| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 16 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 32 | | tagDensity | 0.5 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 78.17% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1145 | | totalAiIsmAdverbs | 5 | | found | | | highlights | | 0 | "suddenly" | | 1 | "slowly" | | 2 | "really" | | 3 | "tightly" |
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| 100.00% | AI-ism character names | Target: 0 AI-default names (17 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 65.07% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1145 | | totalAiIsms | 8 | | found | | | highlights | | 0 | "scanning" | | 1 | "database" | | 2 | "pounding" | | 3 | "loomed" | | 4 | "stomach" | | 5 | "structure" | | 6 | "searing" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "heart pounded in chest" | | count | 1 |
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| | highlights | | 0 | "heart hammered in her chest" |
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| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 1 | | narrationSentences | 68 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 68 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 84 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 54 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 3 | | markdownWords | 7 | | totalWords | 1146 | | ratio | 0.006 | | matches | | 0 | "Really bad, not cool, augh." | | 1 | "begging" | | 2 | "Pleasunged" |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 11 | | unquotedAttributions | 0 | | matches | (empty) | |
| 90.12% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 20 | | wordCount | 668 | | uniqueNames | 8 | | maxNameDensity | 1.2 | | worstName | "Aurora" | | maxWindowNameDensity | 2 | | worstWindowName | "Aurora" | | discoveredNames | | Aurora | 8 | | Timberland | 1 | | Silas | 2 | | Brick | 1 | | Lane | 1 | | Eva | 1 | | London | 1 | | Lucien | 5 |
| | persons | | 0 | "Aurora" | | 1 | "Silas" | | 2 | "Eva" | | 3 | "Lucien" |
| | places | | | globalScore | 0.901 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 57 | | glossingSentenceCount | 1 | | matches | | 0 | "as if trying to read her thoughts" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.873 | | wordCount | 1146 | | matches | | 0 | "not glamorous, but it pays the bills" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 84 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 34 | | mean | 33.71 | | std | 17.68 | | cv | 0.525 | | sampleLengths | | 0 | 4 | | 1 | 50 | | 2 | 59 | | 3 | 37 | | 4 | 39 | | 5 | 56 | | 6 | 22 | | 7 | 21 | | 8 | 50 | | 9 | 25 | | 10 | 45 | | 11 | 43 | | 12 | 27 | | 13 | 9 | | 14 | 28 | | 15 | 2 | | 16 | 80 | | 17 | 28 | | 18 | 26 | | 19 | 28 | | 20 | 14 | | 21 | 45 | | 22 | 26 | | 23 | 43 | | 24 | 46 | | 25 | 31 | | 26 | 38 | | 27 | 15 | | 28 | 22 | | 29 | 69 | | 30 | 22 | | 31 | 38 | | 32 | 10 | | 33 | 48 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 68 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 117 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 84 | | ratio | 0 | | matches | (empty) | |
| 99.53% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 666 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 27 | | adverbRatio | 0.04054054054054054 | | lyAdverbCount | 11 | | lyAdverbRatio | 0.016516516516516516 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 84 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 84 | | mean | 13.64 | | std | 8.95 | | cv | 0.656 | | sampleLengths | | 0 | 4 | | 1 | 16 | | 2 | 20 | | 3 | 14 | | 4 | 10 | | 5 | 28 | | 6 | 21 | | 7 | 15 | | 8 | 22 | | 9 | 20 | | 10 | 19 | | 11 | 24 | | 12 | 32 | | 13 | 5 | | 14 | 17 | | 15 | 21 | | 16 | 35 | | 17 | 15 | | 18 | 25 | | 19 | 9 | | 20 | 9 | | 21 | 3 | | 22 | 12 | | 23 | 5 | | 24 | 7 | | 25 | 18 | | 26 | 10 | | 27 | 11 | | 28 | 4 | | 29 | 7 | | 30 | 9 | | 31 | 11 | | 32 | 9 | | 33 | 6 | | 34 | 2 | | 35 | 9 | | 36 | 11 | | 37 | 2 | | 38 | 16 | | 39 | 11 | | 40 | 13 | | 41 | 25 | | 42 | 15 | | 43 | 7 | | 44 | 15 | | 45 | 6 | | 46 | 18 | | 47 | 3 | | 48 | 5 | | 49 | 3 |
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| 95.24% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 0 | | diversityRatio | 0.5714285714285714 | | totalSentences | 84 | | uniqueOpeners | 48 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 5 | | totalSentences | 65 | | matches | | 0 | "Still, better to be careful." | | 1 | "Suddenly, the door slammed shut" | | 2 | "Slowly, she turned to face" | | 3 | "*Really bad, not cool, augh.*" | | 4 | "Then, with a feral grin," |
| | ratio | 0.077 | |
| 66.15% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 25 | | totalSentences | 65 | | matches | | 0 | "His rheumy eyes surveyed Aurora," | | 1 | "She unfurled herself from her" | | 2 | "She shook his hand off" | | 3 | "He looked into the distance" | | 4 | "He waved towards the glass" | | 5 | "He gestured to a dark" | | 6 | "She went to the doorway" | | 7 | "She reached the top and" | | 8 | "She shook her head, a" | | 9 | "She spun around, her heart" | | 10 | "She'd know it anywhere, even" | | 11 | "He stepped into the light," | | 12 | "It had been the eye-color-gazing" | | 13 | "She could recall how his" | | 14 | "He gave her a sly" | | 15 | "She knew better than to" | | 16 | "She spat the last word," | | 17 | "He moved swiftly, faster than" | | 18 | "His face hovered just inches" | | 19 | "he growled, his voice a" |
| | ratio | 0.385 | |
| 98.46% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 47 | | totalSentences | 65 | | matches | | 0 | "The door swung open." | | 1 | "Silas froze, his jaw dropping" | | 2 | "His rheumy eyes surveyed Aurora," | | 3 | "Aurora squeezed past him, already" | | 4 | "She unfurled herself from her" | | 5 | "Silas pressed a napkin to" | | 6 | "She shook his hand off" | | 7 | "He looked into the distance" | | 8 | "He waved towards the glass" | | 9 | "He gestured to a dark" | | 10 | "She went to the doorway" | | 11 | "She reached the top and" | | 12 | "The door creaked open, revealing" | | 13 | "A tabby cat sauntered by," | | 14 | "Aurora stepped further into the" | | 15 | "Every surface was covered in" | | 16 | "She shook her head, a" | | 17 | "Some things never changed." | | 18 | "She spun around, her heart" | | 19 | "A dark figure loomed in" |
| | ratio | 0.723 | |
| 76.92% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 65 | | matches | | 0 | "Even with his injury, he" |
| | ratio | 0.015 | |
| 37.04% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 27 | | technicalSentenceCount | 4 | | matches | | 0 | "Aurora stepped further into the flat, her eyes adjusting to the dim light filtering through the grimy window." | | 1 | "It had been the eye-color-gazing that called her into his arms, the first time they had spoken and moved her closer to him, bwonding them." | | 2 | "Lucien's eyes searched hers, as if trying to read her thoughts." | | 3 | "In a flash, he was on her again, crashing her against the wall and detailed hands were on her, pulling her hard against the hardness of his body, his lips crash…" |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 16 | | uselessAdditionCount | 5 | | matches | | 0 | "Silas froze, his jaw dropping open like a taxi's passenger door" | | 1 | "She went, her steps squeaking at each riser" | | 2 | "he growled, his voice a low rumble in his chest" | | 3 | "he said, his voice low and dangerous" | | 4 | "she asked, her voice deadly calm" |
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| 87.50% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 5 | | fancyCount | 2 | | fancyTags | | 0 | "he growled (growl)" | | 1 | "she hissed (hiss)" |
| | dialogueSentences | 32 | | tagDensity | 0.156 | | leniency | 0.313 | | rawRatio | 0.4 | | effectiveRatio | 0.125 | |