| 40.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 12 | | adverbTagCount | 2 | | adverbTags | | 0 | "she said stupidly [stupidly]" | | 1 | "he said finally [finally]" |
| | dialogueSentences | 25 | | tagDensity | 0.48 | | leniency | 0.96 | | rawRatio | 0.167 | | effectiveRatio | 0.16 | |
| 61.64% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 782 | | totalAiIsmAdverbs | 6 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | adverb | "deliberately" | | count | 1 |
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| | highlights | | 0 | "softly" | | 1 | "warily" | | 2 | "sharply" | | 3 | "suddenly" | | 4 | "slowly" | | 5 | "deliberately" |
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| 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) | |
| 68.03% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 782 | | totalAiIsms | 5 | | found | | | highlights | | 0 | "eyebrow" | | 1 | "scanning" | | 2 | "fascinating" | | 3 | "glint" | | 4 | "tension" |
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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 | 47 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 47 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 60 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 34 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 778 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 13 | | unquotedAttributions | 0 | | matches | (empty) | |
| 83.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 20 | | wordCount | 624 | | uniqueNames | 6 | | maxNameDensity | 1.28 | | worstName | "Lucien" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Lucien" | | discoveredNames | | Lucien | 8 | | London | 1 | | Brick | 1 | | Lane | 1 | | Rain | 1 | | Rory | 8 |
| | persons | | | places | | 0 | "London" | | 1 | "Brick" | | 2 | "Lane" | | 3 | "Rain" |
| | globalScore | 0.859 | | windowScore | 0.833 | |
| 33.72% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 43 | | glossingSentenceCount | 2 | | matches | | 0 | "not quite meeting her eyes" | | 1 | "something like excitement in his eye" |
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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 | 778 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 60 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 25 | | mean | 31.12 | | std | 17.14 | | cv | 0.551 | | sampleLengths | | 0 | 60 | | 1 | 37 | | 2 | 22 | | 3 | 44 | | 4 | 14 | | 5 | 48 | | 6 | 50 | | 7 | 37 | | 8 | 23 | | 9 | 18 | | 10 | 39 | | 11 | 68 | | 12 | 25 | | 13 | 13 | | 14 | 19 | | 15 | 65 | | 16 | 14 | | 17 | 11 | | 18 | 16 | | 19 | 24 | | 20 | 36 | | 21 | 15 | | 22 | 27 | | 23 | 44 | | 24 | 9 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 47 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 118 | | matches | | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 4 | | semicolonCount | 0 | | flaggedSentences | 3 | | totalSentences | 60 | | ratio | 0.05 | | matches | | 0 | "She'd thought—hoped, maybe—that he wouldn't come back." | | 1 | "It was a bad idea, getting mixed up in whatever trouble Lucien had stumbled into—she knew that." | | 2 | "Rory knew she should step back, cut the tension with a sharp word or a wry laugh like she usually did—but she didn't move." |
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| 90.16% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 630 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 30 | | adverbRatio | 0.047619047619047616 | | lyAdverbCount | 15 | | lyAdverbRatio | 0.023809523809523808 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 60 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 60 | | mean | 12.97 | | std | 6.52 | | cv | 0.503 | | sampleLengths | | 0 | 27 | | 1 | 33 | | 2 | 10 | | 3 | 20 | | 4 | 7 | | 5 | 11 | | 6 | 7 | | 7 | 4 | | 8 | 19 | | 9 | 15 | | 10 | 10 | | 11 | 14 | | 12 | 20 | | 13 | 14 | | 14 | 14 | | 15 | 23 | | 16 | 18 | | 17 | 9 | | 18 | 12 | | 19 | 10 | | 20 | 15 | | 21 | 9 | | 22 | 14 | | 23 | 12 | | 24 | 6 | | 25 | 12 | | 26 | 14 | | 27 | 13 | | 28 | 10 | | 29 | 14 | | 30 | 14 | | 31 | 14 | | 32 | 16 | | 33 | 4 | | 34 | 21 | | 35 | 11 | | 36 | 2 | | 37 | 5 | | 38 | 14 | | 39 | 8 | | 40 | 17 | | 41 | 30 | | 42 | 10 | | 43 | 4 | | 44 | 10 | | 45 | 7 | | 46 | 4 | | 47 | 6 | | 48 | 10 | | 49 | 19 |
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| 67.22% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 3 | | diversityRatio | 0.43333333333333335 | | totalSentences | 60 | | uniqueOpeners | 26 | |
| 70.92% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 47 | | matches | | 0 | "Slowly, deliberately, Lucien dipped his" |
| | ratio | 0.021 | |
| 0.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 29 | | totalSentences | 47 | | matches | | 0 | "Her heart stuttered at the" | | 1 | "she said stupidly, as if" | | 2 | "It had been months since" | | 3 | "She'd thought—hoped, maybe—that he wouldn't" | | 4 | "He offered her a crooked" | | 5 | "he greeted, voice low and" | | 6 | "She hesitated, the shape of" | | 7 | "she managed, stepping back to" | | 8 | "He brushed by her, close" | | 9 | "she asked, proud of how" | | 10 | "He wandered further into her" | | 11 | "he said finally, stopping in" | | 12 | "she repeated, crossing her arms" | | 13 | "She made a skeptical noise," | | 14 | "He reached into his jacket" | | 15 | "It looked ancient, the leather" | | 16 | "It was heavy in her" | | 17 | "She flipped it open to" | | 18 | "she said, recognizing the language" | | 19 | "His jaw tightened, just barely." |
| | ratio | 0.617 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 44 | | totalSentences | 47 | | matches | | 0 | "Rory nearly dropped the stack" | | 1 | "Her heart stuttered at the" | | 2 | "she said stupidly, as if" | | 3 | "It had been months since" | | 4 | "She'd thought—hoped, maybe—that he wouldn't" | | 5 | "He offered her a crooked" | | 6 | "he greeted, voice low and" | | 7 | "She hesitated, the shape of" | | 8 | "The last time he'd stood" | | 9 | "Rory still dreamed about it" | | 10 | "she managed, stepping back to" | | 11 | "He brushed by her, close" | | 12 | "Rory shut the door behind" | | 13 | "she asked, proud of how" | | 14 | "He wandered further into her" | | 15 | "he said finally, stopping in" | | 16 | "Rain spattered softly against the" | | 17 | "Rory raised an eyebrow, setting" | | 18 | "she repeated, crossing her arms" | | 19 | "Lucien turned to face her," |
| | ratio | 0.936 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 47 | | matches | (empty) | | ratio | 0 | |
| 89.95% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 27 | | technicalSentenceCount | 2 | | matches | | 0 | "Her heart stuttered at the unexpected sight of him, all angular cheekbones and slicked-back hair, crisp lines of his charcoal suit somehow untouched by the ligh…" | | 1 | "She hesitated, the shape of him filling her doorway, casting shadows along the edges of her cluttered front hall." |
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| 41.67% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 12 | | uselessAdditionCount | 2 | | matches | | 0 | "she said stupidly, as if her brain had short-circuited" | | 1 | "he greeted, voice low and honeyed" |
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| 70.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 10 | | fancyCount | 2 | | fancyTags | | 0 | "she repeated (repeat)" | | 1 | "she warned (warn)" |
| | dialogueSentences | 25 | | tagDensity | 0.4 | | leniency | 0.8 | | rawRatio | 0.2 | | effectiveRatio | 0.16 | |