| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 15 | | adverbTagCount | 1 | | adverbTags | | 0 | "He stopped just [just]" |
| | dialogueSentences | 41 | | tagDensity | 0.366 | | leniency | 0.732 | | rawRatio | 0.067 | | effectiveRatio | 0.049 | |
| 87.71% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1221 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | 0 | "softly" | | 1 | "really" | | 2 | "slightly" |
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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) | |
| 59.05% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1221 | | totalAiIsms | 10 | | found | | | highlights | | 0 | "vibrated" | | 1 | "silence" | | 2 | "throbbed" | | 3 | "echo" | | 4 | "velvet" | | 5 | "charged" | | 6 | "navigate" | | 7 | "could feel" | | 8 | "magnetic" | | 9 | "tension" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 79 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 0 | | narrationSentences | 79 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 103 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 40 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1221 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 8 | | unquotedAttributions | 0 | | matches | (empty) | |
| 97.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 25 | | wordCount | 860 | | uniqueNames | 10 | | maxNameDensity | 1.05 | | worstName | "Aurora" | | maxWindowNameDensity | 2 | | worstWindowName | "Lucien" | | discoveredNames | | Carter | 1 | | Brick | 1 | | Lane | 1 | | Moreau | 1 | | Ptolemy | 1 | | Lucien | 7 | | Aurora | 9 | | London | 1 | | Avaros | 1 | | Eva | 2 |
| | persons | | 0 | "Carter" | | 1 | "Moreau" | | 2 | "Lucien" | | 3 | "Aurora" | | 4 | "Eva" |
| | places | | | globalScore | 0.977 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 55 | | glossingSentenceCount | 1 | | matches | | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.819 | | wordCount | 1221 | | matches | | 0 | "Not after the way she had vanished from his life three months ago, leaving nothing but a note on a barstool" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 103 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 38 | | mean | 32.13 | | std | 23.43 | | cv | 0.729 | | sampleLengths | | 0 | 94 | | 1 | 32 | | 2 | 58 | | 3 | 50 | | 4 | 19 | | 5 | 11 | | 6 | 58 | | 7 | 30 | | 8 | 61 | | 9 | 29 | | 10 | 47 | | 11 | 68 | | 12 | 57 | | 13 | 2 | | 14 | 38 | | 15 | 5 | | 16 | 14 | | 17 | 66 | | 18 | 22 | | 19 | 6 | | 20 | 24 | | 21 | 55 | | 22 | 3 | | 23 | 22 | | 24 | 4 | | 25 | 38 | | 26 | 76 | | 27 | 5 | | 28 | 5 | | 29 | 4 | | 30 | 32 | | 31 | 54 | | 32 | 17 | | 33 | 20 | | 34 | 19 | | 35 | 19 | | 36 | 23 | | 37 | 34 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 79 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 151 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 103 | | ratio | 0 | | matches | (empty) | |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 866 | | adjectiveStacks | 1 | | stackExamples | | 0 | "small crescent-shaped scar" |
| | adverbCount | 24 | | adverbRatio | 0.02771362586605081 | | lyAdverbCount | 8 | | lyAdverbRatio | 0.009237875288683603 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 103 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 103 | | mean | 11.85 | | std | 8.08 | | cv | 0.682 | | sampleLengths | | 0 | 15 | | 1 | 18 | | 2 | 4 | | 3 | 19 | | 4 | 6 | | 5 | 32 | | 6 | 4 | | 7 | 2 | | 8 | 26 | | 9 | 17 | | 10 | 11 | | 11 | 12 | | 12 | 7 | | 13 | 11 | | 14 | 7 | | 15 | 11 | | 16 | 32 | | 17 | 15 | | 18 | 4 | | 19 | 4 | | 20 | 1 | | 21 | 1 | | 22 | 1 | | 23 | 4 | | 24 | 8 | | 25 | 19 | | 26 | 15 | | 27 | 16 | | 28 | 8 | | 29 | 22 | | 30 | 9 | | 31 | 4 | | 32 | 5 | | 33 | 8 | | 34 | 12 | | 35 | 23 | | 36 | 14 | | 37 | 15 | | 38 | 11 | | 39 | 19 | | 40 | 17 | | 41 | 19 | | 42 | 11 | | 43 | 17 | | 44 | 21 | | 45 | 10 | | 46 | 7 | | 47 | 40 | | 48 | 2 | | 49 | 7 |
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| 40.45% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 10 | | diversityRatio | 0.30097087378640774 | | totalSentences | 103 | | uniqueOpeners | 31 | |
| 45.66% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 73 | | matches | | 0 | "Only then was Brick Lane" |
| | ratio | 0.014 | |
| 11.78% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 38 | | totalSentences | 73 | | matches | | 0 | "She knew the sequence." | | 1 | "She hadn't expected anyone." | | 2 | "Her bright blue eyes narrowed" | | 3 | "She didn't need to see" | | 4 | "She didn't move to open" | | 5 | "She just stood there, her" | | 6 | "She unlocked the bolts." | | 7 | "She opened the door." | | 8 | "He wore a tailored charcoal" | | 9 | "His ivory-handled cane rested against" | | 10 | "He smelled of rain, expensive" | | 11 | "Her voice was steady, cool-headed," | | 12 | "He didn't need to." | | 13 | "His presence was invasive enough." | | 14 | "His eyes, heterochromatic and unsettling," | | 15 | "He finally stepped over the" | | 16 | "She closed the door and" | | 17 | "She turned to face him," | | 18 | "He leaned forward, the movement" | | 19 | "He took a step closer" |
| | ratio | 0.521 | |
| 7.95% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 66 | | totalSentences | 73 | | matches | | 0 | "The third deadbolt slid home" | | 1 | "Aurora Carter pressed her back" | | 2 | "She knew the sequence." | | 3 | "Eva had drilled it into" | | 4 | "She hadn't expected anyone." | | 5 | "Aurora moved to the peephole," | | 6 | "Her bright blue eyes narrowed" | | 7 | "She didn't need to see" | | 8 | "The silhouette was too tall," | | 9 | "The platinum hair caught the" | | 10 | "She didn't move to open" | | 11 | "She just stood there, her" | | 12 | "The small crescent-shaped scar on" | | 13 | "a voice came through the" | | 14 | "She unlocked the bolts." | | 15 | "She opened the door." | | 16 | "Lucien Moreau stood there, filling" | | 17 | "He wore a tailored charcoal" | | 18 | "His ivory-handled cane rested against" | | 19 | "He smelled of rain, expensive" |
| | ratio | 0.904 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 73 | | matches | (empty) | | ratio | 0 | |
| 0.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 33 | | technicalSentenceCount | 7 | | matches | | 0 | "The small crescent-shaped scar on her wrist throbbed, a phantom echo of the childhood accident that had taught her how to bleed, and the adult mistakes that tau…" | | 1 | "He smelled of rain, expensive tobacco, and the ozone tang of something that wasn't quite human." | | 2 | "Ptolemy, the tabby cat, wound himself around Lucien's polished shoes, purring with a lack of self-preservation that annoyed Aurora." | | 3 | "The sharp line of his jaw, the slicked-back hair that hid the horns he kept sheathed, the way his suit strained slightly against his shoulders." | | 4 | "He was half-demon, a creature of the realm of Avaros, and he had been the one person who made her feel safe enough to be reckless." | | 5 | "She could feel the heat radiating from him, a physical pull that made her knees weak." | | 6 | "It was the same pull that had brought them together in the first place, the magnetic attraction that had complicated everything." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 15 | | uselessAdditionCount | 4 | | matches | | 0 | "She closed, her movements sharp" | | 1 | "She gestured, the stacks of paper" | | 2 | "He reached out, his hand hovering near her arm" | | 3 | "she said, her voice firm," |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 4 | | fancyCount | 1 | | fancyTags | | 0 | "she whispered (whisper)" |
| | dialogueSentences | 41 | | tagDensity | 0.098 | | leniency | 0.195 | | rawRatio | 0.25 | | effectiveRatio | 0.049 | |