| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 15 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 38 | | tagDensity | 0.395 | | leniency | 0.789 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 58.25% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 958 | | totalAiIsmAdverbs | 8 | | found | | 0 | | | 1 | | adverb | "deliberately" | | count | 2 |
| | 2 | | | 3 | | | 4 | |
| | highlights | | 0 | "slightly" | | 1 | "deliberately" | | 2 | "very" | | 3 | "precisely" | | 4 | "completely" |
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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) | |
| 73.90% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 958 | | totalAiIsms | 5 | | found | | | highlights | | 0 | "familiar" | | 1 | "stomach" | | 2 | "absolutely" | | 3 | "measured" | | 4 | "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 | 64 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 64 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 86 | | 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 | 962 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 15 | | unquotedAttributions | 0 | | matches | (empty) | |
| 83.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 32 | | wordCount | 768 | | uniqueNames | 11 | | maxNameDensity | 1.17 | | worstName | "Lucien" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Lucien" | | discoveredNames | | Rory | 8 | | Eva | 4 | | Moreau | 2 | | Ptolemy | 3 | | Lucien | 9 | | London | 1 | | English | 1 | | Marseille | 1 | | Brick | 1 | | Lane | 1 | | Whitechapel | 1 |
| | persons | | 0 | "Rory" | | 1 | "Eva" | | 2 | "Moreau" | | 3 | "Ptolemy" | | 4 | "Lucien" |
| | places | | 0 | "London" | | 1 | "English" | | 2 | "Marseille" | | 3 | "Brick" | | 4 | "Lane" | | 5 | "Whitechapel" |
| | globalScore | 0.914 | | windowScore | 0.833 | |
| 87.50% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 40 | | 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 | 962 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 86 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 42 | | mean | 22.9 | | std | 24.31 | | cv | 1.061 | | sampleLengths | | 0 | 16 | | 1 | 4 | | 2 | 85 | | 3 | 7 | | 4 | 3 | | 5 | 6 | | 6 | 15 | | 7 | 1 | | 8 | 57 | | 9 | 6 | | 10 | 50 | | 11 | 63 | | 12 | 6 | | 13 | 2 | | 14 | 6 | | 15 | 29 | | 16 | 7 | | 17 | 7 | | 18 | 15 | | 19 | 19 | | 20 | 73 | | 21 | 6 | | 22 | 5 | | 23 | 7 | | 24 | 65 | | 25 | 23 | | 26 | 1 | | 27 | 5 | | 28 | 2 | | 29 | 31 | | 30 | 26 | | 31 | 26 | | 32 | 55 | | 33 | 41 | | 34 | 45 | | 35 | 6 | | 36 | 87 | | 37 | 9 | | 38 | 4 | | 39 | 14 | | 40 | 22 | | 41 | 5 |
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| 94.30% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 64 | | matches | | 0 | "been told" | | 1 | "was concerned" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 139 | | matches | | 0 | "was staying" | | 1 | "was forming" |
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| 9.97% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 5 | | semicolonCount | 0 | | flaggedSentences | 4 | | totalSentences | 86 | | ratio | 0.047 | | matches | | 0 | "His mismatched eyes — one amber, warm as candlelight, the other black as a stopped clock — moved over her face with an unhurried patience that made her stomach clench." | | 1 | "Lucien came in, and she caught the scent of rain and something underneath it — cedar, smoke, the faint mineral sharpness that was simply him and had no name she'd ever found." | | 2 | "Something shifted in his face — not softening, exactly." | | 3 | "It was a picture of a woman she didn't recognise, standing outside a building she did — a small, undistinguished office front in Whitechapel she'd passed on her delivery route." |
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| 79.22% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 765 | | adjectiveStacks | 1 | | stackExamples | | 0 | "small crescent-shaped scar." |
| | adverbCount | 40 | | adverbRatio | 0.05228758169934641 | | lyAdverbCount | 19 | | lyAdverbRatio | 0.02483660130718954 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 86 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 86 | | mean | 11.19 | | std | 9.65 | | cv | 0.863 | | sampleLengths | | 0 | 16 | | 1 | 4 | | 2 | 31 | | 3 | 5 | | 4 | 19 | | 5 | 30 | | 6 | 5 | | 7 | 2 | | 8 | 3 | | 9 | 6 | | 10 | 11 | | 11 | 4 | | 12 | 1 | | 13 | 21 | | 14 | 6 | | 15 | 6 | | 16 | 24 | | 17 | 6 | | 18 | 3 | | 19 | 15 | | 20 | 32 | | 21 | 17 | | 22 | 7 | | 23 | 14 | | 24 | 14 | | 25 | 11 | | 26 | 6 | | 27 | 2 | | 28 | 6 | | 29 | 23 | | 30 | 6 | | 31 | 4 | | 32 | 3 | | 33 | 7 | | 34 | 9 | | 35 | 6 | | 36 | 15 | | 37 | 4 | | 38 | 21 | | 39 | 6 | | 40 | 40 | | 41 | 3 | | 42 | 3 | | 43 | 4 | | 44 | 2 | | 45 | 5 | | 46 | 7 | | 47 | 2 | | 48 | 26 | | 49 | 3 |
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| 70.16% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 8 | | diversityRatio | 0.47674418604651164 | | totalSentences | 86 | | uniqueOpeners | 41 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 57 | | matches | (empty) | | ratio | 0 | |
| 23.51% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 28 | | totalSentences | 57 | | matches | | 0 | "It was not Eva." | | 1 | "His mismatched eyes — one" | | 2 | "He tilted his head slightly" | | 3 | "She stepped back." | | 4 | "It wasn't an invitation so" | | 5 | "She closed the door and" | | 6 | "He set his cane against" | | 7 | "She pressed her knuckles briefly" | | 8 | "He turned to face her" | | 9 | "She stopped herself from laughing," | | 10 | "She'd been in London seven" | | 11 | "She had successfully, deliberately, kept" | | 12 | "She'd done well." | | 13 | "She'd been cautious." | | 14 | "He always remained standing when" | | 15 | "She spread her hands" | | 16 | "It was more like a" | | 17 | "She stood back up, because" | | 18 | "He said her name the" | | 19 | "She could hear it against" |
| | ratio | 0.491 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 55 | | totalSentences | 57 | | matches | | 0 | "The third deadbolt gave its" | | 1 | "It was not Eva." | | 2 | "Lucien Moreau stood in the" | | 3 | "Water beaded on his shoulders." | | 4 | "A single dark strand had" | | 5 | "His mismatched eyes — one" | | 6 | "Rory gripped the door" | | 7 | "He tilted his head slightly" | | 8 | "Ptolemy chose that moment to" | | 9 | "Lucien looked down at the" | | 10 | "The cat looked up at" | | 11 | "Some silent, irritating negotiation seemed" | | 12 | "Rory said, to the cat" | | 13 | "She stepped back." | | 14 | "It wasn't an invitation so" | | 15 | "Lucien came in, and she" | | 16 | "She closed the door and" | | 17 | "Books stacked three deep on" | | 18 | "Eva's research notes fanned across" | | 19 | "Scrolls she couldn't read tucked" |
| | ratio | 0.965 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 57 | | matches | (empty) | | ratio | 0 | |
| 28.57% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 25 | | technicalSentenceCount | 4 | | matches | | 0 | "Lucien Moreau stood in the narrow hallway with one hand resting on the ivory handle of his cane, his charcoal suit immaculate despite the rain that had clearly …" | | 1 | "His mismatched eyes — one amber, warm as candlelight, the other black as a stopped clock — moved over her face with an unhurried patience that made her stomach …" | | 2 | "Some silent, irritating negotiation seemed to occur, and Ptolemy walked directly over his foot and into the hall as though personally escorting him inside." | | 3 | "Lucien came in, and she caught the scent of rain and something underneath it — cedar, smoke, the faint mineral sharpness that was simply him and had no name she…" |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 15 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 9 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 38 | | tagDensity | 0.237 | | leniency | 0.474 | | rawRatio | 0.111 | | effectiveRatio | 0.053 | |