| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 19 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 61 | | tagDensity | 0.311 | | leniency | 0.623 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1597 | | 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) | |
| 62.43% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1597 | | totalAiIsms | 12 | | found | | | highlights | | 0 | "silence" | | 1 | "gleaming" | | 2 | "traced" | | 3 | "sanctuary" | | 4 | "weight" | | 5 | "potential" | | 6 | "charm" | | 7 | "flicker" | | 8 | "resonance" | | 9 | "footsteps" | | 10 | "flickered" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "blood ran cold" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 106 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 2 | | narrationSentences | 106 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 148 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 45 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1607 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 21 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 51 | | wordCount | 1076 | | uniqueNames | 18 | | maxNameDensity | 0.93 | | worstName | "Eva" | | maxWindowNameDensity | 2 | | worstWindowName | "Eva" | | discoveredNames | | Eva | 10 | | Moreau | 2 | | Savile | 1 | | Row | 1 | | Ptolemy | 5 | | Dragon | 1 | | Tooth | 1 | | Lucien | 9 | | Rory | 6 | | Brick | 2 | | Lane | 2 | | Golden | 1 | | Empress | 1 | | London | 1 | | Avarosi | 1 | | Codex | 1 | | French | 1 | | Three | 5 |
| | persons | | 0 | "Eva" | | 1 | "Moreau" | | 2 | "Row" | | 3 | "Ptolemy" | | 4 | "Lucien" | | 5 | "Rory" |
| | places | | 0 | "Dragon" | | 1 | "Brick" | | 2 | "Lane" | | 3 | "London" |
| | globalScore | 1 | | windowScore | 1 | |
| 80.56% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 72 | | glossingSentenceCount | 2 | | matches | | 0 | "seemed pointless until the moment it wasn't" | | 1 | "looked like ammunition" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1607 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 148 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 74 | | mean | 21.72 | | std | 20.06 | | cv | 0.924 | | sampleLengths | | 0 | 8 | | 1 | 42 | | 2 | 4 | | 3 | 53 | | 4 | 22 | | 5 | 14 | | 6 | 46 | | 7 | 8 | | 8 | 2 | | 9 | 2 | | 10 | 2 | | 11 | 61 | | 12 | 9 | | 13 | 14 | | 14 | 2 | | 15 | 63 | | 16 | 2 | | 17 | 31 | | 18 | 5 | | 19 | 35 | | 20 | 4 | | 21 | 3 | | 22 | 20 | | 23 | 50 | | 24 | 3 | | 25 | 82 | | 26 | 2 | | 27 | 50 | | 28 | 43 | | 29 | 33 | | 30 | 3 | | 31 | 4 | | 32 | 43 | | 33 | 37 | | 34 | 2 | | 35 | 11 | | 36 | 1 | | 37 | 18 | | 38 | 59 | | 39 | 3 | | 40 | 5 | | 41 | 39 | | 42 | 5 | | 43 | 40 | | 44 | 6 | | 45 | 5 | | 46 | 26 | | 47 | 14 | | 48 | 4 | | 49 | 44 |
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| 98.64% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 106 | | matches | | 0 | "was ruined" | | 1 | "been told" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 195 | | matches | (empty) | |
| 27.03% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 9 | | semicolonCount | 0 | | flaggedSentences | 6 | | totalSentences | 148 | | ratio | 0.041 | | matches | | 0 | "She saw it in the way his jaw tightened, the way his heterochromatic eyes — amber and black — went sharp and glassy." | | 1 | "He hadn't — Rory made sure of that — but he had the particular grace of someone who assessed every room he entered for exits and cover." | | 2 | "It was comprehensive — Eva attracted injuries the way Brick Lane attracted tourists." | | 3 | "Up close, she could smell him beneath the blood — cloves and wintergreen, the strange alchemy of half-demon chemistry." | | 4 | "The skin at the edges had a faint iridescence — demon tissue, trying to close." | | 5 | "The third deadbolt — the one that always jammed in the cold — began to turn." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 747 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 19 | | adverbRatio | 0.025435073627844713 | | lyAdverbCount | 3 | | lyAdverbRatio | 0.004016064257028112 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 148 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 148 | | mean | 10.86 | | std | 8.42 | | cv | 0.776 | | sampleLengths | | 0 | 4 | | 1 | 4 | | 2 | 15 | | 3 | 27 | | 4 | 4 | | 5 | 16 | | 6 | 20 | | 7 | 17 | | 8 | 22 | | 9 | 14 | | 10 | 7 | | 11 | 2 | | 12 | 29 | | 13 | 8 | | 14 | 8 | | 15 | 2 | | 16 | 2 | | 17 | 2 | | 18 | 16 | | 19 | 23 | | 20 | 11 | | 21 | 11 | | 22 | 9 | | 23 | 5 | | 24 | 9 | | 25 | 2 | | 26 | 9 | | 27 | 19 | | 28 | 35 | | 29 | 2 | | 30 | 6 | | 31 | 17 | | 32 | 8 | | 33 | 5 | | 34 | 7 | | 35 | 15 | | 36 | 10 | | 37 | 3 | | 38 | 4 | | 39 | 3 | | 40 | 20 | | 41 | 4 | | 42 | 12 | | 43 | 14 | | 44 | 20 | | 45 | 3 | | 46 | 10 | | 47 | 27 | | 48 | 45 | | 49 | 2 |
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| 50.23% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 9 | | diversityRatio | 0.33783783783783783 | | totalSentences | 148 | | uniqueOpeners | 50 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 94 | | matches | | 0 | "Of course it did." | | 1 | "Then he unbuttoned his jacket." | | 2 | "Even the curry-smelling air seemed" |
| | ratio | 0.032 | |
| 71.06% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 35 | | totalSentences | 94 | | matches | | 0 | "His charcoal suit, usually immaculate" | | 1 | "His platinum hair had come" | | 2 | "he said, his accent thicker" | | 3 | "She looked at the blood" | | 4 | "He straightened, and the movement" | | 5 | "She saw it in the" | | 6 | "His cane hung from his" | | 7 | "She almost laughed" | | 8 | "She stepped into the doorway," | | 9 | "His hand pressed harder against" | | 10 | "She stared at him." | | 11 | "She stepped aside." | | 12 | "He hadn't — Rory made" | | 13 | "She watched him catalog the" | | 14 | "She locked the first deadbolt," | | 15 | "She nodded at Ptolemy, who" | | 16 | "He set his cane across" | | 17 | "She crossed to the bathroom" | | 18 | "It was comprehensive — Eva" | | 19 | "She knelt beside the chair." |
| | ratio | 0.372 | |
| 61.06% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 75 | | totalSentences | 94 | | matches | | 0 | "The third deadbolt jammed." | | 1 | "Rory twisted the key the" | | 2 | "The lock surrendered with a" | | 3 | "Lucien Moreau leaned against the" | | 4 | "His charcoal suit, usually immaculate" | | 5 | "His platinum hair had come" | | 6 | "he said, his accent thicker" | | 7 | "Rory's hand tightened on the" | | 8 | "She looked at the blood" | | 9 | "He straightened, and the movement" | | 10 | "She saw it in the" | | 11 | "His cane hung from his" | | 12 | "She almost laughed" | | 13 | "She stepped into the doorway," | | 14 | "The words landed like a" | | 15 | "Ptolemy crept closer, his tabby" | | 16 | "The cat hissed and retreated" | | 17 | "Lucien opened his mouth, then" | | 18 | "His hand pressed harder against" | | 19 | "Demon blood or human blood," |
| | ratio | 0.798 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 94 | | matches | (empty) | | ratio | 0 | |
| 55.75% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 41 | | technicalSentenceCount | 5 | | matches | | 0 | "The man who'd taught her to read demonic script over late-night takeaways." | | 1 | "He set his cane across his knees with the precision of a man who treated every object as a potential weapon." | | 2 | "She'd heard it whispered in the back rooms of the Golden Empress, always by people who checked over their shoulders first." | | 3 | "Eva was always neck-deep in research that seemed pointless until the moment it wasn't." | | 4 | "A low, subsonic vibration that made the water in Eva's forgotten teacup tremble." |
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| 98.68% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 19 | | uselessAdditionCount | 1 | | matches | | 0 | "he said, his accent thicker than she remembered," |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 4 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 61 | | tagDensity | 0.066 | | leniency | 0.131 | | rawRatio | 0 | | effectiveRatio | 0 | |