| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 14 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 95 | | tagDensity | 0.147 | | leniency | 0.295 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 96.55% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1449 | | totalAiIsmAdverbs | 1 | | found | | | highlights | | |
| 80.00% | 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) | |
| 72.39% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1449 | | totalAiIsms | 8 | | found | | | highlights | | 0 | "familiar" | | 1 | "electric" | | 2 | "silence" | | 3 | "weight" | | 4 | "mechanical" | | 5 | "flickered" | | 6 | "shattered" |
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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 | 89 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 89 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 168 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 45 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1442 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 21 | | unquotedAttributions | 0 | | matches | (empty) | |
| 93.04% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 28 | | wordCount | 790 | | uniqueNames | 11 | | maxNameDensity | 1.14 | | worstName | "Silas" | | maxWindowNameDensity | 2 | | worstWindowName | "Maggie" | | discoveredNames | | Wednesday | 1 | | Raven | 1 | | Nest | 1 | | Chen | 1 | | Prague | 2 | | Maggie | 7 | | Swallowed | 1 | | One | 3 | | Set | 1 | | Rory | 1 | | Silas | 9 |
| | persons | | 0 | "Nest" | | 1 | "Chen" | | 2 | "Maggie" | | 3 | "Rory" | | 4 | "Silas" |
| | places | | | globalScore | 0.93 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 57 | | 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 | 1442 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 168 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 102 | | mean | 14.14 | | std | 16.26 | | cv | 1.15 | | sampleLengths | | 0 | 66 | | 1 | 34 | | 2 | 2 | | 3 | 4 | | 4 | 75 | | 5 | 1 | | 6 | 2 | | 7 | 58 | | 8 | 3 | | 9 | 1 | | 10 | 30 | | 11 | 5 | | 12 | 23 | | 13 | 7 | | 14 | 28 | | 15 | 2 | | 16 | 9 | | 17 | 24 | | 18 | 4 | | 19 | 15 | | 20 | 4 | | 21 | 11 | | 22 | 26 | | 23 | 19 | | 24 | 4 | | 25 | 3 | | 26 | 45 | | 27 | 2 | | 28 | 9 | | 29 | 9 | | 30 | 18 | | 31 | 17 | | 32 | 14 | | 33 | 6 | | 34 | 38 | | 35 | 2 | | 36 | 3 | | 37 | 2 | | 38 | 10 | | 39 | 1 | | 40 | 1 | | 41 | 21 | | 42 | 1 | | 43 | 48 | | 44 | 4 | | 45 | 5 | | 46 | 3 | | 47 | 67 | | 48 | 3 | | 49 | 15 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 89 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 144 | | matches | | |
| 40.82% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 6 | | semicolonCount | 0 | | flaggedSentences | 6 | | totalSentences | 168 | | ratio | 0.036 | | matches | | 0 | "He'd closed the bookshelf door to the back room hours ago—no meetings tonight, just the quiet rhythm of glassware and aged wood." | | 1 | "She wore the rain like she'd once worn danger—with a kind of reluctant grace." | | 2 | "She surveyed the room—the maps pinned to the walls, the black-and-white photographs of cities she might have recognized, the modest collection of bottles behind the bar." | | 3 | "\"Honestly?\" She looked at him—really looked, the way she used to when they'd been posted together, when reading each other had meant the difference between extraction and a body bag." | | 4 | "\"—and think about every decision that led me there?\"" | | 5 | "Her reflection warped across the curve of the tumbler—distorted, stretched, unrecognizable." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 696 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 20 | | adverbRatio | 0.028735632183908046 | | lyAdverbCount | 2 | | lyAdverbRatio | 0.0028735632183908046 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 168 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 168 | | mean | 8.58 | | std | 7.75 | | cv | 0.903 | | sampleLengths | | 0 | 18 | | 1 | 26 | | 2 | 22 | | 3 | 20 | | 4 | 4 | | 5 | 10 | | 6 | 2 | | 7 | 4 | | 8 | 6 | | 9 | 12 | | 10 | 23 | | 11 | 20 | | 12 | 14 | | 13 | 1 | | 14 | 2 | | 15 | 12 | | 16 | 26 | | 17 | 20 | | 18 | 3 | | 19 | 1 | | 20 | 10 | | 21 | 10 | | 22 | 10 | | 23 | 5 | | 24 | 4 | | 25 | 19 | | 26 | 7 | | 27 | 6 | | 28 | 18 | | 29 | 4 | | 30 | 2 | | 31 | 9 | | 32 | 17 | | 33 | 7 | | 34 | 4 | | 35 | 9 | | 36 | 6 | | 37 | 4 | | 38 | 9 | | 39 | 2 | | 40 | 13 | | 41 | 10 | | 42 | 3 | | 43 | 9 | | 44 | 10 | | 45 | 4 | | 46 | 3 | | 47 | 13 | | 48 | 32 | | 49 | 2 |
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| 48.02% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 11 | | diversityRatio | 0.3273809523809524 | | totalSentences | 168 | | uniqueOpeners | 55 | |
| 86.58% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 77 | | matches | | 0 | "Then the smile settled into" | | 1 | "Just for a moment." |
| | ratio | 0.026 | |
| 32.99% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 36 | | totalSentences | 77 | | matches | | 0 | "He'd closed the bookshelf door" | | 1 | "She was smaller than he" | | 2 | "Her hair had gone silver" | | 3 | "She wore the rain like" | | 4 | "She surveyed the room—the maps" | | 5 | "Her gaze lingered on his" | | 6 | "She smiled, and for half" | | 7 | "She draped her coat over" | | 8 | "She ignored the question." | | 9 | "She stared at it." | | 10 | "She wrapped her hands around" | | 11 | "She turned the glass a" | | 12 | "She lifted the glass to" | | 13 | "She looked away." | | 14 | "His signet ring clinked against" | | 15 | "She gestured at him, at" | | 16 | "He met her gaze." | | 17 | "She'd finished half her whiskey." | | 18 | "She exhaled through her nose." | | 19 | "Her voice cut through the" |
| | ratio | 0.468 | |
| 11.95% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 69 | | totalSentences | 77 | | matches | | 0 | "The Wednesday crowd at The" | | 1 | "Silas wiped down the mahogany" | | 2 | "He'd closed the bookshelf door" | | 3 | "The green neon sign outside" | | 4 | "The door swung open." | | 5 | "Silas didn't look up from" | | 6 | "The voice stopped his hand" | | 7 | "A woman stood in the" | | 8 | "She was smaller than he" | | 9 | "Her hair had gone silver" | | 10 | "She wore the rain like" | | 11 | "Margaret Chen stepped inside and" | | 12 | "She surveyed the room—the maps" | | 13 | "Her gaze lingered on his" | | 14 | "She smiled, and for half" | | 15 | "She draped her coat over" | | 16 | "She ignored the question." | | 17 | "The silence that followed had" | | 18 | "Silas poured two fingers of" | | 19 | "She stared at it." |
| | ratio | 0.896 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 77 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 34 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 14 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 3 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 95 | | tagDensity | 0.032 | | leniency | 0.063 | | rawRatio | 0 | | effectiveRatio | 0 | |