| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 14 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 27 | | tagDensity | 0.519 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 89.82% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 491 | | totalAiIsmAdverbs | 1 | | found | | | highlights | | |
| 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) | |
| 59.27% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 491 | | totalAiIsms | 4 | | found | | | highlights | | 0 | "echoed" | | 1 | "unreadable" | | 2 | "flickered" | | 3 | "throbbed" |
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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 | 33 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 33 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 45 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 29 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 486 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 7 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 10 | | wordCount | 294 | | uniqueNames | 8 | | maxNameDensity | 0.68 | | worstName | "Carter" | | maxWindowNameDensity | 1 | | worstWindowName | "Carter" | | discoveredNames | | Raven | 1 | | Nest | 1 | | Soho | 1 | | Carter | 2 | | Rory | 1 | | Laila | 1 | | Silas | 2 | | Blackwood | 1 |
| | persons | | 0 | "Raven" | | 1 | "Nest" | | 2 | "Carter" | | 3 | "Rory" | | 4 | "Laila" | | 5 | "Silas" | | 6 | "Blackwood" |
| | places | | | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 28 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 486 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 45 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 14 | | mean | 34.71 | | std | 17.54 | | cv | 0.505 | | sampleLengths | | 0 | 80 | | 1 | 19 | | 2 | 18 | | 3 | 35 | | 4 | 32 | | 5 | 32 | | 6 | 35 | | 7 | 34 | | 8 | 34 | | 9 | 36 | | 10 | 23 | | 11 | 16 | | 12 | 24 | | 13 | 68 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 33 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 54 | | matches | (empty) | |
| 15.87% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 3 | | semicolonCount | 0 | | flaggedSentences | 2 | | totalSentences | 45 | | ratio | 0.044 | | matches | | 0 | "Aurora Carter—Rory, Laila, Carter—leaned against the bar, her black hair slicked back, the crescent scar on her wrist catching the light." | | 1 | "Evan’s face flashed in her mind—a ghost she’d thought she’d buried." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 299 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 6 | | adverbRatio | 0.020066889632107024 | | lyAdverbCount | 3 | | lyAdverbRatio | 0.010033444816053512 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 45 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 45 | | mean | 10.8 | | std | 5.44 | | cv | 0.504 | | sampleLengths | | 0 | 17 | | 1 | 21 | | 2 | 28 | | 3 | 14 | | 4 | 14 | | 5 | 5 | | 6 | 3 | | 7 | 10 | | 8 | 5 | | 9 | 12 | | 10 | 18 | | 11 | 5 | | 12 | 14 | | 13 | 12 | | 14 | 6 | | 15 | 6 | | 16 | 20 | | 17 | 6 | | 18 | 9 | | 19 | 17 | | 20 | 9 | | 21 | 12 | | 22 | 13 | | 23 | 9 | | 24 | 8 | | 25 | 16 | | 26 | 10 | | 27 | 8 | | 28 | 22 | | 29 | 6 | | 30 | 3 | | 31 | 13 | | 32 | 7 | | 33 | 5 | | 34 | 11 | | 35 | 16 | | 36 | 8 | | 37 | 12 | | 38 | 8 | | 39 | 10 | | 40 | 7 | | 41 | 11 | | 42 | 3 | | 43 | 8 | | 44 | 9 |
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| 92.59% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 0 | | diversityRatio | 0.5555555555555556 | | totalSentences | 45 | | uniqueOpeners | 25 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 33 | | matches | (empty) | | ratio | 0 | |
| 0.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 25 | | totalSentences | 33 | | matches | | 0 | "She watched Silas Blackwood slide" | | 1 | "His limp was a ghost" | | 2 | "she said, her voice low," | | 3 | "He didn’t smile." | | 4 | "His voice was gravel, thick" | | 5 | "she countered, sliding a glass" | | 6 | "She gestured at the worn" | | 7 | "he murmured, his gaze drifting" | | 8 | "He tapped the signet ring" | | 9 | "Her fingers tightened around the" | | 10 | "She met his eyes, the" | | 11 | "he echoed, the words tasting" | | 12 | "He leaned closer, his voice" | | 13 | "she snapped, the scar on" | | 14 | "She pushed the watch toward" | | 15 | "He caught her wrist, his" | | 16 | "His hazel eyes held hers," | | 17 | "She yanked her wrist free," | | 18 | "She turned, her back to" | | 19 | "He slid a folded note" |
| | ratio | 0.758 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 32 | | totalSentences | 33 | | matches | | 0 | "The Raven’s Nest’s green neon" | | 1 | "Aurora Carter—Rory, Laila, Carter—leaned against" | | 2 | "She watched Silas Blackwood slide" | | 3 | "His limp was a ghost" | | 4 | "she said, her voice low," | | 5 | "He didn’t smile." | | 6 | "His voice was gravel, thick" | | 7 | "she countered, sliding a glass" | | 8 | "She gestured at the worn" | | 9 | "he murmured, his gaze drifting" | | 10 | "He tapped the signet ring" | | 11 | "Her fingers tightened around the" | | 12 | "She met his eyes, the" | | 13 | "he echoed, the words tasting" | | 14 | "He leaned closer, his voice" | | 15 | "she snapped, the scar on" | | 16 | "She pushed the watch toward" | | 17 | "He caught her wrist, his" | | 18 | "His hazel eyes held hers," | | 19 | "She yanked her wrist free," |
| | ratio | 0.97 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 33 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 7 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 14 | | uselessAdditionCount | 5 | | matches | | 0 | "she said, her voice low, eyes sharp" | | 1 | "he murmured, his gaze drifting to the bookshelf behind the bar" | | 2 | "he echoed, the words tasting bitter" | | 3 | "He leaned, his voice dropping" | | 4 | "His hazel eyes held, unreadable" |
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| 75.93% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 3 | | fancyCount | 2 | | fancyTags | | 0 | "he murmured (murmur)" | | 1 | "she snapped (snap)" |
| | dialogueSentences | 27 | | tagDensity | 0.111 | | leniency | 0.222 | | rawRatio | 0.667 | | effectiveRatio | 0.148 | |