| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 11 | | adverbTagCount | 1 | | adverbTags | | 0 | "His thumb brushed once [once]" |
| | dialogueSentences | 114 | | tagDensity | 0.096 | | leniency | 0.193 | | rawRatio | 0.091 | | effectiveRatio | 0.018 | |
| 97.91% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 2398 | | 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) | |
| 74.98% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 2398 | | totalAiIsms | 12 | | found | | | highlights | | 0 | "churned" | | 1 | "sense of" | | 2 | "comfortable" | | 3 | "traced" | | 4 | "flicker" | | 5 | "pulse" | | 6 | "footsteps" | | 7 | "silence" | | 8 | "intensity" | | 9 | "whisper" |
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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 | 198 | | matches | (empty) | |
| 99.57% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 5 | | narrationSentences | 198 | | filterMatches | | | hedgeMatches | | 0 | "started to" | | 1 | "seemed to" | | 2 | "began to" |
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| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 301 | | 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 | 2394 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 18 | | unquotedAttributions | 0 | | matches | (empty) | |
| 73.50% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 71 | | wordCount | 1830 | | uniqueNames | 12 | | maxNameDensity | 1.53 | | worstName | "Lucien" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Aurora" | | discoveredNames | | Aurora | 21 | | Lucien | 28 | | Moreau | 1 | | Ptolemy | 5 | | Brick | 1 | | Lane | 1 | | Friday-night | 1 | | Eva | 8 | | London | 1 | | Silas | 1 | | Bengali | 1 | | One | 2 |
| | persons | | 0 | "Aurora" | | 1 | "Lucien" | | 2 | "Moreau" | | 3 | "Ptolemy" | | 4 | "Eva" | | 5 | "Silas" | | 6 | "One" |
| | places | | 0 | "Brick" | | 1 | "Lane" | | 2 | "London" | | 3 | "Bengali" |
| | globalScore | 0.735 | | windowScore | 0.833 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 130 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.418 | | wordCount | 2394 | | matches | | 0 | "not fragile but dangerous" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 301 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 191 | | mean | 12.53 | | std | 14.82 | | cv | 1.183 | | sampleLengths | | 0 | 17 | | 1 | 8 | | 2 | 51 | | 3 | 13 | | 4 | 42 | | 5 | 9 | | 6 | 3 | | 7 | 13 | | 8 | 33 | | 9 | 11 | | 10 | 1 | | 11 | 8 | | 12 | 6 | | 13 | 2 | | 14 | 89 | | 15 | 17 | | 16 | 6 | | 17 | 2 | | 18 | 3 | | 19 | 4 | | 20 | 44 | | 21 | 3 | | 22 | 80 | | 23 | 4 | | 24 | 20 | | 25 | 2 | | 26 | 6 | | 27 | 9 | | 28 | 3 | | 29 | 34 | | 30 | 7 | | 31 | 7 | | 32 | 1 | | 33 | 7 | | 34 | 6 | | 35 | 6 | | 36 | 8 | | 37 | 44 | | 38 | 4 | | 39 | 55 | | 40 | 3 | | 41 | 4 | | 42 | 4 | | 43 | 3 | | 44 | 9 | | 45 | 4 | | 46 | 8 | | 47 | 64 | | 48 | 7 | | 49 | 2 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 198 | | matches | | 0 | "been carved" | | 1 | "was stretched" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 310 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 4 | | semicolonCount | 1 | | flaggedSentences | 4 | | totalSentences | 301 | | ratio | 0.013 | | matches | | 0 | "No—that was a lie." | | 1 | "His amber eye caught the light; the black one seemed to swallow it." | | 2 | "Aurora reached for the nearest object—an iron candlestick—and swung it toward the thing crawling through the broken window." | | 3 | "There was no building outside the window, no fire escape—only a black gulf threaded with distant red lights." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1838 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 59 | | adverbRatio | 0.032100108813928184 | | lyAdverbCount | 6 | | lyAdverbRatio | 0.003264417845484222 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 301 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 301 | | mean | 7.95 | | std | 6.45 | | cv | 0.81 | | sampleLengths | | 0 | 17 | | 1 | 8 | | 2 | 8 | | 3 | 18 | | 4 | 25 | | 5 | 13 | | 6 | 4 | | 7 | 20 | | 8 | 4 | | 9 | 7 | | 10 | 7 | | 11 | 7 | | 12 | 2 | | 13 | 3 | | 14 | 13 | | 15 | 7 | | 16 | 26 | | 17 | 7 | | 18 | 4 | | 19 | 1 | | 20 | 5 | | 21 | 3 | | 22 | 6 | | 23 | 2 | | 24 | 12 | | 25 | 26 | | 26 | 9 | | 27 | 23 | | 28 | 17 | | 29 | 1 | | 30 | 1 | | 31 | 17 | | 32 | 6 | | 33 | 2 | | 34 | 3 | | 35 | 4 | | 36 | 6 | | 37 | 14 | | 38 | 24 | | 39 | 3 | | 40 | 4 | | 41 | 25 | | 42 | 22 | | 43 | 16 | | 44 | 13 | | 45 | 4 | | 46 | 2 | | 47 | 2 | | 48 | 16 | | 49 | 2 |
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| 43.36% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 20 | | diversityRatio | 0.2425249169435216 | | totalSentences | 301 | | uniqueOpeners | 73 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 7 | | totalSentences | 174 | | matches | | 0 | "Of course he did." | | 1 | "Then he had disappeared." | | 2 | "Then the sound of footsteps" | | 3 | "Instead she stepped back." | | 4 | "Then the morning after." | | 5 | "Instead it made her more" | | 6 | "Then Aurora rose on her" |
| | ratio | 0.04 | |
| 93.56% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 55 | | totalSentences | 174 | | matches | | 0 | "His platinum hair remained slicked" | | 1 | "He held his ivory-handled cane" | | 2 | "He looked exactly as he" | | 3 | "His amber eye fixed on" | | 4 | "His black eye reflected nothing" | | 5 | "His gaze returned to hers." | | 6 | "She had been barefoot, wearing" | | 7 | "Her fingers tightened around the" | | 8 | "He remembered everything." | | 9 | "He had taken her wrist" | | 10 | "She had been twenty-four, newly" | | 11 | "He had looked at her" | | 12 | "She stared at him." | | 13 | "His mouth tightened." | | 14 | "She glanced over her shoulder." | | 15 | "She looked back at him." | | 16 | "It had been there when" | | 17 | "His face altered, barely." | | 18 | "His eyes held hers." | | 19 | "She went still." |
| | ratio | 0.316 | |
| 43.33% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 145 | | totalSentences | 174 | | matches | | 0 | "The third deadbolt slid free" | | 1 | "Rain silvered the shoulders of" | | 2 | "His platinum hair remained slicked" | | 3 | "He held his ivory-handled cane" | | 4 | "He looked exactly as he" | | 5 | "The Lucien she remembered had" | | 6 | "This Lucien looked tired." | | 7 | "His amber eye fixed on" | | 8 | "His black eye reflected nothing" | | 9 | "Aurora gripped the edge of" | | 10 | "The old nickname landed with" | | 11 | "The tabby had been asleep" | | 12 | "Lucien glanced past her into" | | 13 | "His gaze returned to hers." | | 14 | "Rain ticked against the grimy" | | 15 | "The smell clung to everything" | | 16 | "Aurora had spent the last" | | 17 | "She had been barefoot, wearing" | | 18 | "Lucien had always been best" | | 19 | "Her fingers tightened around the" |
| | ratio | 0.833 | |
| 57.47% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 174 | | matches | | 0 | "Even from the fourth floor," | | 1 | "If anything, absence had honed" |
| | ratio | 0.011 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 70 | | technicalSentenceCount | 3 | | matches | | 0 | "He held his ivory-handled cane in one gloved hand, the tip resting on the landing as if he had all the time in the world." | | 1 | "He had taken her wrist in his hand and traced the crescent with his thumb as though it were a secret map." | | 2 | "It had been there when she arrived, half-hidden beneath a paper marked with a series of symbols that resembled roots or veins." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 11 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 7 | | fancyCount | 1 | | fancyTags | | 0 | "she whispered (whisper)" |
| | dialogueSentences | 114 | | tagDensity | 0.061 | | leniency | 0.123 | | rawRatio | 0.143 | | effectiveRatio | 0.018 | |