| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 16 | | adverbTagCount | 1 | | adverbTags | | 0 | "she said again [again]" |
| | dialogueSentences | 96 | | tagDensity | 0.167 | | leniency | 0.333 | | rawRatio | 0.063 | | effectiveRatio | 0.021 | |
| 97.46% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1970 | | 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) | |
| 77.16% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1970 | | totalAiIsms | 9 | | found | | | highlights | | 0 | "flicked" | | 1 | "familiar" | | 2 | "measured" | | 3 | "echoed" | | 4 | "trembled" | | 5 | "silence" | | 6 | "stomach" | | 7 | "pulse" |
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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 | 135 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 2 | | narrationSentences | 135 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 215 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 52 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1970 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 18 | | unquotedAttributions | 0 | | matches | (empty) | |
| 95.34% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 33 | | wordCount | 1372 | | uniqueNames | 6 | | maxNameDensity | 1.09 | | worstName | "Rory" | | maxWindowNameDensity | 2 | | worstWindowName | "Rory" | | discoveredNames | | Silas | 1 | | Moreau | 1 | | Rory | 15 | | Soho | 1 | | Ptolemy | 6 | | Lucien | 9 |
| | persons | | 0 | "Silas" | | 1 | "Moreau" | | 2 | "Rory" | | 3 | "Ptolemy" | | 4 | "Lucien" |
| | places | | | globalScore | 0.953 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 77 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 98.48% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 2 | | per1kWords | 1.015 | | wordCount | 1970 | | matches | | 0 | "not for support but for habit" | | 1 | "not drawing a weapon because she didn’t have one, but because the body remembered before the mind accepted the thr" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 215 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 120 | | mean | 16.42 | | std | 15.5 | | cv | 0.944 | | sampleLengths | | 0 | 33 | | 1 | 38 | | 2 | 13 | | 3 | 55 | | 4 | 7 | | 5 | 3 | | 6 | 21 | | 7 | 6 | | 8 | 47 | | 9 | 5 | | 10 | 12 | | 11 | 5 | | 12 | 12 | | 13 | 31 | | 14 | 2 | | 15 | 17 | | 16 | 2 | | 17 | 35 | | 18 | 22 | | 19 | 9 | | 20 | 36 | | 21 | 29 | | 22 | 15 | | 23 | 28 | | 24 | 11 | | 25 | 5 | | 26 | 78 | | 27 | 3 | | 28 | 8 | | 29 | 5 | | 30 | 2 | | 31 | 7 | | 32 | 7 | | 33 | 6 | | 34 | 93 | | 35 | 15 | | 36 | 17 | | 37 | 2 | | 38 | 3 | | 39 | 5 | | 40 | 7 | | 41 | 8 | | 42 | 14 | | 43 | 8 | | 44 | 4 | | 45 | 10 | | 46 | 35 | | 47 | 45 | | 48 | 12 | | 49 | 11 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 135 | | matches | | 0 | "being measured" | | 1 | "WAS BORROWED" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 231 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 2 | | flaggedSentences | 1 | | totalSentences | 215 | | ratio | 0.005 | | matches | | 0 | "Hated more that she remembered how those hands had felt on her waist in a crowded alley outside Soho, steering her away from danger; how they had looked around a glass with a cigarette he never smoked; how they had trembled once, just once, when she’d said she wasn’t impressed by him." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1373 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 49 | | adverbRatio | 0.035688273852876914 | | lyAdverbCount | 4 | | lyAdverbRatio | 0.0029133284777858705 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 215 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 215 | | mean | 9.16 | | std | 7.88 | | cv | 0.86 | | sampleLengths | | 0 | 11 | | 1 | 22 | | 2 | 25 | | 3 | 4 | | 4 | 5 | | 5 | 4 | | 6 | 13 | | 7 | 18 | | 8 | 4 | | 9 | 19 | | 10 | 14 | | 11 | 7 | | 12 | 3 | | 13 | 21 | | 14 | 6 | | 15 | 13 | | 16 | 7 | | 17 | 5 | | 18 | 22 | | 19 | 5 | | 20 | 3 | | 21 | 4 | | 22 | 5 | | 23 | 5 | | 24 | 10 | | 25 | 2 | | 26 | 28 | | 27 | 3 | | 28 | 2 | | 29 | 15 | | 30 | 2 | | 31 | 2 | | 32 | 23 | | 33 | 12 | | 34 | 5 | | 35 | 17 | | 36 | 4 | | 37 | 5 | | 38 | 10 | | 39 | 16 | | 40 | 10 | | 41 | 29 | | 42 | 4 | | 43 | 11 | | 44 | 15 | | 45 | 13 | | 46 | 5 | | 47 | 6 | | 48 | 5 | | 49 | 14 |
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| 47.44% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 8 | | diversityRatio | 0.30697674418604654 | | totalSentences | 215 | | uniqueOpeners | 66 | |
| 86.96% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 115 | | matches | | 0 | "Too steady for that." | | 1 | "Just the words." | | 2 | "Then back to Lucien." |
| | ratio | 0.026 | |
| 42.61% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 51 | | totalSentences | 115 | | matches | | 0 | "She pulled the last bolt" | | 1 | "His platinum hair sat slicked" | | 2 | "His gaze dropped to her" | | 3 | "She hooked a thumb over" | | 4 | "He looked down the hall," | | 5 | "Her jaw set." | | 6 | "His eyes flicked to the" | | 7 | "He shifted his cane and" | | 8 | "His gaze held hers." | | 9 | "It made something in her" | | 10 | "She pushed the door wider" | | 11 | "He crossed the threshold with" | | 12 | "She turned and found him" | | 13 | "His expression didn’t move, but" | | 14 | "His attention came back to" | | 15 | "His shoulders lifted a fraction." | | 16 | "He removed one glove with" | | 17 | "She hated that she noticed." | | 18 | "she said again, because silence" | | 19 | "He leaned lightly on the" |
| | ratio | 0.443 | |
| 38.26% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 97 | | totalSentences | 115 | | matches | | 0 | "The first deadbolt gave with" | | 1 | "Rory paused with her hand" | | 2 | "A knock had cut through" | | 3 | "She pulled the last bolt" | | 4 | "Lucien Moreau stood on the" | | 5 | "Rain glossed the shoulders." | | 6 | "His platinum hair sat slicked" | | 7 | "The ivory handle of his" | | 8 | "Rory kept her hand on" | | 9 | "His gaze dropped to her" | | 10 | "She hooked a thumb over" | | 11 | "Books teetered in stacks on" | | 12 | "Ptolemy the tabby lifted his" | | 13 | "Lucien’s mouth tilted." | | 14 | "He looked down the hall," | | 15 | "The smell of wet pavement" | | 16 | "Her jaw set." | | 17 | "His eyes flicked to the" | | 18 | "He shifted his cane and" | | 19 | "Rory’s laugh came out sharp." |
| | ratio | 0.843 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 115 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 48 | | technicalSentenceCount | 2 | | matches | | 0 | "His expression didn’t move, but his gaze lingered on everything as if he could read the shape of her life in the mess." | | 1 | "His cane tapped once against the floor, a controlled little sound that did nothing to steady the pulse in her wrist." |
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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 | 9 | | fancyCount | 2 | | fancyTags | | 0 | "he murmured (murmur)" | | 1 | "he agreed (agree)" |
| | dialogueSentences | 96 | | tagDensity | 0.094 | | leniency | 0.188 | | rawRatio | 0.222 | | effectiveRatio | 0.042 | |