| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 23 | | adverbTagCount | 2 | | adverbTags | | 0 | "She looked around [around]" | | 1 | "Megan laughed softly [softly]" |
| | dialogueSentences | 39 | | tagDensity | 0.59 | | leniency | 1 | | rawRatio | 0.087 | | effectiveRatio | 0.087 | |
| 76.81% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1509 | | totalAiIsmAdverbs | 7 | | found | | | highlights | | 0 | "really" | | 1 | "slightly" | | 2 | "quickly" | | 3 | "softly" | | 4 | "very" |
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| 100.00% | AI-ism character names | Target: 0 AI-default names (16 tracked, −20% each) | | codexExemptions | | | found | (empty) | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 80.12% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1509 | | totalAiIsms | 6 | | found | | | highlights | | 0 | "sentinel" | | 1 | "footfall" | | 2 | "weight" | | 3 | "warmth" | | 4 | "traced" |
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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 | 91 | | matches | (empty) | |
| 17.27% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 7 | | hedgeCount | 1 | | narrationSentences | 91 | | filterMatches | | 0 | "watch" | | 1 | "look" | | 2 | "think" | | 3 | "know" |
| | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 106 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 48 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1521 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 24 | | unquotedAttributions | 0 | | matches | (empty) | |
| 50.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 59 | | wordCount | 1283 | | uniqueNames | 12 | | maxNameDensity | 1.79 | | worstName | "Rory" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Megan" | | discoveredNames | | Raven | 1 | | Nest | 1 | | Rory | 23 | | London | 1 | | Rees | 1 | | Megan | 20 | | Cardiff | 1 | | Silas | 5 | | Tuesday | 1 | | Yu-Fei | 1 | | Soho | 1 | | You | 3 |
| | persons | | 0 | "Raven" | | 1 | "Rory" | | 2 | "Rees" | | 3 | "Megan" | | 4 | "Silas" | | 5 | "Yu-Fei" | | 6 | "You" |
| | places | | 0 | "London" | | 1 | "Cardiff" | | 2 | "Soho" |
| | globalScore | 0.604 | | windowScore | 0.5 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 59 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 2.76% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 3 | | per1kWords | 1.972 | | wordCount | 1521 | | matches | | 0 | "neither present nor" | | 1 | "not to hide it but simply because she'd stopped thinking about it" | | 2 | "not the half-turned, careful glances they'd been trading, but full on, the way you looked at someone" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 2 | | totalSentences | 106 | | matches | | 0 | "thought that the" | | 1 | "hear that something" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 42 | | mean | 36.21 | | std | 28.96 | | cv | 0.8 | | sampleLengths | | 0 | 100 | | 1 | 73 | | 2 | 4 | | 3 | 60 | | 4 | 84 | | 5 | 11 | | 6 | 74 | | 7 | 3 | | 8 | 36 | | 9 | 73 | | 10 | 18 | | 11 | 5 | | 12 | 60 | | 13 | 7 | | 14 | 13 | | 15 | 54 | | 16 | 5 | | 17 | 48 | | 18 | 49 | | 19 | 12 | | 20 | 54 | | 21 | 3 | | 22 | 58 | | 23 | 23 | | 24 | 6 | | 25 | 46 | | 26 | 28 | | 27 | 18 | | 28 | 102 | | 29 | 9 | | 30 | 60 | | 31 | 31 | | 32 | 5 | | 33 | 6 | | 34 | 7 | | 35 | 43 | | 36 | 74 | | 37 | 6 | | 38 | 71 | | 39 | 28 | | 40 | 38 | | 41 | 16 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 91 | | matches | | |
| 11.32% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 6 | | totalVerbs | 212 | | matches | | 0 | "wasn't drinking" | | 1 | "wasn't looking" | | 2 | "was watching" | | 3 | "was shaking" | | 4 | "was taking" | | 5 | "was sitting" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 11 | | semicolonCount | 1 | | flaggedSentences | 11 | | totalSentences | 106 | | ratio | 0.104 | | matches | | 0 | "She wasn't drinking so much as occupying space — the difference, she'd come to understand, between needing a drink and needing somewhere to be." | | 1 | "She was watching the old maps on the far wall the way you watch television when you're not really watching — taking in the shapes without registering the meaning." | | 2 | "Now it was more animal than that — a shift in the air, a change in the quality of the room's attention." | | 3 | "She was shaking rain from an umbrella that had clearly lost the argument with the weather, and her coat — smart wool, the kind of coat you bought for a job interview and then just kept wearing — was dark at the shoulders." | | 4 | "In two seconds, Rory watched something move across Megan's face — surprise first, then a complicated pleasure, then something that flinched and recovered so quickly she might have imagined it." | | 5 | "She also meant something else by it, something that lived in the slight emphasis — the way well carried a question inside it." | | 6 | "You look well; I half expected otherwise." | | 7 | "She had new rings — one on her right hand, three on her left, a thin gold band among them that hadn't been there three years ago." | | 8 | "She thought about the version of herself that Megan still seemed to be addressing — the twenty-two-year-old who'd studied contract law and gone to the same four pubs on rotation and thought that the shape her life was taking was more or less fixed." | | 9 | "Megan turned to look at her properly — not the half-turned, careful glances they'd been trading, but full on, the way you looked at someone when you were done being careful." | | 10 | "Megan smiled at that — a real smile, the one that went up on the left side first." |
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| 90.60% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1281 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 65 | | adverbRatio | 0.0507416081186573 | | lyAdverbCount | 20 | | lyAdverbRatio | 0.0156128024980484 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 106 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 106 | | mean | 14.35 | | std | 12.16 | | cv | 0.848 | | sampleLengths | | 0 | 31 | | 1 | 45 | | 2 | 24 | | 3 | 21 | | 4 | 23 | | 5 | 29 | | 6 | 4 | | 7 | 6 | | 8 | 27 | | 9 | 22 | | 10 | 5 | | 11 | 21 | | 12 | 43 | | 13 | 20 | | 14 | 11 | | 15 | 2 | | 16 | 3 | | 17 | 13 | | 18 | 22 | | 19 | 34 | | 20 | 3 | | 21 | 6 | | 22 | 30 | | 23 | 18 | | 24 | 30 | | 25 | 4 | | 26 | 21 | | 27 | 18 | | 28 | 5 | | 29 | 4 | | 30 | 11 | | 31 | 40 | | 32 | 5 | | 33 | 6 | | 34 | 1 | | 35 | 6 | | 36 | 7 | | 37 | 29 | | 38 | 25 | | 39 | 5 | | 40 | 48 | | 41 | 5 | | 42 | 5 | | 43 | 23 | | 44 | 4 | | 45 | 5 | | 46 | 7 | | 47 | 4 | | 48 | 6 | | 49 | 2 |
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| 47.48% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 18 | | diversityRatio | 0.3867924528301887 | | totalSentences | 106 | | uniqueOpeners | 41 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 74 | | matches | (empty) | | ratio | 0 | |
| 47.03% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 32 | | totalSentences | 74 | | matches | | 0 | "She wasn't drinking so much" | | 1 | "She was watching the old" | | 2 | "She heard the door." | | 3 | "She'd stopped consciously cataloguing sounds" | | 4 | "She turned on her stool." | | 5 | "She was shaking rain from" | | 6 | "She looked up, and the" | | 7 | "She'd always been the kind" | | 8 | "She crossed the bar toward" | | 9 | "She smelled the same." | | 10 | "They separated and looked at" | | 11 | "She gestured vaguely at the" | | 12 | "She looked around at the" | | 13 | "His hazel eyes moved once" | | 14 | "he said to Megan" | | 15 | "She sat, and Rory sat" | | 16 | "She meant it, Rory thought." | | 17 | "She also meant something else" | | 18 | "You look well, considering." | | 19 | "You look well, after everything." |
| | ratio | 0.432 | |
| 27.57% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 64 | | totalSentences | 74 | | matches | | 0 | "The Raven's Nest was the" | | 1 | "Rory had been sitting at" | | 2 | "She wasn't drinking so much" | | 3 | "Silas was restocking the back" | | 4 | "The slight drag of his" | | 5 | "She was watching the old" | | 6 | "She heard the door." | | 7 | "She'd stopped consciously cataloguing sounds" | | 8 | "She turned on her stool." | | 9 | "The woman in the doorway" | | 10 | "She was shaking rain from" | | 11 | "She looked up, and the" | | 12 | "Rory recognised her in the" | | 13 | "A bit of weight in" | | 14 | "She'd always been the kind" | | 15 | "Megan saw her." | | 16 | "The pause lasted perhaps two" | | 17 | "Megan said it softly, the" | | 18 | "She crossed the bar toward" | | 19 | "She smelled the same." |
| | ratio | 0.865 | |
| 67.57% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 74 | | matches | | 0 | "Now it was more animal" |
| | ratio | 0.014 | |
| 23.81% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 42 | | technicalSentenceCount | 7 | | matches | | 0 | "Silas was restocking the back shelf, moving with the unhurried economy of someone who'd learned long ago not to waste motion." | | 1 | "The slight drag of his left leg was nearly imperceptible unless you knew to look for it, and Rory, who knew, wasn't looking." | | 2 | "She was shaking rain from an umbrella that had clearly lost the argument with the weather, and her coat — smart wool, the kind of coat you bought for a job inte…" | | 3 | "In two seconds, Rory watched something move across Megan's face — surprise first, then a complicated pleasure, then something that flinched and recovered so qui…" | | 4 | "She also meant something else by it, something that lived in the slight emphasis — the way well carried a question inside it." | | 5 | "She had new rings — one on her right hand, three on her left, a thin gold band among them that hadn't been there three years ago." | | 6 | "She thought about the version of herself that Megan still seemed to be addressing — the twenty-two-year-old who'd studied contract law and gone to the same four…" |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 23 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 15 | | fancyCount | 1 | | fancyTags | | 0 | "Megan laughed softly (laugh)" |
| | dialogueSentences | 39 | | tagDensity | 0.385 | | leniency | 0.769 | | rawRatio | 0.067 | | effectiveRatio | 0.051 | |