| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 18 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 56 | | tagDensity | 0.321 | | leniency | 0.643 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 87.89% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1651 | | totalAiIsmAdverbs | 4 | | found | | 0 | | | 1 | | | 2 | | adverb | "barely above a whisper" | | count | 1 |
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| | highlights | | 0 | "slightly" | | 1 | "perfectly" | | 2 | "barely above a whisper" |
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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) | |
| 75.77% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1651 | | totalAiIsms | 8 | | found | | | highlights | | 0 | "silence" | | 1 | "glinting" | | 2 | "warmth" | | 3 | "pulse" | | 4 | "could feel" | | 5 | "silk" | | 6 | "traced" | | 7 | "whisper" |
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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 | 2 | | narrationSentences | 117 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 117 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 154 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 35 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1671 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 23 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 30 | | wordCount | 1239 | | uniqueNames | 11 | | maxNameDensity | 0.4 | | worstName | "Lucien" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Lucien" | | discoveredNames | | Moreau | 1 | | Eva | 3 | | French | 2 | | London | 3 | | Wednesday | 1 | | Châteauneuf-du-Pape | 1 | | Lucien | 5 | | Ptolemy | 5 | | Rory | 5 | | Casual | 1 | | Three | 3 |
| | persons | | 0 | "Moreau" | | 1 | "Eva" | | 2 | "Wednesday" | | 3 | "Châteauneuf-du-Pape" | | 4 | "Lucien" | | 5 | "Ptolemy" | | 6 | "Rory" |
| | places | | | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 79 | | glossingSentenceCount | 1 | | matches | | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1671 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 2 | | totalSentences | 154 | | matches | | 0 | "chose that moment" | | 1 | "recognized that silhouette" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 71 | | mean | 23.54 | | std | 21.64 | | cv | 0.919 | | sampleLengths | | 0 | 36 | | 1 | 61 | | 2 | 39 | | 3 | 5 | | 4 | 64 | | 5 | 19 | | 6 | 27 | | 7 | 1 | | 8 | 46 | | 9 | 1 | | 10 | 5 | | 11 | 54 | | 12 | 25 | | 13 | 43 | | 14 | 50 | | 15 | 40 | | 16 | 4 | | 17 | 6 | | 18 | 39 | | 19 | 3 | | 20 | 61 | | 21 | 2 | | 22 | 13 | | 23 | 48 | | 24 | 5 | | 25 | 20 | | 26 | 3 | | 27 | 2 | | 28 | 1 | | 29 | 13 | | 30 | 8 | | 31 | 35 | | 32 | 53 | | 33 | 63 | | 34 | 15 | | 35 | 18 | | 36 | 3 | | 37 | 2 | | 38 | 10 | | 39 | 34 | | 40 | 6 | | 41 | 10 | | 42 | 14 | | 43 | 37 | | 44 | 22 | | 45 | 3 | | 46 | 84 | | 47 | 47 | | 48 | 38 | | 49 | 23 |
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| 93.27% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 4 | | totalSentences | 117 | | matches | | 0 | "was slicked" | | 1 | "been prepared" | | 2 | "was supposed" | | 3 | "been held" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 224 | | matches | | 0 | "was expecting" | | 1 | "was standing" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 19 | | semicolonCount | 1 | | flaggedSentences | 14 | | totalSentences | 154 | | ratio | 0.091 | | matches | | 0 | "She made a mental note to oil it — again — and pulled the door open." | | 1 | "His mismatched eyes — one amber, one black — tracked down to her bare feet, up past the oversized university sweatshirt she'd slept in, and settled on her face." | | 2 | "She hadn't been prepared for that — the accent, the low register, the way French vowels still clung to his consonants no matter how many years he'd spent in London." | | 3 | "Lucien crouched — no stiffness, no awkwardness, just a fluid lowering of his body that made his suit jacket pull across his shoulders — and scratched behind Ptolemy's ears." | | 4 | "No — she knew why she was angry." | | 5 | "Because she'd asked him a question — one question, the only question that mattered — and he'd buttoned his jacket, picked up his cane, and walked out of her life without answering it." | | 6 | "The crescent scar on her left wrist peeked out from under her sleeve cuff; she tugged the sleeve down without thinking." | | 7 | "His expression hadn't changed — still that controlled stillness that made him impossible to read — but something in his posture had." | | 8 | "He walked past her into the flat, and she caught the scent of him — cedar and something darker beneath it, something that didn't quite have a name." | | 9 | "That was part of the problem — or part of the pull, she wasn't sure which." | | 10 | "Her fingers found the knot of his tie — silk, because of course it was — and rested there." | | 11 | "His mouth met hers, and he made a sound against her lips — something low, something that had been held back for too long." | | 12 | "The great fixer, the information broker, the man who always had a contingency — undone." | | 13 | "He met her eyes — amber, black, both steady now." |
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| 97.88% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1155 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 49 | | adverbRatio | 0.04242424242424243 | | lyAdverbCount | 9 | | lyAdverbRatio | 0.007792207792207792 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 154 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 154 | | mean | 10.85 | | std | 8.26 | | cv | 0.761 | | sampleLengths | | 0 | 9 | | 1 | 11 | | 2 | 16 | | 3 | 23 | | 4 | 12 | | 5 | 14 | | 6 | 12 | | 7 | 29 | | 8 | 6 | | 9 | 3 | | 10 | 1 | | 11 | 5 | | 12 | 11 | | 13 | 30 | | 14 | 23 | | 15 | 11 | | 16 | 8 | | 17 | 14 | | 18 | 3 | | 19 | 8 | | 20 | 2 | | 21 | 1 | | 22 | 14 | | 23 | 24 | | 24 | 8 | | 25 | 1 | | 26 | 5 | | 27 | 29 | | 28 | 8 | | 29 | 17 | | 30 | 11 | | 31 | 14 | | 32 | 3 | | 33 | 18 | | 34 | 22 | | 35 | 16 | | 36 | 8 | | 37 | 26 | | 38 | 4 | | 39 | 3 | | 40 | 33 | | 41 | 2 | | 42 | 2 | | 43 | 6 | | 44 | 6 | | 45 | 21 | | 46 | 5 | | 47 | 7 | | 48 | 3 | | 49 | 19 |
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| 44.59% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 13 | | diversityRatio | 0.3181818181818182 | | totalSentences | 154 | | uniqueOpeners | 49 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 99 | | matches | | 0 | "Almost a smile." | | 1 | "Of course he'd bring something" | | 2 | "Instead she was standing here" |
| | ratio | 0.03 | |
| 5.86% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 53 | | totalSentences | 99 | | matches | | 0 | "She made a mental note" | | 1 | "His platinum hair was slicked" | | 2 | "He wore a charcoal suit" | | 3 | "His mismatched eyes — one" | | 4 | "She hadn't been prepared for" | | 5 | "She didn't move from the" | | 6 | "He lifted the wine bottle" | | 7 | "He inclined his head, as" | | 8 | "She watched his long fingers" | | 9 | "He was right." | | 10 | "She should have slammed the" | | 11 | "She just couldn't remember why" | | 12 | "His hand stilled on Ptolemy's" | | 13 | "His black eye swallowed light." | | 14 | "She leaned against the doorframe," | | 15 | "She held up her hand," | | 16 | "His expression hadn't changed —" | | 17 | "He was paying attention in" | | 18 | "Her name in his mouth" | | 19 | "He pronounced the R, rolled" |
| | ratio | 0.535 | |
| 40.81% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 83 | | totalSentences | 99 | | matches | | 0 | "The third deadbolt stuck, same" | | 1 | "Rory jiggled the key, felt" | | 2 | "She made a mental note" | | 3 | "Lucien Moreau stood in the" | | 4 | "His platinum hair was slicked" | | 5 | "He wore a charcoal suit" | | 6 | "His mismatched eyes — one" | | 7 | "The corner of his mouth" | | 8 | "The sound of his voice" | | 9 | "She hadn't been prepared for" | | 10 | "She didn't move from the" | | 11 | "He lifted the wine bottle" | | 12 | "A 2018 Châteauneuf-du-Pape." | | 13 | "He inclined his head, as" | | 14 | "Ptolemy chose that moment to" | | 15 | "The tabby butted his head" | | 16 | "Lucien crouched — no stiffness," | | 17 | "The purring was audible from" | | 18 | "She watched his long fingers" | | 19 | "Lucien said, still crouching, still" |
| | ratio | 0.838 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 99 | | matches | | 0 | "Because he'd walked away." | | 1 | "Because she'd asked him a" |
| | ratio | 0.02 | |
| 23.81% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 48 | | technicalSentenceCount | 8 | | matches | | 0 | "He inclined his head, as though she'd made a reasonable point in a negotiation." | | 1 | "Lucien crouched — no stiffness, no awkwardness, just a fluid lowering of his body that made his suit jacket pull across his shoulders — and scratched behind Pto…" | | 2 | "Should have left him standing on Eva's doorstep with his expensive wine and his expensive suit and his eyes that didn't match." | | 3 | "His expression hadn't changed — still that controlled stillness that made him impossible to read — but something in his posture had." | | 4 | "He walked past her into the flat, and she caught the scent of him — cedar and something darker beneath it, something that didn't quite have a name." | | 5 | "His cane shifted to his right hand, the ivory handle catching the gray London light that filtered through the window." | | 6 | "His fingers were warm, and his thumb traced a line across her knuckles that made her breath stutter." | | 7 | "His mouth met hers, and he made a sound against her lips — something low, something that had been held back for too long." |
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| 97.22% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 18 | | uselessAdditionCount | 1 | | matches | | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 11 | | fancyCount | 2 | | fancyTags | | 0 | "Rory muttered (mutter)" | | 1 | "His forehead pressed (press)" |
| | dialogueSentences | 56 | | tagDensity | 0.196 | | leniency | 0.393 | | rawRatio | 0.182 | | effectiveRatio | 0.071 | |