| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 6 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 38 | | tagDensity | 0.158 | | leniency | 0.316 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 93.94% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 825 | | 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) | |
| 39.39% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 825 | | totalAiIsms | 10 | | found | | | highlights | | 0 | "silence" | | 1 | "charged" | | 2 | "flicked" | | 3 | "pulse" | | 4 | "electric" | | 5 | "traced" | | 6 | "simmering" | | 7 | "blown wide" | | 8 | "searing" |
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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 | 1 | | narrationSentences | 62 | | matches | | |
| 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 | 92 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 37 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 819 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 10 | | unquotedAttributions | 0 | | matches | (empty) | |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 57 | | wordCount | 636 | | uniqueNames | 3 | | maxNameDensity | 4.72 | | worstName | "Eva" | | maxWindowNameDensity | 6.5 | | worstWindowName | "Rory" | | discoveredNames | | | persons | | | places | (empty) | | globalScore | 0 | | windowScore | 0 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 45 | | 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 | 819 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 92 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 42 | | mean | 19.5 | | std | 16.53 | | cv | 0.848 | | sampleLengths | | 0 | 48 | | 1 | 13 | | 2 | 20 | | 3 | 36 | | 4 | 4 | | 5 | 65 | | 6 | 19 | | 7 | 14 | | 8 | 8 | | 9 | 31 | | 10 | 7 | | 11 | 10 | | 12 | 35 | | 13 | 12 | | 14 | 17 | | 15 | 26 | | 16 | 14 | | 17 | 32 | | 18 | 11 | | 19 | 14 | | 20 | 2 | | 21 | 25 | | 22 | 6 | | 23 | 22 | | 24 | 36 | | 25 | 6 | | 26 | 24 | | 27 | 9 | | 28 | 13 | | 29 | 14 | | 30 | 6 | | 31 | 7 | | 32 | 86 | | 33 | 15 | | 34 | 12 | | 35 | 16 | | 36 | 12 | | 37 | 10 | | 38 | 8 | | 39 | 37 | | 40 | 9 | | 41 | 8 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 62 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 113 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 1 | | semicolonCount | 0 | | flaggedSentences | 1 | | totalSentences | 92 | | ratio | 0.011 | | matches | | 0 | "Eva stood there, her dark curls wild as if she’d been running her hands through them all night, her usual sharp gaze softened by something Rory couldn’t place—surprise, maybe, or the ghost of an old argument." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 640 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 18 | | adverbRatio | 0.028125 | | lyAdverbCount | 0 | | lyAdverbRatio | 0 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 92 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 92 | | mean | 8.9 | | std | 6.95 | | cv | 0.781 | | sampleLengths | | 0 | 12 | | 1 | 36 | | 2 | 11 | | 3 | 2 | | 4 | 8 | | 5 | 12 | | 6 | 3 | | 7 | 18 | | 8 | 15 | | 9 | 4 | | 10 | 15 | | 11 | 21 | | 12 | 16 | | 13 | 13 | | 14 | 12 | | 15 | 7 | | 16 | 10 | | 17 | 4 | | 18 | 5 | | 19 | 3 | | 20 | 14 | | 21 | 17 | | 22 | 6 | | 23 | 1 | | 24 | 7 | | 25 | 3 | | 26 | 8 | | 27 | 10 | | 28 | 10 | | 29 | 7 | | 30 | 7 | | 31 | 5 | | 32 | 6 | | 33 | 11 | | 34 | 11 | | 35 | 8 | | 36 | 7 | | 37 | 9 | | 38 | 5 | | 39 | 3 | | 40 | 18 | | 41 | 11 | | 42 | 5 | | 43 | 6 | | 44 | 3 | | 45 | 10 | | 46 | 1 | | 47 | 2 | | 48 | 8 | | 49 | 17 |
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| 47.83% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 6 | | diversityRatio | 0.32608695652173914 | | totalSentences | 92 | | uniqueOpeners | 30 | |
| 54.64% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 61 | | matches | | 0 | "All that mattered was the" |
| | ratio | 0.016 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 4 | | totalSentences | 61 | | matches | | 0 | "She turned away, plucking a" | | 1 | "It wasn’t gentle." | | 2 | "It wasn’t soft." | | 3 | "It was teeth and heat" |
| | ratio | 0.066 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 58 | | totalSentences | 61 | | matches | | 0 | "The door swung open before" | | 1 | "Eva stood there, her dark" | | 2 | "Eva’s voice was rough, like" | | 3 | "Rory held up the plastic" | | 4 | "Eva didn’t move." | | 5 | "The scent of turmeric and" | | 6 | "Ptolemy wound around Eva’s ankles," | | 7 | "Rory stepped forward, forcing Eva" | | 8 | "The doorframe brushed her shoulder" | | 9 | "Books teetered on every surface," | | 10 | "A half-empty mug of tea" | | 11 | "Eva shut the door, the" | | 12 | "The sound was too loud," | | 13 | "Rory set the bag on" | | 14 | "Eva’s laugh was sharp, humorless." | | 15 | "Rory pulled out the containers," | | 16 | "Eva’s fingers drummed against the" | | 17 | "Rory slid a fork across" | | 18 | "Eva cut herself off, jaw" | | 19 | "She turned away, plucking a" |
| | ratio | 0.951 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 61 | | matches | (empty) | | ratio | 0 | |
| 60.44% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 26 | | technicalSentenceCount | 3 | | matches | | 0 | "Eva stood there, her dark curls wild as if she’d been running her hands through them all night, her usual sharp gaze softened by something Rory couldn’t place—s…" | | 1 | "It was teeth and heat and the taste of old coffee and something darker, something that had been simmering between them for years." | | 2 | "Eva gasped against her mouth, her hands flying to Rory’s hips, pulling her closer." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 6 | | uselessAdditionCount | 3 | | matches | | 0 | "Rory pulled out, the steam rising in lazy tendrils" | | 1 | "Eva cut, jaw tightening" | | 2 | "Rory said, voice low" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 2 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 38 | | tagDensity | 0.053 | | leniency | 0.105 | | rawRatio | 0 | | effectiveRatio | 0 | |