| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 15 | | adverbTagCount | 1 | | adverbTags | | 0 | "Lucien corrected softly [softly]" |
| | dialogueSentences | 42 | | tagDensity | 0.357 | | leniency | 0.714 | | rawRatio | 0.067 | | effectiveRatio | 0.048 | |
| 74.85% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1193 | | totalAiIsmAdverbs | 6 | | found | | | highlights | | 0 | "slightly" | | 1 | "precisely" | | 2 | "lightly" | | 3 | "softly" | | 4 | "very" | | 5 | "slowly" |
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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) | |
| 53.90% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1193 | | totalAiIsms | 11 | | found | | 0 | | | 1 | | | 2 | | | 3 | | word | "practiced ease" | | count | 1 |
| | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | |
| | highlights | | 0 | "glinting" | | 1 | "tracing" | | 2 | "simmering" | | 3 | "practiced ease" | | 4 | "echoed" | | 5 | "velvet" | | 6 | "warmth" | | 7 | "chill" | | 8 | "pulse" | | 9 | "electric" | | 10 | "porcelain" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "knuckles turned white" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 48 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 48 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 75 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 46 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 1 | | markdownWords | 1 | | totalWords | 1193 | | ratio | 0.001 | | matches | | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 11 | | unquotedAttributions | 0 | | matches | (empty) | |
| 87.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 21 | | wordCount | 722 | | uniqueNames | 10 | | maxNameDensity | 1.25 | | worstName | "Lucien" | | maxWindowNameDensity | 2 | | worstWindowName | "Lucien" | | discoveredNames | | Brick | 1 | | Lane | 1 | | Moreau | 1 | | Lucien | 9 | | Aurora | 4 | | Earl | 1 | | Grey | 1 | | Latin | 1 | | Persian | 1 | | French | 1 |
| | persons | | 0 | "Moreau" | | 1 | "Lucien" | | 2 | "Aurora" | | 3 | "Earl" | | 4 | "Grey" |
| | places | | | globalScore | 0.877 | | windowScore | 1 | |
| 91.86% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 43 | | glossingSentenceCount | 1 | | matches | | 0 | "felt like a furnace against the autumn" |
| |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1193 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 75 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 39 | | mean | 30.59 | | std | 21.63 | | cv | 0.707 | | sampleLengths | | 0 | 8 | | 1 | 33 | | 2 | 53 | | 3 | 5 | | 4 | 45 | | 5 | 28 | | 6 | 1 | | 7 | 44 | | 8 | 15 | | 9 | 64 | | 10 | 44 | | 11 | 14 | | 12 | 47 | | 13 | 48 | | 14 | 5 | | 15 | 4 | | 16 | 6 | | 17 | 43 | | 18 | 51 | | 19 | 43 | | 20 | 41 | | 21 | 31 | | 22 | 36 | | 23 | 46 | | 24 | 57 | | 25 | 46 | | 26 | 31 | | 27 | 2 | | 28 | 5 | | 29 | 69 | | 30 | 6 | | 31 | 74 | | 32 | 60 | | 33 | 27 | | 34 | 2 | | 35 | 2 | | 36 | 1 | | 37 | 34 | | 38 | 22 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 48 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 114 | | matches | | |
| 66.67% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 2 | | flaggedSentences | 2 | | totalSentences | 75 | | ratio | 0.027 | | matches | | 0 | "The spatial dynamic of the small flat vanished; he dominated the room, drawing all the available heat toward his half-demon frame." | | 1 | "She knocked over a column of bound leather texts; they thudded onto the floor, fanning out around her ankles." |
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| 88.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 729 | | adjectiveStacks | 2 | | stackExamples | | 0 | "expensive rain-soaked wool," | | 1 | "pale, crescent-shaped scar" |
| | adverbCount | 20 | | adverbRatio | 0.027434842249657063 | | lyAdverbCount | 10 | | lyAdverbRatio | 0.013717421124828532 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 75 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 75 | | mean | 15.91 | | std | 9.65 | | cv | 0.607 | | sampleLengths | | 0 | 8 | | 1 | 13 | | 2 | 20 | | 3 | 24 | | 4 | 16 | | 5 | 13 | | 6 | 5 | | 7 | 27 | | 8 | 18 | | 9 | 23 | | 10 | 5 | | 11 | 1 | | 12 | 25 | | 13 | 19 | | 14 | 5 | | 15 | 10 | | 16 | 17 | | 17 | 21 | | 18 | 26 | | 19 | 11 | | 20 | 10 | | 21 | 23 | | 22 | 14 | | 23 | 37 | | 24 | 10 | | 25 | 11 | | 26 | 21 | | 27 | 16 | | 28 | 5 | | 29 | 4 | | 30 | 6 | | 31 | 14 | | 32 | 29 | | 33 | 4 | | 34 | 20 | | 35 | 18 | | 36 | 9 | | 37 | 26 | | 38 | 17 | | 39 | 23 | | 40 | 7 | | 41 | 11 | | 42 | 12 | | 43 | 19 | | 44 | 3 | | 45 | 1 | | 46 | 21 | | 47 | 11 | | 48 | 30 | | 49 | 16 |
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| 50.67% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 7 | | diversityRatio | 0.36 | | totalSentences | 75 | | uniqueOpeners | 27 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 47 | | matches | (empty) | | ratio | 0 | |
| 24.26% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 23 | | totalSentences | 47 | | matches | | 0 | "His amber eye caught the" | | 1 | "He leaned slightly on his" | | 2 | "She gripped the edge of" | | 3 | "He stepped forward, forcing her" | | 4 | "She backed down the narrow" | | 5 | "He shed his wet coat," | | 6 | "he murmured, sweeping a glance" | | 7 | "He stepped closer, his boots" | | 8 | "She lifted her chin, staring" | | 9 | "He reached out, his long" | | 10 | "His thumb brushed the soft" | | 11 | "She didn't pull away from" | | 12 | "Her heart hammered wildly against" | | 13 | "She walked past him, needing" | | 14 | "She knocked over a column" | | 15 | "She kicked them aside and" | | 16 | "Her voice cracked, betraying the" | | 17 | "He crossed the room in" | | 18 | "His voice rose, sharp and" | | 19 | "He rested both hands flat" |
| | ratio | 0.489 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 45 | | totalSentences | 47 | | matches | | 0 | "Aurora dragged the oak door" | | 1 | "The scent of ozone, expensive" | | 2 | "Lucien Moreau stood beneath the" | | 3 | "His amber eye caught the" | | 4 | "He leaned slightly on his" | | 5 | "She gripped the edge of" | | 6 | "He stepped forward, forcing her" | | 7 | "Lucien tipped his hat back" | | 8 | "Aurora ground her molars together." | | 9 | "She backed down the narrow" | | 10 | "The flat smelled of simmering" | | 11 | "Books stacked four feet high" | | 12 | "Ptolemy, the ginger tabby, slunk" | | 13 | "Lucien shut the heavy door," | | 14 | "The crisp *clack-clack-clack* echoed like" | | 15 | "He shed his wet coat," | | 16 | "he murmured, sweeping a glance" | | 17 | "Aurora crossed her arms, tucking" | | 18 | "He stepped closer, his boots" | | 19 | "The spatial dynamic of the" |
| | ratio | 0.957 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 47 | | matches | (empty) | | ratio | 0 | |
| 85.71% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 25 | | technicalSentenceCount | 2 | | matches | | 0 | "He reached out, his long fingers hesitating before sliding beneath her jaw, resting lightly on her pulse point." | | 1 | "Lucien lifted one hand from the desk, cupping the back of her neck, his fingers tangling into her straight black hair." |
| |
| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 15 | | uselessAdditionCount | 4 | | matches | | 0 | "She didn't, though every instinct told her that leaning into it was a dangerous mistake" | | 1 | "Lucien corrected softly, his amber eye narrowing" | | 2 | "she snapped, her chest heaving as she glared into his face" | | 3 | "he breathed, his eyes dropping to her mouth" |
| |
| 54.76% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 4 | | fancyCount | 4 | | fancyTags | | 0 | "he murmured (murmur)" | | 1 | "Lucien corrected softly (correct)" | | 2 | "she snapped (snap)" | | 3 | "he breathed (breathe)" |
| | dialogueSentences | 42 | | tagDensity | 0.095 | | leniency | 0.19 | | rawRatio | 1 | | effectiveRatio | 0.19 | |