| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 17 | | adverbTagCount | 1 | | adverbTags | | 0 | "She leaned back [back]" |
| | dialogueSentences | 38 | | tagDensity | 0.447 | | leniency | 0.895 | | rawRatio | 0.059 | | effectiveRatio | 0.053 | |
| 92.01% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1252 | | totalAiIsmAdverbs | 2 | | 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) | |
| 16.13% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1252 | | totalAiIsms | 21 | | found | | | highlights | | 0 | "scanned" | | 1 | "familiar" | | 2 | "warmth" | | 3 | "pounding" | | 4 | "tracing" | | 5 | "pang" | | 6 | "echoed" | | 7 | "weight" | | 8 | "sense of" | | 9 | "flicker" | | 10 | "ephemeral" | | 11 | "tension" | | 12 | "depths" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "weight of words/silence" | | count | 1 |
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| | highlights | | 0 | "the weight of the words" |
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| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 1 | | narrationSentences | 70 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 70 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 90 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 55 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1252 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 8 | | unquotedAttributions | 0 | | matches | (empty) | |
| 50.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 34 | | wordCount | 833 | | uniqueNames | 10 | | maxNameDensity | 1.56 | | worstName | "Silas" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Silas" | | discoveredNames | | Raven | 1 | | Nest | 1 | | London | 1 | | Palm | 1 | | Rory | 10 | | Silas | 13 | | Aurora | 4 | | Michael | 1 | | Channings | 1 | | Alto | 1 |
| | persons | | 0 | "Raven" | | 1 | "Rory" | | 2 | "Silas" | | 3 | "Aurora" | | 4 | "Michael" | | 5 | "Channings" |
| | places | | | globalScore | 0.72 | | windowScore | 0.5 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 60 | | glossingSentenceCount | 1 | | matches | | 0 | "appeared womanly in both body and bearing- threads of worry and weather had left their mark, yet retained a glacial allure that made his heart constrict" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.799 | | wordCount | 1252 | | matches | | 0 | "Not the glossy promise of \"-if onlys\" or \"what might-be's\" but this" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 90 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 16 | | mean | 78.25 | | std | 150.67 | | cv | 1.925 | | sampleLengths | | 0 | 58 | | 1 | 62 | | 2 | 8 | | 3 | 44 | | 4 | 73 | | 5 | 36 | | 6 | 26 | | 7 | 56 | | 8 | 27 | | 9 | 26 | | 10 | 30 | | 11 | 34 | | 12 | 17 | | 13 | 56 | | 14 | 41 | | 15 | 658 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 70 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 147 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 90 | | ratio | 0 | | matches | (empty) | |
| 85.67% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 408 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 23 | | adverbRatio | 0.056372549019607844 | | lyAdverbCount | 4 | | lyAdverbRatio | 0.00980392156862745 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 90 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 90 | | mean | 13.91 | | std | 8.58 | | cv | 0.617 | | sampleLengths | | 0 | 29 | | 1 | 29 | | 2 | 13 | | 3 | 10 | | 4 | 15 | | 5 | 24 | | 6 | 7 | | 7 | 1 | | 8 | 8 | | 9 | 13 | | 10 | 23 | | 11 | 11 | | 12 | 11 | | 13 | 23 | | 14 | 28 | | 15 | 24 | | 16 | 12 | | 17 | 11 | | 18 | 15 | | 19 | 8 | | 20 | 21 | | 21 | 2 | | 22 | 8 | | 23 | 17 | | 24 | 9 | | 25 | 18 | | 26 | 6 | | 27 | 20 | | 28 | 9 | | 29 | 21 | | 30 | 6 | | 31 | 14 | | 32 | 9 | | 33 | 5 | | 34 | 6 | | 35 | 11 | | 36 | 25 | | 37 | 20 | | 38 | 11 | | 39 | 41 | | 40 | 2 | | 41 | 12 | | 42 | 21 | | 43 | 1 | | 44 | 3 | | 45 | 10 | | 46 | 19 | | 47 | 18 | | 48 | 17 | | 49 | 55 |
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| 72.22% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 5 | | diversityRatio | 0.4666666666666667 | | totalSentences | 90 | | uniqueOpeners | 42 | |
| 49.75% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 67 | | matches | | 0 | "Too many damn years, Silas" |
| | ratio | 0.015 | |
| 70.75% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 25 | | totalSentences | 67 | | matches | | 0 | "It had been years since" | | 1 | "She scanned the dimly lit" | | 2 | "Her gaze landed on a" | | 3 | "His head jerked up, lock" | | 4 | "He looked older, the grey" | | 5 | "he murmured into her hair" | | 6 | "He gestured to the seat" | | 7 | "She sipped the amber liquid," | | 8 | "He raised his own glass" | | 9 | "She pushed the last of" | | 10 | "He paused, chewing on his" | | 11 | "She tapped her fingers on" | | 12 | "She smiled, just barely." | | 13 | "She was one foot out" | | 14 | "She hadn't meant to linger" | | 15 | "Their glasses clinked, a medley" | | 16 | "He reached out, his rough" | | 17 | "He drank deep, the whiskey" | | 18 | "She nodded, a sad smile" | | 19 | "She leaned back, tilting her" |
| | ratio | 0.373 | |
| 27.16% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 58 | | totalSentences | 67 | | matches | | 0 | "Rory found herself staring at" | | 1 | "It had been years since" | | 2 | "The scent of whiskey and" | | 3 | "Rory breathed it in deeply," | | 4 | "She scanned the dimly lit" | | 5 | "Her gaze landed on a" | | 6 | "A startled laugh burst from" | | 7 | "His head jerked up, lock" | | 8 | "A flash of surprise crossed" | | 9 | "The familiar husk of" | | 10 | "Rory moved to intercept him" | | 11 | "He looked older, the grey" | | 12 | "he murmured into her hair" | | 13 | "Rory stepped back, looking up" | | 14 | "Silas chuckled, the sound rumbling" | | 15 | "He gestured to the seat" | | 16 | "Aurora nodded, sliding onto the" | | 17 | "Silas poured her a generosity" | | 18 | "She sipped the amber liquid," | | 19 | "He raised his own glass" |
| | ratio | 0.866 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 67 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 33 | | technicalSentenceCount | 1 | | matches | | 0 | "But she appeared womanly, in both body and bearing- threads of worry and weather had left their mark, yet retained a glacial allure that made his heart constric…" |
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| 7.35% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 17 | | uselessAdditionCount | 4 | | matches | | 0 | "She pushed, fingers tracing the worn edge of the bar" | | 1 | "Silas tested, as if they were something rare" | | 2 | "Rory shrugged, the strain of autumn caught in her throat" | | 3 | "He drank, the whiskey burning a familiar trail down his throat" |
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| 71.05% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 5 | | fancyCount | 3 | | fancyTags | | 0 | "he murmured (murmur)" | | 1 | "Aurora laughed (laugh)" | | 2 | "Aurora described (describe)" |
| | dialogueSentences | 38 | | tagDensity | 0.132 | | leniency | 0.263 | | rawRatio | 0.6 | | effectiveRatio | 0.158 | |