| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 16 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 48 | | tagDensity | 0.333 | | leniency | 0.667 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 82.16% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1401 | | totalAiIsmAdverbs | 5 | | found | | | highlights | | 0 | "slightly" | | 1 | "slowly" | | 2 | "quickly" | | 3 | "very" |
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| 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) | |
| 89.29% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1401 | | totalAiIsms | 3 | | found | | | highlights | | 0 | "silence" | | 1 | "traced" | | 2 | "efficient" |
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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 | 1 | | narrationSentences | 53 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 53 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 85 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 74 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1403 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 10 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 16 | | wordCount | 726 | | uniqueNames | 6 | | maxNameDensity | 0.69 | | worstName | "Ptolemy" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Ptolemy" | | discoveredNames | | Ptolemy | 5 | | Dublin | 1 | | Lucien | 4 | | Moreau | 1 | | Eva | 4 | | Marseille | 1 |
| | persons | | 0 | "Ptolemy" | | 1 | "Lucien" | | 2 | "Moreau" | | 3 | "Eva" |
| | places | | | globalScore | 1 | | windowScore | 1 | |
| 78.57% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 35 | | glossingSentenceCount | 1 | | matches | | 0 | "tasted like rain and copper, and his hand" |
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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 | 1403 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 85 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 52 | | mean | 26.98 | | std | 24.03 | | cv | 0.891 | | sampleLengths | | 0 | 27 | | 1 | 33 | | 2 | 4 | | 3 | 22 | | 4 | 42 | | 5 | 3 | | 6 | 53 | | 7 | 2 | | 8 | 41 | | 9 | 39 | | 10 | 30 | | 11 | 3 | | 12 | 38 | | 13 | 2 | | 14 | 41 | | 15 | 3 | | 16 | 83 | | 17 | 6 | | 18 | 4 | | 19 | 1 | | 20 | 24 | | 21 | 41 | | 22 | 17 | | 23 | 20 | | 24 | 73 | | 25 | 9 | | 26 | 38 | | 27 | 3 | | 28 | 39 | | 29 | 71 | | 30 | 14 | | 31 | 31 | | 32 | 10 | | 33 | 8 | | 34 | 93 | | 35 | 18 | | 36 | 8 | | 37 | 17 | | 38 | 7 | | 39 | 66 | | 40 | 62 | | 41 | 2 | | 42 | 62 | | 43 | 2 | | 44 | 23 | | 45 | 42 | | 46 | 50 | | 47 | 8 | | 48 | 8 | | 49 | 3 |
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| 98.64% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 53 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 135 | | matches | | |
| 75.63% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 2 | | semicolonCount | 0 | | flaggedSentences | 2 | | totalSentences | 85 | | ratio | 0.024 | | matches | | 0 | "The shirt came off and she catalogued him like a scene she was processing — the old scar across his shoulder from a job in Marseille, the fresh claw-marks, the way his amber eye caught the lamp and his black one swallowed it." | | 1 | "His good hand rose, and she watched it come, and she watched it stop — hovering at her jaw, asking." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 729 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 25 | | adverbRatio | 0.03429355281207133 | | lyAdverbCount | 8 | | lyAdverbRatio | 0.010973936899862825 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 85 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 85 | | mean | 16.51 | | std | 15.05 | | cv | 0.912 | | sampleLengths | | 0 | 5 | | 1 | 22 | | 2 | 8 | | 3 | 25 | | 4 | 4 | | 5 | 22 | | 6 | 2 | | 7 | 40 | | 8 | 3 | | 9 | 23 | | 10 | 7 | | 11 | 23 | | 12 | 2 | | 13 | 13 | | 14 | 28 | | 15 | 5 | | 16 | 19 | | 17 | 15 | | 18 | 3 | | 19 | 27 | | 20 | 3 | | 21 | 19 | | 22 | 19 | | 23 | 2 | | 24 | 2 | | 25 | 30 | | 26 | 2 | | 27 | 7 | | 28 | 3 | | 29 | 44 | | 30 | 39 | | 31 | 6 | | 32 | 4 | | 33 | 1 | | 34 | 14 | | 35 | 10 | | 36 | 27 | | 37 | 14 | | 38 | 17 | | 39 | 3 | | 40 | 5 | | 41 | 12 | | 42 | 73 | | 43 | 9 | | 44 | 15 | | 45 | 23 | | 46 | 3 | | 47 | 8 | | 48 | 31 | | 49 | 28 |
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| 77.25% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 6 | | diversityRatio | 0.5058823529411764 | | totalSentences | 85 | | uniqueOpeners | 43 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 45 | | matches | | 0 | "Slightly iridescent, like oil on" | | 1 | "Somewhere below, the curry house" |
| | ratio | 0.044 | |
| 0.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 27 | | totalSentences | 45 | | matches | | 0 | "She crossed the book-strewn floor," | | 1 | "She threw each one with" | | 2 | "His platinum hair had collapsed" | | 3 | "He offered a smile that" | | 4 | "She looked past his shoulder." | | 5 | "She stepped aside." | | 6 | "She shut the door and" | | 7 | "He had lowered himself onto" | | 8 | "He unbuttoned his waistcoat with" | | 9 | "He laughed, a short, rough" | | 10 | "She crossed to the kitchenette," | | 11 | "She planted her hands on" | | 12 | "She straightened up" | | 13 | "She jabbed a finger at" | | 14 | "He worked the buttons slowly," | | 15 | "She knelt, cleaned the wounds" | | 16 | "His silence stretched long enough" | | 17 | "His voice dropped, and for" | | 18 | "She sat back on her" | | 19 | "He reached down and scratched" |
| | ratio | 0.6 | |
| 26.67% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 39 | | totalSentences | 45 | | matches | | 0 | "The knock came in threes." | | 1 | "Rory set down Ptolemy's food" | | 2 | "Eva had been in Dublin" | | 3 | "The knock came again." | | 4 | "She crossed the book-strewn floor," | | 5 | "She threw each one with" | | 6 | "His platinum hair had collapsed" | | 7 | "The charcoal suit clung to" | | 8 | "He offered a smile that" | | 9 | "She looked past his shoulder." | | 10 | "A man in a rain" | | 11 | "She stepped aside." | | 12 | "Lucien limped past her, trailing" | | 13 | "She shut the door and" | | 14 | "He had lowered himself onto" | | 15 | "He unbuttoned his waistcoat with" | | 16 | "He laughed, a short, rough" | | 17 | "She crossed to the kitchenette," | | 18 | "The kit bounced." | | 19 | "Bandages spilled across the table." |
| | ratio | 0.867 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 45 | | matches | (empty) | | ratio | 0 | |
| 40.82% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 21 | | technicalSentenceCount | 3 | | matches | | 0 | "Slow, deliberate, spaced like a man who knew exactly how long it took to walk down a flight of stairs and reconsider." | | 1 | "He had lowered himself onto the arm of Eva's reading chair, and now he peeled the glove from his right hand, revealing fingers slick with blood that wasn't enti…" | | 2 | "His good hand rose, and she watched it come, and she watched it stop — hovering at her jaw, asking." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 16 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 5 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 48 | | tagDensity | 0.104 | | leniency | 0.208 | | rawRatio | 0 | | effectiveRatio | 0 | |