| 0.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 2 | | adverbTagCount | 1 | | adverbTags | | 0 | "she said softly [softly]" |
| | dialogueSentences | 8 | | tagDensity | 0.25 | | leniency | 0.5 | | rawRatio | 0.5 | | effectiveRatio | 0.25 | |
| 80.87% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 784 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | 0 | "softly" | | 1 | "slightly" | | 2 | "very" |
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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) | |
| 10.71% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 784 | | totalAiIsms | 14 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | word | "down her spine" | | count | 1 |
| | 7 | | | 8 | | | 9 | | | 10 | | | 11 | |
| | highlights | | 0 | "flickered" | | 1 | "familiar" | | 2 | "scanned" | | 3 | "footsteps" | | 4 | "echoes" | | 5 | "grave" | | 6 | "down her spine" | | 7 | "weight" | | 8 | "unspoken" | | 9 | "silence" | | 10 | "traced" | | 11 | "resolve" |
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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 unspoken words" |
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| 53.57% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 3 | | narrationSentences | 35 | | matches | | 0 | "g in surprise" | | 1 | "a twinge of sadness" | | 2 | "felt a twinge" |
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| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 35 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 41 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 47 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 787 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 2 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 15 | | wordCount | 636 | | uniqueNames | 4 | | maxNameDensity | 0.94 | | worstName | "Silas" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Silas" | | discoveredNames | | Aurora | 2 | | Carter | 2 | | Silas | 6 | | Rory | 5 |
| | persons | | 0 | "Aurora" | | 1 | "Carter" | | 2 | "Silas" | | 3 | "Rory" |
| | places | (empty) | | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 30 | | 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 | 787 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 41 | | matches | (empty) | |
| 33.81% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 17 | | mean | 46.29 | | std | 12.42 | | cv | 0.268 | | sampleLengths | | 0 | 59 | | 1 | 44 | | 2 | 58 | | 3 | 46 | | 4 | 32 | | 5 | 43 | | 6 | 30 | | 7 | 23 | | 8 | 41 | | 9 | 42 | | 10 | 50 | | 11 | 44 | | 12 | 64 | | 13 | 55 | | 14 | 74 | | 15 | 44 | | 16 | 38 |
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| 95.24% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 35 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 105 | | matches | (empty) | |
| 3.48% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 3 | | semicolonCount | 0 | | flaggedSentences | 2 | | totalSentences | 41 | | ratio | 0.049 | | matches | | 0 | "But the idea of facing them - facing him - sent a shudder of fear down her spine." | | 1 | "As she tucked the key into her pocket and stood, resolve straightening her spine, Rory felt a twinge of sadness for the girl she used to be - the girl who had laughed with carefree abandon, who had faced the world with a defiant tilt of her chin." |
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| 92.22% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 571 | | adjectiveStacks | 1 | | stackExamples | | 0 | "small crescent-shaped scar" |
| | adverbCount | 24 | | adverbRatio | 0.04203152364273205 | | lyAdverbCount | 9 | | lyAdverbRatio | 0.01576182136602452 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 41 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 41 | | mean | 19.2 | | std | 11.1 | | cv | 0.578 | | sampleLengths | | 0 | 27 | | 1 | 32 | | 2 | 40 | | 3 | 3 | | 4 | 1 | | 5 | 23 | | 6 | 29 | | 7 | 6 | | 8 | 20 | | 9 | 26 | | 10 | 18 | | 11 | 14 | | 12 | 15 | | 13 | 18 | | 14 | 10 | | 15 | 9 | | 16 | 21 | | 17 | 7 | | 18 | 16 | | 19 | 15 | | 20 | 26 | | 21 | 5 | | 22 | 19 | | 23 | 18 | | 24 | 13 | | 25 | 10 | | 26 | 11 | | 27 | 16 | | 28 | 44 | | 29 | 32 | | 30 | 32 | | 31 | 17 | | 32 | 16 | | 33 | 4 | | 34 | 18 | | 35 | 48 | | 36 | 26 | | 37 | 17 | | 38 | 21 | | 39 | 6 | | 40 | 38 |
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| 86.18% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 3 | | diversityRatio | 0.5609756097560976 | | totalSentences | 41 | | uniqueOpeners | 23 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 4 | | totalSentences | 34 | | matches | | 0 | "Abruptly, Silas stood, wincing slightly" | | 1 | "Of course, the injury that" | | 2 | "Perhaps Silas was right." | | 3 | "Perhaps it was finally time" |
| | ratio | 0.118 | |
| 67.06% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 13 | | totalSentences | 34 | | matches | | 0 | "She scanned the room, taking" | | 1 | "Her breath hitched." | | 2 | "she said softly, the nickname" | | 3 | "He turned to face her," | | 4 | "She shrugged, dropping her gaze" | | 5 | "It had always been hard" | | 6 | "He chuckled, the sound low" | | 7 | "She knew he was right," | | 8 | "It seemed time had left" | | 9 | "He fished a key out" | | 10 | "She traced it with her" | | 11 | "She was long gone now," | | 12 | "It was worth a try," |
| | ratio | 0.382 | |
| 100.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 19 | | totalSentences | 34 | | matches | | 0 | "The distinctive green neon sign" | | 1 | "The familiar scents of aged" | | 2 | "She scanned the room, taking" | | 3 | "Her breath hitched." | | 4 | "Rory wove through the scattered" | | 5 | "she said softly, the nickname" | | 6 | "He turned to face her," | | 7 | "She shrugged, dropping her gaze" | | 8 | "It had always been hard" | | 9 | "He chuckled, the sound low" | | 10 | "A wry smile tugged at" | | 11 | "Silas signaled the bartender for" | | 12 | "Rory nodded, her throat tight." | | 13 | "She knew he was right," | | 14 | "It seemed time had left" | | 15 | "He fished a key out" | | 16 | "She traced it with her" | | 17 | "She was long gone now," | | 18 | "It was worth a try," |
| | ratio | 0.559 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 34 | | matches | (empty) | | ratio | 0 | |
| 28.57% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 25 | | technicalSentenceCount | 4 | | matches | | 0 | "Up close, she noticed the strands of silver threading through his hair, echoes of the neatly trimmed beard that failed to fully hide the deep lines bracketing h…" | | 1 | "Silas signaled the bartender for another drink before turning back to her, his expression sobering." | | 2 | "As she tucked the key into her pocket and stood, resolve straightening her spine, Rory felt a twinge of sadness for the girl she used to be - the girl who had l…" | | 3 | "Or at least to a version of herself that could look in the mirror without flinching away from her own reflection." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 2 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 25.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 2 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 8 | | tagDensity | 0.25 | | leniency | 0.5 | | rawRatio | 0.5 | | effectiveRatio | 0.25 | |