| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 19 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 50 | | tagDensity | 0.38 | | leniency | 0.76 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1137 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 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) | |
| 69.22% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1137 | | totalAiIsms | 7 | | found | | | highlights | | 0 | "familiar" | | 1 | "perfect" | | 2 | "could feel" | | 3 | "weight" | | 4 | "glinting" | | 5 | "flickered" | | 6 | "trembled" |
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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 her words" |
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| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 68 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 68 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 98 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 58 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1129 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 15 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 18 | | wordCount | 699 | | uniqueNames | 11 | | maxNameDensity | 0.57 | | worstName | "Eva" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Silas" | | discoveredNames | | Cardiff | 1 | | Golden | 1 | | Empress | 1 | | Perfect | 1 | | Eva | 4 | | Mercer | 1 | | Consultant | 1 | | London | 1 | | Raven | 2 | | Nest | 2 | | Silas | 3 |
| | persons | | 0 | "Eva" | | 1 | "Mercer" | | 2 | "Raven" | | 3 | "Nest" | | 4 | "Silas" |
| | places | | | globalScore | 1 | | windowScore | 1 | |
| 45.83% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 48 | | glossingSentenceCount | 2 | | matches | | 0 | "sounded like a gunshot" | | 1 | "appeared in front of me" |
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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 | 1129 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 98 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 45 | | mean | 25.09 | | std | 21.76 | | cv | 0.867 | | sampleLengths | | 0 | 41 | | 1 | 5 | | 2 | 87 | | 3 | 17 | | 4 | 21 | | 5 | 34 | | 6 | 9 | | 7 | 46 | | 8 | 63 | | 9 | 10 | | 10 | 18 | | 11 | 12 | | 12 | 17 | | 13 | 2 | | 14 | 15 | | 15 | 45 | | 16 | 7 | | 17 | 36 | | 18 | 19 | | 19 | 52 | | 20 | 3 | | 21 | 85 | | 22 | 27 | | 23 | 6 | | 24 | 55 | | 25 | 17 | | 26 | 2 | | 27 | 45 | | 28 | 30 | | 29 | 14 | | 30 | 53 | | 31 | 7 | | 32 | 35 | | 33 | 4 | | 34 | 1 | | 35 | 1 | | 36 | 32 | | 37 | 34 | | 38 | 8 | | 39 | 2 | | 40 | 4 | | 41 | 20 | | 42 | 19 | | 43 | 55 | | 44 | 14 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 68 | | matches | (empty) | |
| 98.22% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 131 | | matches | | 0 | "was setting" | | 1 | "was digging" |
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| 55.39% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 4 | | semicolonCount | 0 | | flaggedSentences | 3 | | totalSentences | 98 | | ratio | 0.031 | | matches | | 0 | "And her eyes—those green eyes that had once sparkled with mischief—held a wariness that made my chest tighten." | | 1 | "I watched the whiskey disappear into the fabric, wondering if that was how time worked—just absorbing everything until nothing remained but stains." | | 2 | "\"Thirty-five will do that to you.\" She slid onto the stool beside me, close enough that I caught the scent of her perfume—something expensive, sandalwood and bergamot, nothing like the drugstore vanilla she used to wear." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 705 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 14 | | adverbRatio | 0.019858156028368795 | | lyAdverbCount | 0 | | lyAdverbRatio | 0 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 98 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 98 | | mean | 11.52 | | std | 9.49 | | cv | 0.824 | | sampleLengths | | 0 | 20 | | 1 | 21 | | 2 | 5 | | 3 | 11 | | 4 | 14 | | 5 | 23 | | 6 | 21 | | 7 | 18 | | 8 | 11 | | 9 | 6 | | 10 | 12 | | 11 | 9 | | 12 | 12 | | 13 | 22 | | 14 | 8 | | 15 | 1 | | 16 | 36 | | 17 | 10 | | 18 | 3 | | 19 | 3 | | 20 | 27 | | 21 | 6 | | 22 | 13 | | 23 | 6 | | 24 | 5 | | 25 | 5 | | 26 | 5 | | 27 | 14 | | 28 | 4 | | 29 | 10 | | 30 | 2 | | 31 | 6 | | 32 | 11 | | 33 | 2 | | 34 | 6 | | 35 | 9 | | 36 | 15 | | 37 | 30 | | 38 | 7 | | 39 | 7 | | 40 | 29 | | 41 | 6 | | 42 | 6 | | 43 | 7 | | 44 | 11 | | 45 | 41 | | 46 | 3 | | 47 | 27 | | 48 | 58 | | 49 | 10 |
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| 57.82% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 10 | | diversityRatio | 0.40816326530612246 | | totalSentences | 98 | | uniqueOpeners | 40 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 63 | | matches | | 0 | "Somewhere in the back room," | | 1 | "Somewhere in the distance, a" |
| | ratio | 0.032 | |
| 35.87% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 29 | | totalSentences | 63 | | matches | | 0 | "Her name tasted strange on" | | 1 | "She nodded toward the stage" | | 2 | "I watched the whiskey disappear" | | 3 | "I searched for the right" | | 4 | "She slid onto the stool" | | 5 | "I deserved it." | | 6 | "I'd told her" | | 7 | "I signalled for another drink." | | 8 | "She nodded at my Golden" | | 9 | "I pushed the fresh glass" | | 10 | "She hesitated, then took a" | | 11 | "Her laugh was brittle" | | 12 | "I watched the bassist's fingers" | | 13 | "She swirled her drink" | | 14 | "I rubbed it through my" | | 15 | "She set her glass down" | | 16 | "She leaned in, her voice" | | 17 | "I could feel the weight" | | 18 | "She shook her head" | | 19 | "She reached into her bag," |
| | ratio | 0.46 | |
| 47.30% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 52 | | totalSentences | 63 | | matches | | 0 | "The glass slipped from my" | | 1 | "The ice cubes skittered across" | | 2 | "The voice was deeper than" | | 3 | "Eva's once-vibrant red hair had" | | 4 | "The freckles I used to" | | 5 | "Her name tasted strange on" | | 6 | "She nodded toward the stage" | | 7 | "The bartender appeared with a" | | 8 | "I watched the whiskey disappear" | | 9 | "I searched for the right" | | 10 | "She slid onto the stool" | | 11 | "The jab landed." | | 12 | "I deserved it." | | 13 | "The last time we'd spoken," | | 14 | "I'd told her" | | 15 | "I signalled for another drink." | | 16 | "She nodded at my Golden" | | 17 | "I pushed the fresh glass" | | 18 | "She hesitated, then took a" | | 19 | "Her laugh was brittle" |
| | ratio | 0.825 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 63 | | matches | (empty) | | ratio | 0 | |
| 60.44% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 26 | | technicalSentenceCount | 3 | | matches | | 0 | "Eva's once-vibrant red hair had dulled to a muted auburn, pulled back in a severe bun that did nothing for her sharp cheekbones." | | 1 | "I could feel the weight of her words pressing against my ribs, making it hard to breathe." | | 2 | "I sat there, staring at the business card, at the neat, professional font that bore no resemblance to the wild, passionate girl I'd known." |
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| 98.68% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 19 | | uselessAdditionCount | 1 | | matches | | 0 | "She leaned in, her voice dropping" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 3 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 50 | | tagDensity | 0.06 | | leniency | 0.12 | | rawRatio | 0 | | effectiveRatio | 0 | |