| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 16 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 37 | | tagDensity | 0.432 | | leniency | 0.865 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 926 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 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) | |
| 2.81% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 926 | | totalAiIsms | 18 | | found | | | highlights | | 0 | "scanning" | | 1 | "tension" | | 2 | "pounding" | | 3 | "silence" | | 4 | "racing" | | 5 | "whisper" | | 6 | "electric" | | 7 | "reminder" | | 8 | "resolve" | | 9 | "wavered" | | 10 | "unwavering" | | 11 | "weight" | | 12 | "loomed" | | 13 | "sense of" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 46 | | matches | (empty) | |
| 80.75% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 2 | | narrationSentences | 46 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 67 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 50 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 924 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 22 | | unquotedAttributions | 0 | | matches | (empty) | |
| 10.59% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 32 | | wordCount | 538 | | uniqueNames | 6 | | maxNameDensity | 2.79 | | worstName | "Lucien" | | maxWindowNameDensity | 4 | | worstWindowName | "Aurora" | | discoveredNames | | Moreau | 1 | | Eva | 1 | | Ptolemy | 1 | | Aurora | 13 | | Lucien | 15 | | Avaros | 1 |
| | persons | | 0 | "Moreau" | | 1 | "Eva" | | 2 | "Ptolemy" | | 3 | "Aurora" | | 4 | "Lucien" | | 5 | "Avaros" |
| | places | (empty) | | globalScore | 0.106 | | windowScore | 0.333 | |
| 0.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 34 | | glossingSentenceCount | 3 | | matches | | 0 | "as if sensing the tension, and darted behind the sofa" | | 1 | "quite match his usual cool demeanor" | | 2 | "seemed untouchable a fixer who could handle anything" |
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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 | 924 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 67 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 30 | | mean | 30.8 | | std | 15.78 | | cv | 0.512 | | sampleLengths | | 0 | 39 | | 1 | 15 | | 2 | 43 | | 3 | 17 | | 4 | 12 | | 5 | 26 | | 6 | 29 | | 7 | 37 | | 8 | 9 | | 9 | 32 | | 10 | 56 | | 11 | 20 | | 12 | 36 | | 13 | 18 | | 14 | 19 | | 15 | 28 | | 16 | 48 | | 17 | 31 | | 18 | 33 | | 19 | 40 | | 20 | 26 | | 21 | 66 | | 22 | 47 | | 23 | 16 | | 24 | 6 | | 25 | 32 | | 26 | 14 | | 27 | 45 | | 28 | 16 | | 29 | 68 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 46 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 103 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 67 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 540 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 16 | | adverbRatio | 0.02962962962962963 | | lyAdverbCount | 3 | | lyAdverbRatio | 0.005555555555555556 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 67 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 67 | | mean | 13.79 | | std | 7.96 | | cv | 0.577 | | sampleLengths | | 0 | 8 | | 1 | 15 | | 2 | 16 | | 3 | 10 | | 4 | 5 | | 5 | 28 | | 6 | 15 | | 7 | 12 | | 8 | 5 | | 9 | 3 | | 10 | 9 | | 11 | 11 | | 12 | 12 | | 13 | 3 | | 14 | 8 | | 15 | 21 | | 16 | 11 | | 17 | 26 | | 18 | 3 | | 19 | 6 | | 20 | 17 | | 21 | 15 | | 22 | 23 | | 23 | 18 | | 24 | 15 | | 25 | 10 | | 26 | 10 | | 27 | 11 | | 28 | 25 | | 29 | 7 | | 30 | 11 | | 31 | 11 | | 32 | 8 | | 33 | 9 | | 34 | 19 | | 35 | 12 | | 36 | 15 | | 37 | 21 | | 38 | 8 | | 39 | 23 | | 40 | 7 | | 41 | 26 | | 42 | 3 | | 43 | 18 | | 44 | 19 | | 45 | 14 | | 46 | 12 | | 47 | 16 | | 48 | 50 | | 49 | 8 |
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| 63.68% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 4 | | diversityRatio | 0.417910447761194 | | totalSentences | 67 | | uniqueOpeners | 28 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 46 | | matches | (empty) | | ratio | 0 | |
| 89.57% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 15 | | totalSentences | 46 | | matches | | 0 | "His tailored charcoal suit was" | | 1 | "He leaned on his ivory-handled" | | 2 | "he said, his voice low" | | 3 | "He closed the door behind" | | 4 | "She had seen the danger" | | 5 | "he said, his voice barely" | | 6 | "He had been a mysterious" | | 7 | "she said, her voice sharp" | | 8 | "She couldn't deny the pull" | | 9 | "she said, her voice trembling" | | 10 | "She knew the risks, but" | | 11 | "she said, her voice firm" | | 12 | "She knew the road ahead" | | 13 | "She had faced worse before," | | 14 | "she said, moving towards the" |
| | ratio | 0.326 | |
| 3.48% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 42 | | totalSentences | 46 | | matches | | 0 | "The door creaked open, and" | | 1 | "Lucien Moreau, standing in the" | | 2 | "The tabby cat, Ptolemy, meowed" | | 3 | "Aurora said, her voice steady" | | 4 | "His tailored charcoal suit was" | | 5 | "He leaned on his ivory-handled" | | 6 | "he said, his voice low" | | 7 | "Aurora's eyes narrowed." | | 8 | "Lucien replied, stepping into the" | | 9 | "He closed the door behind" | | 10 | "Aurora asked, her mind racing" | | 11 | "She had seen the danger" | | 12 | "he said, his voice barely" | | 13 | "Aurora's jaw tightened." | | 14 | "Lucien said, his eyes locking" | | 15 | "Aurora's thoughts flashed back to" | | 16 | "He had been a mysterious" | | 17 | "she said, her voice sharp" | | 18 | "Lucien replied, his tone defensive" | | 19 | "Aurora crossed her arms, her" |
| | ratio | 0.913 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 46 | | matches | | 0 | "Now, standing in her flat," |
| | ratio | 0.022 | |
| 12.99% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 22 | | technicalSentenceCount | 4 | | matches | | 0 | "His tailored charcoal suit was as impeccably pressed as ever, but there was a tension in his stance, a wariness that didn't quite match his usual cool demeanor." | | 1 | "She had seen the danger in the supernatural world, but Lucien had always seemed untouchable, a fixer who could handle anything." | | 2 | "He had been a mysterious figure, a man who seemed to know everything and yet revealed so little." | | 3 | "Lucien followed her, his presence a constant reminder of the bond they shared, and the danger that loomed over them." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 16 | | uselessAdditionCount | 13 | | matches | | 0 | "Aurora said, her voice steady but her heart pounding" | | 1 | "he said, his voice low and urgent" | | 2 | "Aurora asked, her mind racing" | | 3 | "he said, his voice barely more than a whisper" | | 4 | "Lucien said, his eyes locking onto hers" | | 5 | "she said, her voice sharp" | | 6 | "Lucien replied, his tone defensive" | | 7 | "Aurora said, her voice dripping with sarcasm" | | 8 | "Lucien said, his voice low" | | 9 | "she said, her voice trembling" | | 10 | "she said, her voice firm" | | 11 | "Lucien said, his eyes hopeful" | | 12 | "Aurora said, her gaze unwavering" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 16 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 37 | | tagDensity | 0.432 | | leniency | 0.865 | | rawRatio | 0 | | effectiveRatio | 0 | |