| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 20 | | adverbTagCount | 1 | | adverbTags | | 0 | "she said instead [instead]" |
| | dialogueSentences | 57 | | tagDensity | 0.351 | | leniency | 0.702 | | rawRatio | 0.05 | | effectiveRatio | 0.035 | |
| 87.48% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1198 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | 0 | "very" | | 1 | "slightly" | | 2 | "gently" |
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| 100.00% | AI-ism character names | Target: 0 AI-default names (16 tracked, −20% each) | | codexExemptions | | | found | (empty) | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 91.65% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1198 | | totalAiIsms | 2 | | found | | | highlights | | |
| 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 | 62 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 62 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 97 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 53 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1197 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 20 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 7 | | wordCount | 631 | | uniqueNames | 3 | | maxNameDensity | 0.79 | | worstName | "Aurora" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Aurora" | | discoveredNames | | | persons | | | places | (empty) | | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 35 | | 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 | 1197 | | matches | (empty) | |
| 97.94% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 2 | | totalSentences | 97 | | matches | | 0 | "hated that he'd" | | 1 | "clicked, that they" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 50 | | mean | 23.94 | | std | 17.68 | | cv | 0.739 | | sampleLengths | | 0 | 43 | | 1 | 3 | | 2 | 36 | | 3 | 6 | | 4 | 17 | | 5 | 31 | | 6 | 2 | | 7 | 7 | | 8 | 22 | | 9 | 49 | | 10 | 2 | | 11 | 18 | | 12 | 46 | | 13 | 34 | | 14 | 22 | | 15 | 18 | | 16 | 45 | | 17 | 17 | | 18 | 7 | | 19 | 3 | | 20 | 45 | | 21 | 37 | | 22 | 20 | | 23 | 43 | | 24 | 4 | | 25 | 3 | | 26 | 22 | | 27 | 21 | | 28 | 4 | | 29 | 27 | | 30 | 37 | | 31 | 6 | | 32 | 9 | | 33 | 58 | | 34 | 2 | | 35 | 10 | | 36 | 54 | | 37 | 38 | | 38 | 23 | | 39 | 83 | | 40 | 30 | | 41 | 35 | | 42 | 20 | | 43 | 7 | | 44 | 22 | | 45 | 2 | | 46 | 17 | | 47 | 28 | | 48 | 33 | | 49 | 29 |
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| 93.94% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 62 | | matches | | 0 | "was gone" | | 1 | "being asked" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 122 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 1 | | semicolonCount | 0 | | flaggedSentences | 1 | | totalSentences | 97 | | ratio | 0.01 | | matches | | 0 | "This one filled the room a different way—by occupying as little of it as possible and somehow being unmissable for it." |
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| 97.85% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 636 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 27 | | adverbRatio | 0.04245283018867924 | | lyAdverbCount | 8 | | lyAdverbRatio | 0.012578616352201259 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 97 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 97 | | mean | 12.34 | | std | 10.09 | | cv | 0.818 | | sampleLengths | | 0 | 19 | | 1 | 24 | | 2 | 3 | | 3 | 8 | | 4 | 5 | | 5 | 23 | | 6 | 6 | | 7 | 12 | | 8 | 5 | | 9 | 2 | | 10 | 5 | | 11 | 24 | | 12 | 2 | | 13 | 7 | | 14 | 5 | | 15 | 17 | | 16 | 3 | | 17 | 1 | | 18 | 23 | | 19 | 14 | | 20 | 8 | | 21 | 2 | | 22 | 18 | | 23 | 5 | | 24 | 12 | | 25 | 29 | | 26 | 23 | | 27 | 11 | | 28 | 11 | | 29 | 11 | | 30 | 11 | | 31 | 7 | | 32 | 5 | | 33 | 22 | | 34 | 18 | | 35 | 9 | | 36 | 8 | | 37 | 7 | | 38 | 3 | | 39 | 15 | | 40 | 30 | | 41 | 22 | | 42 | 15 | | 43 | 7 | | 44 | 13 | | 45 | 3 | | 46 | 19 | | 47 | 21 | | 48 | 4 | | 49 | 3 |
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| 72.85% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 6 | | diversityRatio | 0.4742268041237113 | | totalSentences | 97 | | uniqueOpeners | 46 | |
| 62.89% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 53 | | matches | | 0 | "Maybe because she knew the" |
| | ratio | 0.019 | |
| 1.13% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 29 | | totalSentences | 53 | | matches | | 0 | "He didn't pour straight away." | | 1 | "He looked at her with" | | 2 | "She peeled off her gloves" | | 3 | "She set the glass down." | | 4 | "Her hand wasn't quite steady," | | 5 | "She watched the words land" | | 6 | "He poured himself a measure" | | 7 | "She turned the glass in" | | 8 | "He finally drank" | | 9 | "She studied him." | | 10 | "She shook her head" | | 11 | "She searched for it" | | 12 | "He wiped a ring of" | | 13 | "She let it go, because" | | 14 | "She'd done the same thing" | | 15 | "she said instead" | | 16 | "He went very still." | | 17 | "She heard her own voice" | | 18 | "He set his glass down" | | 19 | "She didn't say it." |
| | ratio | 0.547 | |
| 16.60% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 47 | | totalSentences | 53 | | matches | | 0 | "The green neon buzzed over" | | 1 | "Aurora shouldered through it, rain" | | 2 | "Silas set down the glass" | | 3 | "He didn't pour straight away." | | 4 | "He looked at her with" | | 5 | "She peeled off her gloves" | | 6 | "The glass stopped halfway to" | | 7 | "The grey threaded through the" | | 8 | "Hazel and patient and impossible" | | 9 | "She set the glass down." | | 10 | "Her hand wasn't quite steady," | | 11 | "Silas straightened, and the limp" | | 12 | "She watched the words land" | | 13 | "A breath that might have" | | 14 | "The bar was near empty." | | 15 | "A man in the corner" | | 16 | "The photographs watched them, all" | | 17 | "He poured himself a measure" | | 18 | "She turned the glass in" | | 19 | "He finally drank" |
| | ratio | 0.887 | |
| 94.34% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 53 | | matches | | | ratio | 0.019 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 19 | | technicalSentenceCount | 1 | | matches | | 0 | "He looked at her with the kind of stillness she'd forgotten existed in people, the stillness of someone who measured before he moved." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 20 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 9 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 57 | | tagDensity | 0.158 | | leniency | 0.316 | | rawRatio | 0 | | effectiveRatio | 0 | |