| 84.06% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 22 | | adverbTagCount | 4 | | adverbTags | | 0 | "he said finally [finally]" | | 1 | "He shifted again [again]" | | 2 | "Rory asked quietly [quietly]" | | 3 | "Rory crossed back [back]" |
| | dialogueSentences | 69 | | tagDensity | 0.319 | | leniency | 0.638 | | rawRatio | 0.182 | | effectiveRatio | 0.116 | |
| 78.18% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1375 | | totalAiIsmAdverbs | 6 | | found | | | highlights | | 0 | "lightly" | | 1 | "very" | | 2 | "slightly" | | 3 | "slowly" | | 4 | "truly" |
| |
| 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) | |
| 45.45% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1375 | | totalAiIsms | 15 | | found | | | highlights | | 0 | "pristine" | | 1 | "weight" | | 2 | "intensity" | | 3 | "unsettled" | | 4 | "flawless" | | 5 | "flickered" | | 6 | "dancing" | | 7 | "implication" | | 8 | "coded" | | 9 | "ensure" | | 10 | "marble" |
| |
| 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 | 76 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 1 | | narrationSentences | 76 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 122 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 47 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1371 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 16 | | unquotedAttributions | 0 | | matches | (empty) | |
| 50.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 33 | | wordCount | 702 | | uniqueNames | 9 | | maxNameDensity | 1.85 | | worstName | "Rory" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Lucien" | | discoveredNames | | London | 3 | | Lucien | 11 | | Moreau | 1 | | Marseille | 1 | | Shoreditch | 1 | | Rory | 13 | | Understanding | 1 | | Brick | 1 | | Lane | 1 |
| | persons | | 0 | "Lucien" | | 1 | "Moreau" | | 2 | "Rory" | | 3 | "Understanding" |
| | places | | 0 | "London" | | 1 | "Marseille" | | 2 | "Shoreditch" | | 3 | "Brick" | | 4 | "Lane" |
| | globalScore | 0.574 | | windowScore | 0.5 | |
| 0.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 52 | | glossingSentenceCount | 4 | | matches | | 0 | "looked like something that had been dragg" | | 1 | "felt like a deliberate statement" | | 2 | "quite managing the repairs" | | 3 | "Not quite a smile, but something in the same family" |
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| 54.12% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 2 | | per1kWords | 1.459 | | wordCount | 1371 | | matches | | 0 | "not beside him, but near enough to speak without raising her voice" | | 1 | "Not quite a smile, but something in the same family" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 122 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 68 | | mean | 20.16 | | std | 19.52 | | cv | 0.968 | | sampleLengths | | 0 | 16 | | 1 | 37 | | 2 | 69 | | 3 | 1 | | 4 | 2 | | 5 | 39 | | 6 | 3 | | 7 | 35 | | 8 | 29 | | 9 | 3 | | 10 | 48 | | 11 | 22 | | 12 | 49 | | 13 | 7 | | 14 | 7 | | 15 | 36 | | 16 | 9 | | 17 | 62 | | 18 | 28 | | 19 | 4 | | 20 | 6 | | 21 | 41 | | 22 | 32 | | 23 | 2 | | 24 | 40 | | 25 | 20 | | 26 | 11 | | 27 | 3 | | 28 | 1 | | 29 | 10 | | 30 | 7 | | 31 | 51 | | 32 | 3 | | 33 | 10 | | 34 | 2 | | 35 | 56 | | 36 | 6 | | 37 | 61 | | 38 | 6 | | 39 | 60 | | 40 | 6 | | 41 | 3 | | 42 | 36 | | 43 | 8 | | 44 | 64 | | 45 | 9 | | 46 | 37 | | 47 | 1 | | 48 | 4 | | 49 | 40 |
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| 96.03% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 76 | | matches | | 0 | "been dragged" | | 1 | "was carved" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 121 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 122 | | ratio | 0 | | matches | (empty) | |
| 79.50% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 705 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 41 | | adverbRatio | 0.05815602836879433 | | lyAdverbCount | 18 | | lyAdverbRatio | 0.02553191489361702 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 122 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 122 | | mean | 11.24 | | std | 9.89 | | cv | 0.88 | | sampleLengths | | 0 | 16 | | 1 | 7 | | 2 | 30 | | 3 | 12 | | 4 | 24 | | 5 | 17 | | 6 | 9 | | 7 | 7 | | 8 | 1 | | 9 | 2 | | 10 | 26 | | 11 | 6 | | 12 | 7 | | 13 | 3 | | 14 | 9 | | 15 | 26 | | 16 | 9 | | 17 | 10 | | 18 | 1 | | 19 | 9 | | 20 | 3 | | 21 | 9 | | 22 | 8 | | 23 | 18 | | 24 | 13 | | 25 | 6 | | 26 | 3 | | 27 | 13 | | 28 | 39 | | 29 | 8 | | 30 | 2 | | 31 | 7 | | 32 | 4 | | 33 | 2 | | 34 | 1 | | 35 | 28 | | 36 | 8 | | 37 | 9 | | 38 | 37 | | 39 | 25 | | 40 | 2 | | 41 | 6 | | 42 | 4 | | 43 | 7 | | 44 | 9 | | 45 | 4 | | 46 | 3 | | 47 | 3 | | 48 | 14 | | 49 | 15 |
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| 59.29% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 6 | | diversityRatio | 0.38524590163934425 | | totalSentences | 122 | | uniqueOpeners | 47 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 68 | | matches | (empty) | | ratio | 0 | |
| 84.71% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 23 | | totalSentences | 68 | | matches | | 0 | "He looked like something that" | | 1 | "His platinum hair had lost" | | 2 | "He leaned on it with" | | 3 | "His heterochromatic eyes, that impossible" | | 4 | "She'd learned to hate that" | | 5 | "He didn't move from where" | | 6 | "It unsettled her more than" | | 7 | "She stepped back." | | 8 | "He moved with careful deliberation," | | 9 | "He'd walked away from her" | | 10 | "She moved into the flat's" | | 11 | "He settled into the nearest" | | 12 | "He pressed his fingertips together," | | 13 | "He shifted his weight, and" | | 14 | "She held up a hand" | | 15 | "His amber eye seemed to" | | 16 | "he said finally" | | 17 | "He shifted again, this time" | | 18 | "she repeated, sharper this time" | | 19 | "He pulled his hand back," |
| | ratio | 0.338 | |
| 40.88% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 57 | | totalSentences | 68 | | matches | | 0 | "Rory didn't recognise the shadow" | | 1 | "He looked like something that" | | 2 | "His platinum hair had lost" | | 3 | "The tailored charcoal suit, normally" | | 4 | "He leaned on it with" | | 5 | "His heterochromatic eyes, that impossible" | | 6 | "She'd learned to hate that" | | 7 | "He didn't move from where" | | 8 | "The old Lucien would have" | | 9 | "This version, the one bleeding" | | 10 | "It unsettled her more than" | | 11 | "She stepped back." | | 12 | "He moved with careful deliberation," | | 13 | "The limp hadn't been there" | | 14 | "He'd walked away from her" | | 15 | "Rory locked the door behind" | | 16 | "The sound of each one" | | 17 | "She moved into the flat's" | | 18 | "The space felt smaller with" | | 19 | "The non-sequitur landed wrong." |
| | ratio | 0.838 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 68 | | matches | (empty) | | ratio | 0 | |
| 45.45% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 22 | | technicalSentenceCount | 3 | | matches | | 0 | "His platinum hair had lost its architectural precision, falling across his forehead in a way that suggested he'd raked his hands through it repeatedly." | | 1 | "His heterochromatic eyes, that impossible amber and black, fixed on her with the intensity that had always made her chest feel too small for her ribs." | | 2 | "Bleeding slightly into her upholstery, watching her with eyes that belonged to two different worlds." |
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| 79.55% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 22 | | uselessAdditionCount | 2 | | matches | | 0 | "She moved, not looking at him" | | 1 | "He shifted again, this time reaching for something in his jacket" |
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| 92.03% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 8 | | fancyCount | 4 | | fancyTags | | 0 | "He pressed (press)" | | 1 | "Lucien agreed (agree)" | | 2 | "she repeated (repeat)" | | 3 | "she breathed (breathe)" |
| | dialogueSentences | 69 | | tagDensity | 0.116 | | leniency | 0.232 | | rawRatio | 0.5 | | effectiveRatio | 0.116 | |