| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 15 | | adverbTagCount | 1 | | adverbTags | | 0 | "His amber eye softened almost [almost]" |
| | dialogueSentences | 32 | | tagDensity | 0.469 | | leniency | 0.938 | | rawRatio | 0.067 | | effectiveRatio | 0.063 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 739 | | 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) | |
| 66.17% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 739 | | totalAiIsms | 5 | | found | | | highlights | | 0 | "familiar" | | 1 | "weight" | | 2 | "traced" | | 3 | "silence" | | 4 | "throbbed" |
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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 | 59 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 59 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 76 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 27 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 730 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 12 | | unquotedAttributions | 0 | | matches | (empty) | |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 39 | | wordCount | 505 | | uniqueNames | 7 | | maxNameDensity | 3.17 | | worstName | "Rory" | | maxWindowNameDensity | 4 | | worstWindowName | "Rory" | | discoveredNames | | Eva | 11 | | Rory | 16 | | Moreau | 1 | | French | 1 | | Lucien | 7 | | Marseille | 1 | | Ptolemy | 2 |
| | persons | | 0 | "Eva" | | 1 | "Rory" | | 2 | "Moreau" | | 3 | "Lucien" | | 4 | "Ptolemy" |
| | places | | | globalScore | 0 | | windowScore | 0.333 | |
| 85.90% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 39 | | glossingSentenceCount | 1 | | matches | | 0 | "not quite a smile, but closer than before" |
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| 63.01% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 1.37 | | wordCount | 730 | | matches | | 0 | "not quite a smile, but closer than before" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 76 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 38 | | mean | 19.21 | | std | 11.01 | | cv | 0.573 | | sampleLengths | | 0 | 20 | | 1 | 23 | | 2 | 18 | | 3 | 7 | | 4 | 44 | | 5 | 17 | | 6 | 46 | | 7 | 12 | | 8 | 12 | | 9 | 5 | | 10 | 45 | | 11 | 21 | | 12 | 24 | | 13 | 15 | | 14 | 13 | | 15 | 23 | | 16 | 9 | | 17 | 26 | | 18 | 20 | | 19 | 28 | | 20 | 27 | | 21 | 20 | | 22 | 31 | | 23 | 14 | | 24 | 4 | | 25 | 25 | | 26 | 10 | | 27 | 7 | | 28 | 11 | | 29 | 41 | | 30 | 24 | | 31 | 9 | | 32 | 11 | | 33 | 16 | | 34 | 11 | | 35 | 19 | | 36 | 19 | | 37 | 3 |
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| 99.32% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 59 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 85 | | matches | (empty) | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 9 | | semicolonCount | 0 | | flaggedSentences | 8 | | totalSentences | 76 | | ratio | 0.105 | | matches | | 0 | "The deadbolts clicked back in a frantic stutter—one, two, three—then the door to Eva's flat tore open against the chain." | | 1 | "Books teetered in stacks across every surface—scrolls pinned to the walls with knives, research notes taped over the stove." | | 2 | "She wore a dark jacket over her delivery uniform, sleeves rolled past her wrists—past the small crescent scar on her left wrist, pale against her skin." | | 3 | "His charcoal suit looked untouched by the flat's chaos—sharp lapels, crisp shirt, platinum hair slicked back without mercy." | | 4 | "The blade inside stayed hidden, but she knew it lived there—thin, vicious, patient." | | 5 | "She remembered Marseille, the half-demon's mouth on hers in a rain-soaked alley behind a club—teeth too sharp, promises too broken." | | 6 | "Lucien moved then—slow, precise." | | 7 | "Lucien's mouth curved—not quite a smile, but closer than before." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 520 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 15 | | adverbRatio | 0.028846153846153848 | | lyAdverbCount | 0 | | lyAdverbRatio | 0 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 76 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 76 | | mean | 9.61 | | std | 5.64 | | cv | 0.587 | | sampleLengths | | 0 | 20 | | 1 | 23 | | 2 | 15 | | 3 | 3 | | 4 | 7 | | 5 | 10 | | 6 | 19 | | 7 | 15 | | 8 | 12 | | 9 | 5 | | 10 | 12 | | 11 | 8 | | 12 | 26 | | 13 | 3 | | 14 | 9 | | 15 | 6 | | 16 | 6 | | 17 | 2 | | 18 | 3 | | 19 | 17 | | 20 | 18 | | 21 | 10 | | 22 | 21 | | 23 | 9 | | 24 | 15 | | 25 | 10 | | 26 | 5 | | 27 | 7 | | 28 | 6 | | 29 | 20 | | 30 | 3 | | 31 | 5 | | 32 | 4 | | 33 | 15 | | 34 | 11 | | 35 | 7 | | 36 | 13 | | 37 | 15 | | 38 | 5 | | 39 | 8 | | 40 | 7 | | 41 | 20 | | 42 | 11 | | 43 | 9 | | 44 | 7 | | 45 | 12 | | 46 | 12 | | 47 | 3 | | 48 | 11 | | 49 | 4 |
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| 53.07% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 3 | | diversityRatio | 0.34210526315789475 | | totalSentences | 76 | | uniqueOpeners | 26 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 53 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 13 | | totalSentences | 53 | | matches | | 0 | "Her black hair clung to" | | 1 | "She wore a dark jacket" | | 2 | "Her breath hitched." | | 3 | "His charcoal suit looked untouched" | | 4 | "She hated that name from" | | 5 | "His amber eye softened, almost" | | 6 | "She remembered Marseille, the half-demon's" | | 7 | "she said, quieter now" | | 8 | "She gestured to the chaos" | | 9 | "His hand closed around her" | | 10 | "His thumb traced the crescent" | | 11 | "She tapped the scroll against" | | 12 | "she told them both" |
| | ratio | 0.245 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 50 | | totalSentences | 53 | | matches | | 0 | "The deadbolts clicked back in" | | 1 | "Rory froze on the curry-scented" | | 2 | "Eva's hair had been chopped" | | 3 | "Ptolemy wound between Rory's boots," | | 4 | "Rory stepped into the cramped" | | 5 | "Books teetered in stacks across" | | 6 | "The air hung thick with" | | 7 | "Eva tugged her inside, chain" | | 8 | "Rory dropped her bag on" | | 9 | "Her black hair clung to" | | 10 | "She wore a dark jacket" | | 11 | "Eva's grin faltered." | | 12 | "The door clicked shut behind" | | 13 | "Her breath hitched." | | 14 | "Lucien Moreau stood beside Eva's" | | 15 | "His charcoal suit looked untouched" | | 16 | "Rory's voice stayed flat, but" | | 17 | "Eva hovered between them, small" | | 18 | "Lucien's accent curled, low and" | | 19 | "She hated that name from" |
| | ratio | 0.943 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 53 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 18 | | technicalSentenceCount | 1 | | matches | | 0 | "The air hung thick with old paper and some sharp incense that scratched her throat." |
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| 91.67% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 15 | | uselessAdditionCount | 1 | | matches | | 0 | "Rory's voice stayed, but her fingers curled tight around the strap of her bag" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 6 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 32 | | tagDensity | 0.188 | | leniency | 0.375 | | rawRatio | 0.167 | | effectiveRatio | 0.063 | |