green eyes widened behind" |
| | ratio | 0.228 | |
| 7.79% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 123 | | totalSentences | 136 | | matches | | 0 | "The abandoned Tube station beneath" | | 1 | "Detective Harlow Quinn stepped over" | | 2 | "The air hung thick, the" | | 3 | "She adjusted the worn leather" | | 4 | "A single bulb flickered overhead," | | 5 | "The beam from her torch" | | 6 | "A man, mid-thirties, sprawled on" | | 7 | "His suit was too fine" | | 8 | "The kind that didn’t come" | | 9 | "His face was frozen in" | | 10 | "Quinn crouched, gloved fingers hovering" | | 11 | "She didn’t turn." | | 12 | "The sharp click of heels" | | 13 | "the voice continued, smoother this" | | 14 | "A beat of silence." | | 15 | "Quinn exhaled through her nose." | | 16 | "DS Carter stepped beside her," | | 17 | "He was younger, eager in" | | 18 | "His tie was already loosened," | | 19 | "Quinn’s gaze flicked to the" |
| | ratio | 0.904 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 136 | | matches | (empty) | | ratio | 0 | |
| 61.22% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 35 | | technicalSentenceCount | 4 | | matches | | 0 | "His face was frozen in an expression of surprise, eyes wide, mouth slightly open as if he’d seen something he couldn’t quite believe." | | 1 | "The casing had a patina of verdigris, the kind that came with age or something less natural." | | 2 | "The air that rushed out was thick with the scent of spices and something older, something that made the hairs on her arms stand up." | | 3 | "The orbs of light around them dimmed, as if the Market itself was holding its breath." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 20 | | uselessAdditionCount | 1 | | matches | | 0 | "DS Carter stepped, his torchlight joining hers" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 5 | | fancyCount | 3 | | fancyTags | | 0 | "the voice continued (continue)" | | 1 | "he muttered (mutter)" | | 2 | "Eva muttered (mutter)" |
| | dialogueSentences | 74 | | tagDensity | 0.068 | | leniency | 0.135 | | rawRatio | 0.6 | | effectiveRatio | 0.081 | |