| 86.79% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 21 | | adverbTagCount | 3 | | adverbTags | | 0 | "Eva gestured vaguely [vaguely]" | | 1 | "Eva said finally [finally]" | | 2 | "Eva said quietly [quietly]" |
| | dialogueSentences | 53 | | tagDensity | 0.396 | | leniency | 0.792 | | rawRatio | 0.143 | | effectiveRatio | 0.113 | |
| 85.48% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1377 | | totalAiIsmAdverbs | 4 | | found | | | highlights | | 0 | "slightly" | | 1 | "suddenly" | | 2 | "carefully" |
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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) | |
| 63.69% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1377 | | totalAiIsms | 10 | | found | | | highlights | | 0 | "warmth" | | 1 | "weight" | | 2 | "flickered" | | 3 | "electric" | | 4 | "traced" | | 5 | "silence" | | 6 | "methodical" | | 7 | "trembled" |
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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 | 85 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 1 | | narrationSentences | 85 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 117 | | 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 | 1361 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 18 | | unquotedAttributions | 0 | | matches | (empty) | |
| 5.77% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 72 | | wordCount | 936 | | uniqueNames | 15 | | maxNameDensity | 2.88 | | worstName | "Rory" | | maxWindowNameDensity | 4.5 | | worstWindowName | "Rory" | | discoveredNames | | Rory | 27 | | Raven | 1 | | Nest | 1 | | Silas | 7 | | Volvo | 2 | | Morrison | 2 | | London | 2 | | Eva | 21 | | Prague | 1 | | Despite | 1 | | Unlike | 1 | | Edinburgh | 1 | | Golden | 1 | | Empress | 1 | | Didn | 3 |
| | persons | | 0 | "Rory" | | 1 | "Raven" | | 2 | "Silas" | | 3 | "Morrison" | | 4 | "Eva" |
| | places | | 0 | "London" | | 1 | "Prague" | | 2 | "Edinburgh" | | 3 | "Golden" |
| | globalScore | 0.058 | | windowScore | 0.167 | |
| 63.79% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 58 | | glossingSentenceCount | 2 | | matches | | 0 | "quite reach her eyes" | | 1 | "quite regret it" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1361 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 117 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 53 | | mean | 25.68 | | std | 19.32 | | cv | 0.752 | | sampleLengths | | 0 | 58 | | 1 | 16 | | 2 | 40 | | 3 | 20 | | 4 | 12 | | 5 | 51 | | 6 | 61 | | 7 | 35 | | 8 | 36 | | 9 | 5 | | 10 | 23 | | 11 | 32 | | 12 | 35 | | 13 | 2 | | 14 | 14 | | 15 | 54 | | 16 | 48 | | 17 | 9 | | 18 | 28 | | 19 | 1 | | 20 | 23 | | 21 | 19 | | 22 | 30 | | 23 | 6 | | 24 | 19 | | 25 | 14 | | 26 | 15 | | 27 | 55 | | 28 | 12 | | 29 | 52 | | 30 | 2 | | 31 | 60 | | 32 | 10 | | 33 | 1 | | 34 | 4 | | 35 | 3 | | 36 | 50 | | 37 | 24 | | 38 | 43 | | 39 | 3 | | 40 | 58 | | 41 | 16 | | 42 | 5 | | 43 | 34 | | 44 | 1 | | 45 | 17 | | 46 | 27 | | 47 | 38 | | 48 | 22 | | 49 | 7 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 85 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 166 | | matches | | 0 | "were probably cataloging" | | 1 | "was staring" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 14 | | semicolonCount | 0 | | flaggedSentences | 8 | | totalSentences | 117 | | ratio | 0.068 | | matches | | 0 | "Not loud—barely more than a breath—but it hit her like cold water." | | 1 | "She wore a charcoal suit that probably cost more than Rory made in a month, and her fingers—ringless, Rory noticed, though that might mean nothing—curved around a tumbler of something amber." | | 2 | "Silas placed a steaming mug in front of Rory—chamomile with honey, the way she liked it—and retreated to the far end of the bar." | | 3 | "Above their heads, one of Silas's old maps—Prague, Rory had noticed months ago—curled slightly at the edges." | | 4 | "Silas moved to serve them, his slight limp more pronounced than usual—the weather always made his knee ache." | | 5 | "Not forgiveness—not yet, maybe not ever—but understanding." | | 6 | "Rory checked her phone—one more delivery, across town." | | 7 | "Anything but the gulf between who they'd been—two girls sharing secrets in the back of a Volvo—and who they'd become." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 874 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 32 | | adverbRatio | 0.036613272311212815 | | lyAdverbCount | 8 | | lyAdverbRatio | 0.009153318077803204 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 117 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 117 | | mean | 11.63 | | std | 9.31 | | cv | 0.8 | | sampleLengths | | 0 | 18 | | 1 | 18 | | 2 | 22 | | 3 | 14 | | 4 | 2 | | 5 | 24 | | 6 | 16 | | 7 | 17 | | 8 | 3 | | 9 | 12 | | 10 | 11 | | 11 | 12 | | 12 | 4 | | 13 | 24 | | 14 | 30 | | 15 | 31 | | 16 | 2 | | 17 | 10 | | 18 | 5 | | 19 | 18 | | 20 | 21 | | 21 | 1 | | 22 | 2 | | 23 | 12 | | 24 | 5 | | 25 | 11 | | 26 | 12 | | 27 | 9 | | 28 | 17 | | 29 | 6 | | 30 | 13 | | 31 | 22 | | 32 | 2 | | 33 | 7 | | 34 | 7 | | 35 | 4 | | 36 | 6 | | 37 | 13 | | 38 | 31 | | 39 | 24 | | 40 | 19 | | 41 | 5 | | 42 | 7 | | 43 | 2 | | 44 | 9 | | 45 | 14 | | 46 | 5 | | 47 | 1 | | 48 | 23 | | 49 | 16 |
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| 76.35% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 9 | | diversityRatio | 0.5042735042735043 | | totalSentences | 117 | | uniqueOpeners | 59 | |
| 88.89% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 75 | | matches | | 0 | "Then it smoothed into a" | | 1 | "Just in different directions." |
| | ratio | 0.027 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 16 | | totalSentences | 75 | | matches | | 0 | "She'd made four deliveries in" | | 1 | "She peeled off her jacket" | | 2 | "She was halfway onto a" | | 3 | "She knew that laugh." | | 4 | "She wore a charcoal suit" | | 5 | "His former-spymaster instincts were probably" | | 6 | "She traced the small crescent" | | 7 | "She trailed off, took a" | | 8 | "He pulled out the ledger" | | 9 | "She didn't mean it kindly," | | 10 | "She felt her jaw tighten." | | 11 | "She looked down at her" | | 12 | "She looked up, and her" | | 13 | "They'd both been running." | | 14 | "She should go." | | 15 | "They talked, carefully at first," |
| | ratio | 0.213 | |
| 100.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 54 | | totalSentences | 75 | | matches | | 0 | "The rain had followed Rory" | | 1 | "She'd made four deliveries in" | | 2 | "The green neon glow from" | | 3 | "Silas looked up from polishing" | | 4 | "She peeled off her jacket" | | 5 | "Silas set down the glass" | | 6 | "She was halfway onto a" | | 7 | "She knew that laugh." | | 8 | "The woman sat three stools" | | 9 | "She wore a charcoal suit" | | 10 | "Eva fucking Morrison, who'd begged" | | 11 | "Eva must have felt the" | | 12 | "Silas glanced between them, his" | | 13 | "His former-spymaster instincts were probably" | | 14 | "Rory's voice came out steadier" | | 15 | "She traced the small crescent" | | 16 | "Eva gestured vaguely with her" | | 17 | "She trailed off, took a" | | 18 | "Eva's laugh had a sharp" | | 19 | "Silas placed a steaming mug" |
| | ratio | 0.72 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 75 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 32 | | technicalSentenceCount | 1 | | matches | | 0 | "The front door opened, bringing in a gust of wet wind and two laughing women who made their way to a corner table." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 21 | | uselessAdditionCount | 1 | | matches | | 0 | "She looked up, and her eyes were bright with unshed tears" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 6 | | fancyCount | 1 | | fancyTags | | 0 | "Rory repeated (repeat)" |
| | dialogueSentences | 53 | | tagDensity | 0.113 | | leniency | 0.226 | | rawRatio | 0.167 | | effectiveRatio | 0.038 | |