| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 5 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 142 | | tagDensity | 0.035 | | leniency | 0.07 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 94.88% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1952 | | 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) | |
| 84.63% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1952 | | totalAiIsms | 6 | | found | | | highlights | | 0 | "warmth" | | 1 | "flickered" | | 2 | "unreadable" | | 3 | "complex" | | 4 | "pulse" | | 5 | "velvet" |
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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 | 143 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 143 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 280 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 39 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1950 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 27 | | unquotedAttributions | 1 | | matches | | 0 | "Before she touched the third, Lucien spoke through the door." |
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| 50.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 54 | | wordCount | 1200 | | uniqueNames | 10 | | maxNameDensity | 1.92 | | worstName | "Lucien" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Lucien" | | discoveredNames | | Lucien | 23 | | Moreau | 1 | | Eva | 1 | | London | 1 | | Aurora | 18 | | French | 1 | | Brick | 1 | | Lane | 1 | | Soho | 1 | | Ptolemy | 6 |
| | persons | | 0 | "Lucien" | | 1 | "Moreau" | | 2 | "Eva" | | 3 | "Aurora" | | 4 | "Ptolemy" |
| | places | | 0 | "London" | | 1 | "Brick" | | 2 | "Lane" | | 3 | "Soho" |
| | globalScore | 0.542 | | windowScore | 0.5 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 87 | | 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 | 1950 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 280 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 214 | | mean | 9.11 | | std | 10.73 | | cv | 1.177 | | sampleLengths | | 0 | 7 | | 1 | 42 | | 2 | 4 | | 3 | 10 | | 4 | 2 | | 5 | 4 | | 6 | 22 | | 7 | 7 | | 8 | 3 | | 9 | 7 | | 10 | 4 | | 11 | 14 | | 12 | 42 | | 13 | 44 | | 14 | 3 | | 15 | 1 | | 16 | 7 | | 17 | 15 | | 18 | 3 | | 19 | 58 | | 20 | 6 | | 21 | 5 | | 22 | 4 | | 23 | 4 | | 24 | 6 | | 25 | 5 | | 26 | 5 | | 27 | 2 | | 28 | 4 | | 29 | 10 | | 30 | 5 | | 31 | 6 | | 32 | 8 | | 33 | 3 | | 34 | 8 | | 35 | 8 | | 36 | 1 | | 37 | 1 | | 38 | 4 | | 39 | 2 | | 40 | 12 | | 41 | 20 | | 42 | 11 | | 43 | 8 | | 44 | 15 | | 45 | 49 | | 46 | 9 | | 47 | 8 | | 48 | 23 | | 49 | 9 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 143 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 206 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 2 | | semicolonCount | 0 | | flaggedSentences | 1 | | totalSentences | 280 | | ratio | 0.004 | | matches | | 0 | "She snatched the nearest object from the table—a brass paperweight shaped like an owl—and raised it." |
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| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1204 | | adjectiveStacks | 1 | | stackExamples | | 0 | "striking hard beneath her" |
| | adverbCount | 30 | | adverbRatio | 0.024916943521594685 | | lyAdverbCount | 2 | | lyAdverbRatio | 0.0016611295681063123 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 280 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 280 | | mean | 6.96 | | std | 5.28 | | cv | 0.758 | | sampleLengths | | 0 | 7 | | 1 | 31 | | 2 | 7 | | 3 | 4 | | 4 | 4 | | 5 | 10 | | 6 | 2 | | 7 | 4 | | 8 | 13 | | 9 | 9 | | 10 | 7 | | 11 | 3 | | 12 | 7 | | 13 | 4 | | 14 | 4 | | 15 | 10 | | 16 | 5 | | 17 | 16 | | 18 | 21 | | 19 | 7 | | 20 | 8 | | 21 | 5 | | 22 | 11 | | 23 | 13 | | 24 | 3 | | 25 | 1 | | 26 | 7 | | 27 | 7 | | 28 | 8 | | 29 | 3 | | 30 | 3 | | 31 | 13 | | 32 | 8 | | 33 | 34 | | 34 | 6 | | 35 | 5 | | 36 | 4 | | 37 | 4 | | 38 | 6 | | 39 | 5 | | 40 | 5 | | 41 | 2 | | 42 | 4 | | 43 | 10 | | 44 | 5 | | 45 | 6 | | 46 | 5 | | 47 | 3 | | 48 | 3 | | 49 | 8 |
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| 42.14% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 22 | | diversityRatio | 0.19642857142857142 | | totalSentences | 280 | | uniqueOpeners | 55 | |
| 48.66% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 137 | | matches | | 0 | "Somewhere below, a delivery scooter" | | 1 | "Instead, she caught his wrist" |
| | ratio | 0.015 | |
| 41.90% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 61 | | totalSentences | 137 | | matches | | 0 | "She shut the door." | | 1 | "His cane slid between the" | | 2 | "He withdrew the cane." | | 3 | "She heard its ferrule touch" | | 4 | "She had spent enough time" | | 5 | "Her grip slipped on the" | | 6 | "His expression sharpened." | | 7 | "He had always been good" | | 8 | "He hid it in the" | | 9 | "She knew every version of" | | 10 | "His fingers tightened around the" | | 11 | "She stood with her back" | | 12 | "She hated that he knew" | | 13 | "She hated more that he" | | 14 | "She threw back the first" | | 15 | "Her hand paused." | | 16 | "He had not changed much" | | 17 | "His face still held that" | | 18 | "His mouth still invited trouble." | | 19 | "He lowered his gaze to" |
| | ratio | 0.445 | |
| 0.15% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 126 | | totalSentences | 137 | | matches | | 0 | "The door opened on Lucien" | | 1 | "Aurora held the chain in" | | 2 | "The other remained black." | | 3 | "Ptolemy yowled behind her." | | 4 | "Lucien’s mouth tilted, though his" | | 5 | "She shut the door." | | 6 | "His cane slid between the" | | 7 | "The thin blade inside it" | | 8 | "Aurora’s fingers tightened around the" | | 9 | "He withdrew the cane." | | 10 | "She heard its ferrule touch" | | 11 | "Aurora kept the chain fastened." | | 12 | "She had spent enough time" | | 13 | "Lucien looked past her through" | | 14 | "Books leaned in unstable towers" | | 15 | "Scrolls covered the coffee table." | | 16 | "Ptolemy crouched behind Aurora’s ankles," | | 17 | "Her grip slipped on the" | | 18 | "His expression sharpened." | | 19 | "The old flinch, almost hidden" |
| | ratio | 0.92 | |
| 72.99% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 137 | | matches | | 0 | "Before she touched the third," | | 1 | "Even Ptolemy stopped moving." |
| | ratio | 0.015 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 40 | | technicalSentenceCount | 2 | | matches | | 0 | "She had spent enough time in London’s supernatural underworld to know a locked door only mattered to people who respected locks." | | 1 | "The flat smelled of curry from the restaurant below, old paper, and the rain that had followed her in from Brick Lane." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 5 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 5 | | fancyCount | 2 | | fancyTags | | 0 | "Aurora muttered (mutter)" | | 1 | "she whispered (whisper)" |
| | dialogueSentences | 142 | | tagDensity | 0.035 | | leniency | 0.07 | | rawRatio | 0.4 | | effectiveRatio | 0.028 | |