| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 11 | | adverbTagCount | 1 | | adverbTags | | 0 | "he said softly [softly]" |
| | dialogueSentences | 19 | | tagDensity | 0.579 | | leniency | 1 | | rawRatio | 0.091 | | effectiveRatio | 0.091 | |
| 66.02% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 883 | | totalAiIsmAdverbs | 6 | | found | | | highlights | | 0 | "softly" | | 1 | "really" | | 2 | "truly" |
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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) | |
| 49.04% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 883 | | totalAiIsms | 9 | | found | | 0 | | | 1 | | word | "moth to a flame" | | count | 1 |
| | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | |
| | highlights | | 0 | "silk" | | 1 | "moth to a flame" | | 2 | "unraveling" | | 3 | "dancing" | | 4 | "could feel" | | 5 | "fluttered" | | 6 | "etched" | | 7 | "resolve" | | 8 | "echoes" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "couldn't help but" | | count | 1 |
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| | highlights | | 0 | "couldn't help but wonder" |
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| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 46 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 46 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 54 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 48 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 887 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 10 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 9 | | wordCount | 738 | | uniqueNames | 5 | | maxNameDensity | 0.41 | | worstName | "Rory" | | maxWindowNameDensity | 1 | | worstWindowName | "Eva" | | discoveredNames | | Eva | 2 | | Ptolemy | 2 | | French | 1 | | Rory | 3 | | London | 1 |
| | persons | | | places | | | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 42 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 87.26% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 1.127 | | wordCount | 887 | | matches | | 0 | "not touching her, but close enough" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 54 | | matches | (empty) | |
| 77.59% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 23 | | mean | 38.57 | | std | 16.26 | | cv | 0.422 | | sampleLengths | | 0 | 48 | | 1 | 39 | | 2 | 15 | | 3 | 58 | | 4 | 22 | | 5 | 78 | | 6 | 47 | | 7 | 28 | | 8 | 20 | | 9 | 38 | | 10 | 27 | | 11 | 49 | | 12 | 49 | | 13 | 24 | | 14 | 30 | | 15 | 51 | | 16 | 35 | | 17 | 54 | | 18 | 43 | | 19 | 25 | | 20 | 54 | | 21 | 5 | | 22 | 48 |
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| 90.01% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 46 | | matches | | 0 | "was holed" | | 1 | "been drawn" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 149 | | matches | | 0 | "wasn't expecting" | | 1 | "was coming" |
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| 37.04% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 2 | | semicolonCount | 0 | | flaggedSentences | 2 | | totalSentences | 54 | | ratio | 0.037 | | matches | | 0 | "She wasn't expecting anyone — Eva was out gathering supplies, and nobody else knew she was holed up here." | | 1 | "Lucien had offered her a way out — excitement, danger, purpose." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 737 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 20 | | adverbRatio | 0.027137042062415198 | | lyAdverbCount | 7 | | lyAdverbRatio | 0.009497964721845319 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 54 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 54 | | mean | 16.43 | | std | 9.15 | | cv | 0.557 | | sampleLengths | | 0 | 11 | | 1 | 18 | | 2 | 19 | | 3 | 8 | | 4 | 10 | | 5 | 21 | | 6 | 15 | | 7 | 16 | | 8 | 20 | | 9 | 22 | | 10 | 17 | | 11 | 5 | | 12 | 26 | | 13 | 30 | | 14 | 11 | | 15 | 11 | | 16 | 18 | | 17 | 14 | | 18 | 15 | | 19 | 11 | | 20 | 12 | | 21 | 5 | | 22 | 20 | | 23 | 14 | | 24 | 24 | | 25 | 12 | | 26 | 9 | | 27 | 6 | | 28 | 39 | | 29 | 10 | | 30 | 34 | | 31 | 15 | | 32 | 11 | | 33 | 13 | | 34 | 13 | | 35 | 17 | | 36 | 17 | | 37 | 34 | | 38 | 16 | | 39 | 12 | | 40 | 3 | | 41 | 4 | | 42 | 13 | | 43 | 13 | | 44 | 28 | | 45 | 11 | | 46 | 20 | | 47 | 12 | | 48 | 20 | | 49 | 5 |
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| 76.54% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 2 | | diversityRatio | 0.48148148148148145 | | totalSentences | 54 | | uniqueOpeners | 26 | |
| 74.07% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 45 | | matches | | 0 | "Instead, he straightened, his face" |
| | ratio | 0.022 | |
| 0.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 26 | | totalSentences | 45 | | matches | | 0 | "She wasn't expecting anyone —" | | 1 | "she called, crossing the cramped" | | 2 | "he purred, his French accent" | | 3 | "She'd been drawn to him" | | 4 | "He'd shown her wonders and" | | 5 | "She'd fallen hard for his" | | 6 | "She'd fled, tail between her" | | 7 | "He'd stayed away, as promised." | | 8 | "She surprised herself with how" | | 9 | "Her nails bit crescents into" | | 10 | "He tilted his head, considering" | | 11 | "he said softly" | | 12 | "she snapped, trying to forget" | | 13 | "His voice was low, dangerous," | | 14 | "Her eyes fluttered shut as" | | 15 | "His voice cracked, the façade" | | 16 | "She peeked at him through" | | 17 | "She cut him off fiercely," | | 18 | "His eyes flashed, liquid fire," | | 19 | "He turned to go, his" |
| | ratio | 0.578 | |
| 26.67% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 39 | | totalSentences | 45 | | matches | | 0 | "The door rattled as someone" | | 1 | "Aurora pulled herself away from" | | 2 | "She wasn't expecting anyone —" | | 3 | "she called, crossing the cramped" | | 4 | "Ptolemy, Eva's sleepy tabby, yawned" | | 5 | "Rory undid the three deadbolts" | | 6 | "The words died on her" | | 7 | "Lucien leaned against the door" | | 8 | "The platinum hair slicked back" | | 9 | "A faint smirk played at" | | 10 | "he purred, his French accent" | | 11 | "Rory's heart clenched at the" | | 12 | "Weeks ago, she'd been desperate" | | 13 | "Lucien had offered her a" | | 14 | "She'd been drawn to him" | | 15 | "He'd shown her wonders and" | | 16 | "She'd fallen hard for his" | | 17 | "She'd fled, tail between her" | | 18 | "He'd stayed away, as promised." | | 19 | "She surprised herself with how" |
| | ratio | 0.867 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 45 | | matches | | 0 | "Now, here he was again," |
| | ratio | 0.022 | |
| 77.92% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 33 | | technicalSentenceCount | 3 | | matches | | 0 | "Rory stared at the space he'd occupied, her breath hitching, her body trembling with the effort of keeping herself upright." | | 1 | "She repeated it like a mantra, her fingers finding the crescent-shaped scar on her wrist, rubbing it like a talisman." | | 2 | "But as she collapsed against the wall, crumpling to the floor while Ptolemy wound around her legs, purring softly, she couldn't help but wonder if it was worth …" |
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| 34.09% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 11 | | uselessAdditionCount | 2 | | matches | | 0 | "His voice cracked, the façade breaking for just a moment" | | 1 | "he murmured, his eyes cutting right through her," |
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| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 6 | | fancyCount | 4 | | fancyTags | | 0 | "she snapped (snap)" | | 1 | "he snarled (snarl)" | | 2 | "he murmured (murmur)" | | 3 | "she whispered (whisper)" |
| | dialogueSentences | 19 | | tagDensity | 0.316 | | leniency | 0.632 | | rawRatio | 0.667 | | effectiveRatio | 0.421 | |