| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 1 | | adverbTagCount | 1 | | adverbTags | | 0 | "He looked entirely [entirely]" |
| | dialogueSentences | 40 | | tagDensity | 0.025 | | leniency | 0.05 | | rawRatio | 1 | | effectiveRatio | 0.05 | |
| 85.71% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1050 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | 0 | "perfectly" | | 1 | "very" | | 2 | "suddenly" |
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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) | |
| 14.29% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1050 | | totalAiIsms | 18 | | found | | | highlights | | 0 | "chaotic" | | 1 | "warmth" | | 2 | "familiar" | | 3 | "reminder" | | 4 | "weight" | | 5 | "vibrated" | | 6 | "resolve" | | 7 | "tension" | | 8 | "rhythmic" | | 9 | "grave" | | 10 | "intensity" | | 11 | "velvet" | | 12 | "magnetic" | | 13 | "gleaming" | | 14 | "echoed" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 0 | | maxInWindow | 0 | | found | (empty) | | highlights | (empty) | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 49 | | matches | (empty) | |
| 84.55% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 2 | | narrationSentences | 49 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 89 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 34 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1050 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 5 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 10 | | wordCount | 606 | | uniqueNames | 6 | | maxNameDensity | 0.5 | | worstName | "Lucien" | | maxWindowNameDensity | 1 | | worstWindowName | "Lucien" | | discoveredNames | | Golden | 1 | | Empress | 1 | | Avaros | 1 | | London | 1 | | Lucien | 3 | | Aurora | 3 |
| | persons | | 0 | "Avaros" | | 1 | "Lucien" | | 2 | "Aurora" |
| | places | | | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 43 | | 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 | 1050 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 89 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 58 | | mean | 18.1 | | std | 14.88 | | cv | 0.822 | | sampleLengths | | 0 | 16 | | 1 | 10 | | 2 | 57 | | 3 | 8 | | 4 | 53 | | 5 | 2 | | 6 | 2 | | 7 | 29 | | 8 | 7 | | 9 | 16 | | 10 | 44 | | 11 | 17 | | 12 | 35 | | 13 | 10 | | 14 | 24 | | 15 | 3 | | 16 | 4 | | 17 | 53 | | 18 | 12 | | 19 | 4 | | 20 | 6 | | 21 | 29 | | 22 | 27 | | 23 | 2 | | 24 | 10 | | 25 | 49 | | 26 | 5 | | 27 | 12 | | 28 | 6 | | 29 | 12 | | 30 | 34 | | 31 | 27 | | 32 | 3 | | 33 | 15 | | 34 | 14 | | 35 | 4 | | 36 | 7 | | 37 | 33 | | 38 | 17 | | 39 | 7 | | 40 | 34 | | 41 | 14 | | 42 | 14 | | 43 | 4 | | 44 | 21 | | 45 | 17 | | 46 | 19 | | 47 | 20 | | 48 | 10 | | 49 | 30 |
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| 98.10% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 49 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 90 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 89 | | ratio | 0 | | matches | (empty) | |
| 90.20% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 451 | | adjectiveStacks | 1 | | stackExamples | | 0 | "single, half-empty takeout" |
| | adverbCount | 20 | | adverbRatio | 0.04434589800443459 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.011086474501108648 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 89 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 89 | | mean | 11.8 | | std | 6.92 | | cv | 0.587 | | sampleLengths | | 0 | 16 | | 1 | 10 | | 2 | 7 | | 3 | 17 | | 4 | 10 | | 5 | 23 | | 6 | 8 | | 7 | 5 | | 8 | 22 | | 9 | 26 | | 10 | 2 | | 11 | 2 | | 12 | 10 | | 13 | 19 | | 14 | 7 | | 15 | 16 | | 16 | 12 | | 17 | 19 | | 18 | 13 | | 19 | 17 | | 20 | 12 | | 21 | 10 | | 22 | 3 | | 23 | 10 | | 24 | 10 | | 25 | 24 | | 26 | 3 | | 27 | 4 | | 28 | 5 | | 29 | 11 | | 30 | 16 | | 31 | 21 | | 32 | 12 | | 33 | 4 | | 34 | 6 | | 35 | 10 | | 36 | 6 | | 37 | 13 | | 38 | 27 | | 39 | 2 | | 40 | 10 | | 41 | 13 | | 42 | 20 | | 43 | 16 | | 44 | 5 | | 45 | 12 | | 46 | 6 | | 47 | 12 | | 48 | 9 | | 49 | 18 |
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| 40.45% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 9 | | diversityRatio | 0.30337078651685395 | | totalSentences | 89 | | uniqueOpeners | 27 | |
| 69.44% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 48 | | matches | | 0 | "Instead, he used the head" |
| | ratio | 0.021 | |
| 0.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 28 | | totalSentences | 48 | | matches | | 0 | "He stepped past the threshold," | | 1 | "He paused, his gaze sweeping" | | 2 | "He turned back to her." | | 3 | "He looked entirely out of" | | 4 | "He leaned on his cane," | | 5 | "His platinum blond hair remained" | | 6 | "He moved closer, invading her" | | 7 | "He smelled of expensive cologne" | | 8 | "He reached out, his long" | | 9 | "He didn't touch her, but" | | 10 | "She stared back, her bright" | | 11 | "He grasped her left wrist," | | 12 | "He pulled her arm up," | | 13 | "He pulled her closer, forcing" | | 14 | "His voice dropped to a" | | 15 | "He tilted his head, his" | | 16 | "He released her wrist, but" | | 17 | "He stepped back, giving her" | | 18 | "He began to pace the" | | 19 | "He stopped abruptly at the" |
| | ratio | 0.583 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 47 | | totalSentences | 48 | | matches | | 0 | "The door swung open to" | | 1 | "The man didn't wait for" | | 2 | "He stepped past the threshold," | | 3 | "He paused, his gaze sweeping" | | 4 | "Books lay in higgledy-piggledy piles" | | 5 | "He turned back to her." | | 6 | "The hallway light caught the" | | 7 | "He looked entirely out of" | | 8 | "He leaned on his cane," | | 9 | "His platinum blond hair remained" | | 10 | "Lucien smiled, a thin, dangerous" | | 11 | "He moved closer, invading her" | | 12 | "He smelled of expensive cologne" | | 13 | "He reached out, his long" | | 14 | "He didn't touch her, but" | | 15 | "Aurora didn't flinch." | | 16 | "She stared back, her bright" | | 17 | "Lucien finally closed the gap." | | 18 | "He grasped her left wrist," | | 19 | "He pulled her arm up," |
| | ratio | 0.979 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 48 | | matches | (empty) | | ratio | 0 | |
| 77.92% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 33 | | technicalSentenceCount | 3 | | matches | | 0 | "Lucien smiled, a thin, dangerous expression that didn't reach his mismatched eyes." | | 1 | "The touch sent a jolt of electricity through her, a familiar, jagged heat that tasted of old regrets and midnight mistakes." | | 2 | "The atmosphere in the room shifted, growing heavy and thick, as if the oxygen had been replaced by liquid lead." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 1 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |