| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 6 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 21 | | tagDensity | 0.286 | | leniency | 0.571 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 90.33% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 517 | | totalAiIsmAdverbs | 1 | | 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) | |
| 70.99% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 517 | | totalAiIsms | 3 | | found | | | highlights | | 0 | "stark" | | 1 | "echoing" | | 2 | "intensity" |
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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 | 19 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 19 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 33 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 33 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 517 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 4 | | unquotedAttributions | 0 | | matches | (empty) | |
| 26.92% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 15 | | wordCount | 325 | | uniqueNames | 2 | | maxNameDensity | 2.46 | | worstName | "Lucien" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Lucien" | | discoveredNames | | | persons | | | places | (empty) | | globalScore | 0.269 | | windowScore | 0.5 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 18 | | 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 | 517 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 33 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 22 | | mean | 23.5 | | std | 14.25 | | cv | 0.607 | | sampleLengths | | 0 | 10 | | 1 | 37 | | 2 | 8 | | 3 | 43 | | 4 | 23 | | 5 | 5 | | 6 | 50 | | 7 | 25 | | 8 | 48 | | 9 | 7 | | 10 | 17 | | 11 | 36 | | 12 | 16 | | 13 | 17 | | 14 | 19 | | 15 | 15 | | 16 | 5 | | 17 | 5 | | 18 | 43 | | 19 | 30 | | 20 | 27 | | 21 | 31 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 19 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 45 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 33 | | ratio | 0 | | matches | (empty) | |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 329 | | adjectiveStacks | 1 | | stackExamples | | 0 | "small crescent-shaped scar" |
| | adverbCount | 9 | | adverbRatio | 0.02735562310030395 | | lyAdverbCount | 4 | | lyAdverbRatio | 0.0121580547112462 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 33 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 33 | | mean | 15.67 | | std | 7.42 | | cv | 0.474 | | sampleLengths | | 0 | 10 | | 1 | 19 | | 2 | 18 | | 3 | 8 | | 4 | 17 | | 5 | 26 | | 6 | 18 | | 7 | 5 | | 8 | 5 | | 9 | 26 | | 10 | 24 | | 11 | 14 | | 12 | 11 | | 13 | 33 | | 14 | 15 | | 15 | 7 | | 16 | 17 | | 17 | 16 | | 18 | 20 | | 19 | 16 | | 20 | 17 | | 21 | 19 | | 22 | 15 | | 23 | 5 | | 24 | 5 | | 25 | 20 | | 26 | 23 | | 27 | 8 | | 28 | 22 | | 29 | 20 | | 30 | 7 | | 31 | 27 | | 32 | 4 |
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| 95.96% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 0 | | diversityRatio | 0.5757575757575758 | | totalSentences | 33 | | uniqueOpeners | 19 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 19 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 0 | | totalSentences | 19 | | matches | (empty) | | ratio | 0 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 18 | | totalSentences | 19 | | matches | | 0 | "Aurora turns the topmost deadbolt," | | 1 | "Platinum hair catches the harsh" | | 2 | "Lucien steps across the threshold" | | 3 | "The musky scent of rain" | | 4 | "Aurora says, her hand remaining" | | 5 | "An amber eye locks onto" | | 6 | "Lucien tilts his head, platinum" | | 7 | "Aurora says, her jaw tightening" | | 8 | "Lucien steps closer, closing the" | | 9 | "Aurora’s breath catches, the memory" | | 10 | "Ptolemy weaves between Lucien’s tailored" | | 11 | "Aurora says, her voice dropping" | | 12 | "Lucien slams the ivory cane" | | 13 | "Lucien gestures broadly with a" | | 14 | "Aurora steps hard onto his" | | 15 | "Lucien doesn't flinch, his heterochromatic" | | 16 | "Aurora whispers, her chest rising" | | 17 | "Lucien murmurs, his hand rising" |
| | ratio | 0.947 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 19 | | matches | (empty) | | ratio | 0 | |
| 77.92% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 11 | | technicalSentenceCount | 1 | | matches | | 0 | "Lucien doesn't flinch, his heterochromatic gaze remaining fixed, burning into her bright blue eyes with an intensity that leaves her skin prickling." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 6 | | uselessAdditionCount | 2 | | matches | | 0 | "Aurora says, her jaw tightening" | | 1 | "Aurora says, her voice dropping an octave, losing its edge" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 4 | | fancyCount | 1 | | fancyTags | | 0 | "Aurora whispers (whisper)" |
| | dialogueSentences | 21 | | tagDensity | 0.19 | | leniency | 0.381 | | rawRatio | 0.25 | | effectiveRatio | 0.095 | |