| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1777 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 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) | |
| 85.93% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1777 | | totalAiIsms | 5 | | found | | | highlights | | 0 | "weight" | | 1 | "pulse" | | 2 | "electric" | | 3 | "silence" | | 4 | "traced" |
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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 | 137 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 137 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 207 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 46 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1779 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 14 | | unquotedAttributions | 0 | | matches | (empty) | |
| 66.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 49 | | wordCount | 1121 | | uniqueNames | 14 | | maxNameDensity | 1.61 | | worstName | "Lucien" | | maxWindowNameDensity | 3 | | worstWindowName | "Lucien" | | discoveredNames | | Lucien | 18 | | Moreau | 1 | | August | 1 | | Post-its | 2 | | Golden | 1 | | Empress | 1 | | Thames | 1 | | Carter | 1 | | Cardiff | 1 | | London | 1 | | Brick | 1 | | Lane | 1 | | Rory | 15 | | Ptolemy | 4 |
| | persons | | 0 | "Lucien" | | 1 | "Moreau" | | 2 | "Post-its" | | 3 | "Carter" | | 4 | "Rory" | | 5 | "Ptolemy" |
| | places | | 0 | "Golden" | | 1 | "Thames" | | 2 | "Cardiff" | | 3 | "London" | | 4 | "Brick" | | 5 | "Lane" |
| | globalScore | 0.697 | | windowScore | 0.667 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 89 | | 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 | 1779 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 207 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 121 | | mean | 14.7 | | std | 11.95 | | cv | 0.813 | | sampleLengths | | 0 | 4 | | 1 | 32 | | 2 | 11 | | 3 | 6 | | 4 | 48 | | 5 | 11 | | 6 | 11 | | 7 | 4 | | 8 | 2 | | 9 | 5 | | 10 | 12 | | 11 | 14 | | 12 | 21 | | 13 | 15 | | 14 | 62 | | 15 | 18 | | 16 | 37 | | 17 | 5 | | 18 | 9 | | 19 | 10 | | 20 | 12 | | 21 | 12 | | 22 | 35 | | 23 | 4 | | 24 | 3 | | 25 | 3 | | 26 | 18 | | 27 | 12 | | 28 | 8 | | 29 | 5 | | 30 | 5 | | 31 | 26 | | 32 | 10 | | 33 | 15 | | 34 | 16 | | 35 | 13 | | 36 | 14 | | 37 | 36 | | 38 | 5 | | 39 | 8 | | 40 | 4 | | 41 | 31 | | 42 | 14 | | 43 | 10 | | 44 | 17 | | 45 | 27 | | 46 | 9 | | 47 | 3 | | 48 | 18 | | 49 | 37 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 137 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 195 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 2 | | semicolonCount | 0 | | flaggedSentences | 2 | | totalSentences | 207 | | ratio | 0.01 | | matches | | 0 | "That night in the warehouse off the Thames came back whole — the smell of river mud, the sigil burned into the crate, Lucien's hand on her wrist pulling her back, her wrenching free." | | 1 | "The contrast jarred — the immaculate fixer, the blade hidden in his cane, the soft touch." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1124 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 20 | | adverbRatio | 0.017793594306049824 | | lyAdverbCount | 0 | | lyAdverbRatio | 0 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 207 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 207 | | mean | 8.59 | | std | 6.44 | | cv | 0.749 | | sampleLengths | | 0 | 4 | | 1 | 7 | | 2 | 10 | | 3 | 8 | | 4 | 7 | | 5 | 4 | | 6 | 7 | | 7 | 6 | | 8 | 5 | | 9 | 12 | | 10 | 11 | | 11 | 9 | | 12 | 11 | | 13 | 4 | | 14 | 7 | | 15 | 8 | | 16 | 3 | | 17 | 4 | | 18 | 2 | | 19 | 5 | | 20 | 3 | | 21 | 3 | | 22 | 6 | | 23 | 14 | | 24 | 6 | | 25 | 15 | | 26 | 3 | | 27 | 5 | | 28 | 7 | | 29 | 2 | | 30 | 10 | | 31 | 8 | | 32 | 5 | | 33 | 22 | | 34 | 7 | | 35 | 8 | | 36 | 9 | | 37 | 9 | | 38 | 4 | | 39 | 7 | | 40 | 13 | | 41 | 13 | | 42 | 5 | | 43 | 9 | | 44 | 10 | | 45 | 12 | | 46 | 10 | | 47 | 2 | | 48 | 8 | | 49 | 14 |
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| 45.17% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 10 | | diversityRatio | 0.20772946859903382 | | totalSentences | 207 | | uniqueOpeners | 43 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 131 | | matches | (empty) | | ratio | 0 | |
| 49.01% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 56 | | totalSentences | 131 | | matches | | 0 | "She yanked the bolt." | | 1 | "It gave with a shriek" | | 2 | "He filled the narrow landing." | | 3 | "His platinum hair gleamed under" | | 4 | "He had not bothered with" | | 5 | "Her knuckles blanched." | | 6 | "His mouth twitched." | | 7 | "Her bare feet caught on" | | 8 | "He tapped his cane once" | | 9 | "He took in the mess" | | 10 | "His gaze snagged on the" | | 11 | "She had not changed since" | | 12 | "She set the mug down" | | 13 | "He shrugged off his jacket" | | 14 | "They brushed her shoulder." | | 15 | "She hated how he noticed." | | 16 | "She reached for the mug" | | 17 | "Her bright blue eyes stayed" | | 18 | "He dragged a hand through" | | 19 | "He smelled of rain and" |
| | ratio | 0.427 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 123 | | totalSentences | 131 | | matches | | 0 | "The third deadbolt stuck." | | 1 | "Rory threw her shoulder into" | | 2 | "The wood swelled with heat" | | 3 | "Ptolemy threaded between her ankles" | | 4 | "She yanked the bolt." | | 5 | "It gave with a shriek" | | 6 | "The door opened onto Lucien" | | 7 | "He filled the narrow landing." | | 8 | "Charcoal suit, waistcoat, no crease" | | 9 | "His platinum hair gleamed under" | | 10 | "The ivory handle of his" | | 11 | "He had not bothered with" | | 12 | "Rory kept her hand on" | | 13 | "Her knuckles blanched." | | 14 | "His mouth twitched." | | 15 | "The line between his brows" | | 16 | "Ptolemy made the decision for" | | 17 | "The tabby butted his head" | | 18 | "Rory stepped back." | | 19 | "The movement was short, abrupt." |
| | ratio | 0.939 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 131 | | matches | (empty) | | ratio | 0 | |
| 87.91% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 39 | | technicalSentenceCount | 3 | | matches | | 0 | "That night in the warehouse off the Thames came back whole — the smell of river mud, the sigil burned into the crate, Lucien's hand on her wrist pulling her bac…" | | 1 | "He smelled of rain and vetiver and something colder, the faint brimstone that clung to his skin when his other blood rose." | | 2 | "He made a low sound and caged her with his arms, careful of the cat, careful of the books, careful of her in a way that made her chest ache." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 0 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |