| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 3 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 107 | | tagDensity | 0.028 | | leniency | 0.056 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 95.44% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 2194 | | totalAiIsmAdverbs | 2 | | 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) | |
| 63.54% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 2194 | | totalAiIsms | 16 | | found | | | highlights | | 0 | "flicked" | | 1 | "perfect" | | 2 | "familiar" | | 3 | "unreadable" | | 4 | "efficient" | | 5 | "flicker" | | 6 | "silence" | | 7 | "sense of" | | 8 | "pulse" | | 9 | "affection" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 150 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 2 | | narrationSentences | 150 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 254 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 36 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 2194 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 19 | | unquotedAttributions | 0 | | matches | (empty) | |
| 69.35% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 58 | | wordCount | 1550 | | uniqueNames | 6 | | maxNameDensity | 1.61 | | worstName | "Rory" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Rory" | | discoveredNames | | Moreau | 1 | | Eva | 4 | | Rory | 25 | | Lucien | 20 | | Ptolemy | 7 | | Aurora | 1 |
| | persons | | 0 | "Moreau" | | 1 | "Eva" | | 2 | "Rory" | | 3 | "Lucien" | | 4 | "Ptolemy" |
| | places | (empty) | | globalScore | 0.694 | | windowScore | 0.833 | |
| 27.45% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 102 | | glossingSentenceCount | 5 | | matches | | 0 | "not quite a smile" | | 1 | "smelled like damp plaster and his expressi" | | 2 | "looked like a storm had sat down to think" | | 3 | "looked like he had stepped out of another" | | 4 | "felt like another person in the room" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 2 | | per1kWords | 0.912 | | wordCount | 2194 | | matches | | 0 | "not to touch her face, not yet, but toward the wrist" | | 1 | "not yet, but toward the wrist" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 3 | | totalSentences | 254 | | matches | | 0 | "hated that his" | | 1 | "hated that strangers" | | 2 | "hated that her" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 171 | | mean | 12.83 | | std | 15.15 | | cv | 1.181 | | sampleLengths | | 0 | 10 | | 1 | 74 | | 2 | 14 | | 3 | 14 | | 4 | 7 | | 5 | 17 | | 6 | 4 | | 7 | 36 | | 8 | 19 | | 9 | 5 | | 10 | 6 | | 11 | 46 | | 12 | 6 | | 13 | 10 | | 14 | 9 | | 15 | 23 | | 16 | 5 | | 17 | 3 | | 18 | 26 | | 19 | 10 | | 20 | 22 | | 21 | 8 | | 22 | 4 | | 23 | 4 | | 24 | 6 | | 25 | 7 | | 26 | 15 | | 27 | 34 | | 28 | 9 | | 29 | 4 | | 30 | 5 | | 31 | 6 | | 32 | 19 | | 33 | 2 | | 34 | 8 | | 35 | 13 | | 36 | 4 | | 37 | 2 | | 38 | 2 | | 39 | 47 | | 40 | 10 | | 41 | 74 | | 42 | 34 | | 43 | 34 | | 44 | 4 | | 45 | 2 | | 46 | 2 | | 47 | 5 | | 48 | 14 | | 49 | 6 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 150 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 254 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 254 | | ratio | 0 | | matches | (empty) | |
| 91.17% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1557 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 78 | | adverbRatio | 0.05009633911368015 | | lyAdverbCount | 13 | | lyAdverbRatio | 0.008349389852280027 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 254 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 254 | | mean | 8.64 | | std | 6.98 | | cv | 0.808 | | sampleLengths | | 0 | 10 | | 1 | 31 | | 2 | 5 | | 3 | 12 | | 4 | 7 | | 5 | 7 | | 6 | 12 | | 7 | 14 | | 8 | 14 | | 9 | 7 | | 10 | 17 | | 11 | 4 | | 12 | 21 | | 13 | 9 | | 14 | 6 | | 15 | 19 | | 16 | 5 | | 17 | 6 | | 18 | 23 | | 19 | 15 | | 20 | 3 | | 21 | 5 | | 22 | 6 | | 23 | 10 | | 24 | 9 | | 25 | 19 | | 26 | 4 | | 27 | 5 | | 28 | 3 | | 29 | 26 | | 30 | 10 | | 31 | 22 | | 32 | 8 | | 33 | 4 | | 34 | 4 | | 35 | 6 | | 36 | 7 | | 37 | 15 | | 38 | 10 | | 39 | 7 | | 40 | 17 | | 41 | 9 | | 42 | 4 | | 43 | 5 | | 44 | 6 | | 45 | 4 | | 46 | 7 | | 47 | 8 | | 48 | 2 | | 49 | 8 |
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| 46.06% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 10 | | diversityRatio | 0.22440944881889763 | | totalSentences | 254 | | uniqueOpeners | 57 | |
| 95.92% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 4 | | totalSentences | 139 | | matches | | 0 | "Then she let the chain" | | 1 | "Just tense enough that every" | | 2 | "Bright blue eyes, sharp enough" | | 3 | "Of course he did." |
| | ratio | 0.029 | |
| 81.87% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 48 | | totalSentences | 139 | | matches | | 0 | "His ivory-handled cane rested against" | | 1 | "His gaze dropped to her" | | 2 | "It lasted only a moment," | | 3 | "He always noticed the details" | | 4 | "He looked past her shoulder" | | 5 | "His ears flattened." | | 6 | "She tugged the door a" | | 7 | "He leaned on the cane" | | 8 | "He held her gaze." | | 9 | "She barked a laugh that" | | 10 | "She stepped back and folded" | | 11 | "He shut the door behind" | | 12 | "He watched Lucien with the" | | 13 | "He took off one glove," | | 14 | "His eyes lifted, sharp and" | | 15 | "She stepped into the kitchen" | | 16 | "She hated that his presence" | | 17 | "His gaze slipped back to" | | 18 | "She faced him fully then." | | 19 | "His clothes still looked too" |
| | ratio | 0.345 | |
| 21.15% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 122 | | totalSentences | 139 | | matches | | 0 | "Rory cracked the third deadbolt" | | 1 | "Lucien Moreau filled the narrow" | | 2 | "Both fixed on her face" | | 3 | "His ivory-handled cane rested against" | | 4 | "Water darkened the shoulder of" | | 5 | "The smell of wet pavement" | | 6 | "Rory kept one hand on" | | 7 | "Lucien’s mouth tilted, not quite" | | 8 | "His gaze dropped to her" | | 9 | "It lasted only a moment," | | 10 | "He always noticed the details" | | 11 | "He looked past her shoulder" | | 12 | "Ptolemy, the tabby cat, wound" | | 13 | "His ears flattened." | | 14 | "The tail flicked once, hard." | | 15 | "Lucien glanced down at the" | | 16 | "Ptolemy gave Lucien a long," | | 17 | "Lucien lifted one brow." | | 18 | "She tugged the door a" | | 19 | "He leaned on the cane" |
| | ratio | 0.878 | |
| 35.97% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 139 | | matches | | 0 | "Even soaked and tired and" |
| | ratio | 0.007 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 63 | | technicalSentenceCount | 3 | | matches | | 0 | "The flat felt too small suddenly, too warm, as if his voice had pulled the air closer." | | 1 | "Lucien’s gaze shifted over her face as if he were reading a version of the night she still kept under lock." | | 2 | "Lucien’s mouth twitched, this time with something that looked dangerously close to affection." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 3 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 3 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 107 | | tagDensity | 0.028 | | leniency | 0.056 | | rawRatio | 0.333 | | effectiveRatio | 0.019 | |