| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 3 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 6 | | tagDensity | 0.5 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 58.85% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 243 | | 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) | |
| 0.00% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 243 | | totalAiIsms | 5 | | found | | | highlights | | 0 | "thundered" | | 1 | "charged" | | 2 | "tension" | | 3 | "scanning" | | 4 | "encounter" |
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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 | 22 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 22 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 24 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 24 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 242 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 4 | | unquotedAttributions | 0 | | matches | (empty) | |
| 79.58% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 5 | | wordCount | 213 | | uniqueNames | 2 | | maxNameDensity | 1.41 | | worstName | "Aurora" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Aurora" | | discoveredNames | | | persons | | | places | (empty) | | globalScore | 0.796 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 15 | | 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 | 242 | | matches | (empty) | |
| 27.78% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 24 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 15 | | mean | 16.13 | | std | 10.3 | | cv | 0.639 | | sampleLengths | | 0 | 29 | | 1 | 10 | | 2 | 30 | | 3 | 1 | | 4 | 32 | | 5 | 9 | | 6 | 9 | | 7 | 21 | | 8 | 12 | | 9 | 16 | | 10 | 33 | | 11 | 7 | | 12 | 20 | | 13 | 5 | | 14 | 8 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 22 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 37 | | matches | (empty) | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 3 | | semicolonCount | 0 | | flaggedSentences | 2 | | totalSentences | 24 | | ratio | 0.083 | | matches | | 0 | "Charcoal suit impeccable, platinum hair slicked back, those mismatched eyes — one amber, one black — sizing her up with surgical precision." | | 1 | "Aurora's hand reflexively touched the small crescent-shaped scar on her left wrist — a nervous tell she'd never quite conquered." |
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| 85.31% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 214 | | adjectiveStacks | 1 | | stackExamples | | 0 | "small crescent-shaped scar" |
| | adverbCount | 10 | | adverbRatio | 0.04672897196261682 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.02336448598130841 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 24 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 24 | | mean | 10.08 | | std | 6.08 | | cv | 0.603 | | sampleLengths | | 0 | 17 | | 1 | 12 | | 2 | 4 | | 3 | 6 | | 4 | 10 | | 5 | 20 | | 6 | 1 | | 7 | 10 | | 8 | 22 | | 9 | 9 | | 10 | 3 | | 11 | 6 | | 12 | 3 | | 13 | 6 | | 14 | 12 | | 15 | 12 | | 16 | 7 | | 17 | 9 | | 18 | 10 | | 19 | 23 | | 20 | 7 | | 21 | 20 | | 22 | 5 | | 23 | 8 |
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| 100.00% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 0 | | diversityRatio | 0.7916666666666666 | | totalSentences | 24 | | uniqueOpeners | 19 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 20 | | matches | | 0 | "Slowly, she set down her" |
| | ratio | 0.05 | |
| 80.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 7 | | totalSentences | 20 | | matches | | 0 | "She knew that rhythm." | | 1 | "Her heart thundered against her" | | 2 | "He stepped forward." | | 3 | "She didn't move, blocking the" | | 4 | "Their bodies nearly touched, a" | | 5 | "His gaze lingered on the" | | 6 | "he asked, already moving inside" |
| | ratio | 0.35 | |
| 60.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 16 | | totalSentences | 20 | | matches | | 0 | "The knock came sharp and" | | 1 | "Aurora froze, takeout container halfway" | | 2 | "She knew that rhythm." | | 3 | "Her heart thundered against her" | | 4 | "Charcoal suit impeccable, platinum hair" | | 5 | "Aurora said, her voice flat" | | 6 | "A slight smile." | | 7 | "He stepped forward." | | 8 | "She didn't move, blocking the" | | 9 | "Their bodies nearly touched, a" | | 10 | "The question was more accusation" | | 11 | "Lucien's ivory-handled cane tapped against" | | 12 | "The half-demon fixer looked past" | | 13 | "His gaze lingered on the" | | 14 | "he asked, already moving inside" | | 15 | "Aurora's hand reflexively touched the" |
| | ratio | 0.8 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 20 | | matches | (empty) | | ratio | 0 | |
| 0.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 10 | | technicalSentenceCount | 3 | | matches | | 0 | "The knock came sharp and staccato, three precise raps that cut through the quiet of her flat." | | 1 | "Her heart thundered against her ribcage, a betraying rhythm that suggested her body remembered what her mind wanted to forget." | | 2 | "Their bodies nearly touched, a charged proximity that crackled with unresolved tension." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 3 | | uselessAdditionCount | 1 | | matches | | 0 | "Aurora said, her voice flat" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 3 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 6 | | tagDensity | 0.5 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |