| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 11 | | adverbTagCount | 1 | | adverbTags | | | dialogueSentences | 0 | | tagDensity | 1 | | leniency | 1 | | rawRatio | 0.091 | | effectiveRatio | 0.091 | |
| 85.91% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1774 | | totalAiIsmAdverbs | 5 | | found | | | highlights | | 0 | "suddenly" | | 1 | "completely" | | 2 | "slowly" | | 3 | "precisely" |
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| 60.00% | AI-ism character names | Target: 0 AI-default names (16 tracked, −20% each) | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 77.45% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1774 | | totalAiIsms | 8 | | found | | 0 | | word | "practiced ease" | | count | 1 |
| | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | |
| | highlights | | 0 | "practiced ease" | | 1 | "lilt" | | 2 | "calculated" | | 3 | "perfect" | | 4 | "silk" | | 5 | "flickered" | | 6 | "tracing" | | 7 | "weight" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "hung in the air" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 101 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 1 | | narrationSentences | 101 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 149 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 51 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1751 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 14 | | unquotedAttributions | 0 | | matches | (empty) | |
| 75.12% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 85 | | wordCount | 1202 | | uniqueNames | 37 | | maxNameDensity | 1.5 | | worstName | "Aurora" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Aurora" | | discoveredNames | | London | 3 | | Raven | 1 | | Nest | 1 | | Silas | 5 | | Tube | 1 | | Cardiff | 3 | | Aurora | 18 | | Hughes | 2 | | Sunday | 1 | | Vivi | 11 | | Kensington | 1 | | Italy | 1 | | Lake | 1 | | Como | 1 | | Clifford | 2 | | Chance | 2 | | Evan | 2 | | Eva | 2 | | Have | 1 | | National | 1 | | Tate | 1 | | Last | 1 | | Rory | 1 | | Carter | 2 | | Empress | 1 | | Soho | 1 | | Lord | 1 | | Henderson | 1 | | Chinese | 1 | | Manchester | 1 | | Barrister | 1 | | Law | 1 | | Lincoln | 1 | | Inn | 1 | | Fields | 1 | | You | 6 | | Could | 3 |
| | persons | | 0 | "Raven" | | 1 | "Silas" | | 2 | "Aurora" | | 3 | "Hughes" | | 4 | "Vivi" | | 5 | "Clifford" | | 6 | "Chance" | | 7 | "Evan" | | 8 | "Eva" | | 9 | "Have" | | 10 | "Tate" | | 11 | "Rory" | | 12 | "Carter" | | 13 | "Lord" | | 14 | "Henderson" | | 15 | "Law" | | 16 | "Lincoln" | | 17 | "You" | | 18 | "Could" |
| | places | | 0 | "London" | | 1 | "Cardiff" | | 2 | "Kensington" | | 3 | "Italy" | | 4 | "Lake" | | 5 | "Como" | | 6 | "National" | | 7 | "Last" | | 8 | "Soho" | | 9 | "Manchester" |
| | globalScore | 0.751 | | windowScore | 0.833 | |
| 38.06% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 67 | | glossingSentenceCount | 3 | | matches | | 0 | "looked like it had never known the inside" | | 1 | "seemed perfect until he wasn't" | | 2 | "felt like she was drowning in expectati" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.571 | | wordCount | 1751 | | matches | | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 2 | | totalSentences | 149 | | matches | | 0 | "taken that training" | | 1 | "realised that love" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 47 | | mean | 37.26 | | std | 27.53 | | cv | 0.739 | | sampleLengths | | 0 | 92 | | 1 | 80 | | 2 | 11 | | 3 | 1 | | 4 | 93 | | 5 | 21 | | 6 | 4 | | 7 | 19 | | 8 | 70 | | 9 | 61 | | 10 | 15 | | 11 | 2 | | 12 | 65 | | 13 | 48 | | 14 | 2 | | 15 | 16 | | 16 | 87 | | 17 | 9 | | 18 | 52 | | 19 | 3 | | 20 | 37 | | 21 | 47 | | 22 | 23 | | 23 | 22 | | 24 | 41 | | 25 | 9 | | 26 | 91 | | 27 | 87 | | 28 | 30 | | 29 | 48 | | 30 | 29 | | 31 | 30 | | 32 | 26 | | 33 | 66 | | 34 | 42 | | 35 | 73 | | 36 | 33 | | 37 | 14 | | 38 | 58 | | 39 | 25 | | 40 | 5 | | 41 | 43 | | 42 | 42 | | 43 | 14 | | 44 | 2 | | 45 | 28 | | 46 | 35 |
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| 87.89% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 5 | | totalSentences | 101 | | matches | | 0 | "being noticed" | | 1 | "been carved" | | 2 | "been meant" | | 3 | "was aimed" | | 4 | "being asked" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 212 | | matches | | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 12 | | semicolonCount | 0 | | flaggedSentences | 11 | | totalSentences | 149 | | ratio | 0.074 | | matches | | 0 | "She nodded at Silas behind the bar—he acknowledged her with a slight raise of his glass—and made her way to the corner table she'd claimed as her own over the past three years." | | 1 | "The voice was the same—rounded vowels, that particular Cardiff lilt that turned certain words into questions." | | 2 | "Vivi had been the one person who understood why Aurora had chosen Cardiff in the first place—close enough to home for Sunday dinners with her parents, far enough to feel like her own life." | | 3 | "A diamond caught the light on her left hand—large enough to cast its own shadow." | | 4 | "The wedding's next autumn—we're thinking Italy." | | 5 | "No one called her Rory anymore—except Silas, sometimes, and only when they were alone." | | 6 | "You had everything mapped out—pupillage, tenancy, silk eventually." | | 7 | "Aurora thought of her father's voice on the telephone, the last time they'd spoken—his disappointment a physical thing, pressing against her ear like a hand." | | 8 | "Did you—was there someone?" | | 9 | "Vivi's expression flickered—hurt, perhaps, or something closer to recognition." | | 10 | "I just—I miss you, sometimes." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 128 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 5 | | adverbRatio | 0.0390625 | | lyAdverbCount | 2 | | lyAdverbRatio | 0.015625 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 149 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 149 | | mean | 11.75 | | std | 10.3 | | cv | 0.876 | | sampleLengths | | 0 | 26 | | 1 | 33 | | 2 | 33 | | 3 | 39 | | 4 | 41 | | 5 | 11 | | 6 | 1 | | 7 | 16 | | 8 | 12 | | 9 | 2 | | 10 | 1 | | 11 | 28 | | 12 | 34 | | 13 | 15 | | 14 | 6 | | 15 | 3 | | 16 | 1 | | 17 | 2 | | 18 | 15 | | 19 | 2 | | 20 | 10 | | 21 | 7 | | 22 | 19 | | 23 | 19 | | 24 | 15 | | 25 | 29 | | 26 | 10 | | 27 | 9 | | 28 | 6 | | 29 | 7 | | 30 | 10 | | 31 | 5 | | 32 | 2 | | 33 | 3 | | 34 | 6 | | 35 | 2 | | 36 | 24 | | 37 | 4 | | 38 | 6 | | 39 | 12 | | 40 | 8 | | 41 | 6 | | 42 | 42 | | 43 | 2 | | 44 | 11 | | 45 | 3 | | 46 | 2 | | 47 | 5 | | 48 | 12 | | 49 | 29 |
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| 63.31% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 9 | | diversityRatio | 0.4161073825503356 | | totalSentences | 149 | | uniqueOpeners | 62 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 88 | | matches | | 0 | "Only my mother still calls" | | 1 | "Instead, she said:" | | 2 | "Just Carter, most days, a" |
| | ratio | 0.034 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 23 | | totalSentences | 88 | | matches | | 0 | "She nodded at Silas behind" | | 1 | "She'd barely settled into the" | | 2 | "They'd shared a flat in" | | 3 | "Her hair, once a wild" | | 4 | "We're in Kensington, near the" | | 5 | "You'll have to come round" | | 6 | "I assumed you'd be a" | | 7 | "You clerked for Lord Henderson." | | 8 | "You had your pick of" | | 9 | "You had everything mapped out—pupillage," | | 10 | "She thought of Evan's smile" | | 11 | "She thought of Eva, gone" | | 12 | "It was my father's dream," | | 13 | "You remember how he" | | 14 | "You didn't even say goodbye." | | 15 | "She sat back, the distance" | | 16 | "I have my life here." | | 17 | "She reached into her handbag" | | 18 | "Her fingers lingered on it" | | 19 | "I just—I miss you, sometimes." |
| | ratio | 0.261 | |
| 100.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 62 | | totalSentences | 88 | | matches | | 0 | "The rain had been falling" | | 1 | "Aurora pushed through the door" | | 2 | "She nodded at Silas behind" | | 3 | "She'd barely settled into the" | | 4 | "The woman paused just inside" | | 5 | "Aurora shrank back against the" | | 6 | "The voice was the same—rounded" | | 7 | "They'd shared a flat in" | | 8 | "Vivi had been the one" | | 9 | "Aurora hadn't moved." | | 10 | "The roundness that had softened" | | 11 | "Her hair, once a wild" | | 12 | "A diamond caught the light" | | 13 | "We're in Kensington, near the" | | 14 | "You'll have to come round" | | 15 | "The words landed like small" | | 16 | "Aurora watched the ripples spread." | | 17 | "The wedding's next autumn—we're thinking" | | 18 | "Marcus wants Lake Como, but" | | 19 | "The last I heard, you'd" |
| | ratio | 0.705 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 88 | | matches | | 0 | "Before Aurora could answer, Vivi" | | 1 | "To the rest of the" |
| | ratio | 0.023 | |
| 23.81% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 42 | | technicalSentenceCount | 7 | | matches | | 0 | "The woman paused just inside the entrance, shaking water from an umbrella that looked like it had never known the inside of a Tube station, and her gaze swept t…" | | 1 | "They'd shared a flat in second year, stayed up until dawn dissecting constitutional law, planned their future careers in chambers that smelled of old books and …" | | 2 | "Vivi had been the one person who understood why Aurora had chosen Cardiff in the first place—close enough to home for Sunday dinners with her parents, far enoug…" | | 3 | "The roundness that had softened Vivi's face at twenty-one had been carved away, replaced by cheekbones that looked architectural." | | 4 | "Aurora's hands rested on the table, and she was suddenly conscious of the delivery ink stains on her fingers, the chipped nail polish, the small crescent scar o…" | | 5 | "Beneath the polish and the diamonds, Aurora caught a glimpse of the woman who'd once cried in their shared kitchen because she'd gotten a first instead of a dis…" | | 6 | "Aurora watched her cross the room, watched Silas's eyes follow Vivi's retreat with the careful attention of a man who'd spent decades reading exits." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 11 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 1 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 0 | | tagDensity | 1 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |