| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 14 | | adverbTagCount | 1 | | adverbTags | | 0 | "I said quietly [quietly]" |
| | dialogueSentences | 89 | | tagDensity | 0.157 | | leniency | 0.315 | | rawRatio | 0.071 | | effectiveRatio | 0.022 | |
| 89.71% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1458 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | 0 | "sharply" | | 1 | "very" | | 2 | "carefully" |
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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) | |
| 69.14% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1458 | | totalAiIsms | 9 | | found | | | highlights | | 0 | "familiar" | | 1 | "silence" | | 2 | "electric" | | 3 | "trembled" | | 4 | "shattered" | | 5 | "echoing" | | 6 | "footsteps" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "sent a shiver through" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 105 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 105 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 178 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 53 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 17 | | markdownWords | 19 | | totalWords | 1450 | | ratio | 0.013 | | matches | | 0 | "here" | | 1 | "fuck" | | 2 | "Evan" | | 3 | "let go" | | 4 | "obsessed" | | 5 | "certain" | | 6 | "you" | | 7 | "needed" | | 8 | "saw" | | 9 | "know" | | 10 | "fixer" | | 11 | "do" | | 12 | "months" | | 13 | "should’ve" | | 14 | "definitely" | | 15 | "endures" | | 16 | "Why now?" |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 21 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 15 | | wordCount | 944 | | uniqueNames | 6 | | maxNameDensity | 0.85 | | worstName | "Aurora" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Aurora" | | discoveredNames | | Golden | 1 | | Empress | 1 | | Eva | 3 | | Aurora | 8 | | Evan | 1 | | Carter | 1 |
| | persons | | 0 | "Empress" | | 1 | "Eva" | | 2 | "Aurora" | | 3 | "Evan" | | 4 | "Carter" |
| | places | | | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 67 | | glossingSentenceCount | 1 | | matches | | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1450 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 178 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 95 | | mean | 15.26 | | std | 17.65 | | cv | 1.156 | | sampleLengths | | 0 | 84 | | 1 | 6 | | 2 | 7 | | 3 | 71 | | 4 | 23 | | 5 | 2 | | 6 | 4 | | 7 | 51 | | 8 | 7 | | 9 | 12 | | 10 | 10 | | 11 | 33 | | 12 | 5 | | 13 | 2 | | 14 | 45 | | 15 | 9 | | 16 | 7 | | 17 | 5 | | 18 | 13 | | 19 | 19 | | 20 | 2 | | 21 | 30 | | 22 | 3 | | 23 | 2 | | 24 | 4 | | 25 | 47 | | 26 | 50 | | 27 | 7 | | 28 | 1 | | 29 | 4 | | 30 | 1 | | 31 | 3 | | 32 | 14 | | 33 | 49 | | 34 | 6 | | 35 | 16 | | 36 | 36 | | 37 | 2 | | 38 | 19 | | 39 | 40 | | 40 | 6 | | 41 | 4 | | 42 | 3 | | 43 | 22 | | 44 | 7 | | 45 | 36 | | 46 | 41 | | 47 | 8 | | 48 | 7 | | 49 | 8 |
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| 98.58% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 105 | | matches | | 0 | "was braced" | | 1 | "been pressed" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 180 | | matches | | 0 | "was looking" | | 1 | "was looking" |
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| 62.60% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 7 | | semicolonCount | 0 | | flaggedSentences | 5 | | totalSentences | 178 | | ratio | 0.028 | | matches | | 0 | "The flat smelled of old books and the faintest hint of lavender—her shampoo, maybe, or the candle Eva always kept burning." | | 1 | "She hadn’t changed much in the months since I’d last seen her—same sharp edges, same way of holding herself like she was braced for impact." | | 2 | "Then she grabbed the nearest thing—a half-empty mug of tea—and hurled it against the wall." | | 3 | "What mattered was the way she was looking at me—like I was the one thing standing between her and the edge." | | 4 | "But the way she was looking at me—like she wanted to believe me, like she *needed* to—made the truth spill out before I could stop it." |
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| 99.12% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 951 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 39 | | adverbRatio | 0.04100946372239748 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.005257623554153523 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 178 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 178 | | mean | 8.15 | | std | 7.07 | | cv | 0.867 | | sampleLengths | | 0 | 18 | | 1 | 18 | | 2 | 14 | | 3 | 34 | | 4 | 6 | | 5 | 7 | | 6 | 4 | | 7 | 22 | | 8 | 11 | | 9 | 21 | | 10 | 13 | | 11 | 7 | | 12 | 13 | | 13 | 3 | | 14 | 2 | | 15 | 4 | | 16 | 5 | | 17 | 25 | | 18 | 13 | | 19 | 2 | | 20 | 6 | | 21 | 6 | | 22 | 1 | | 23 | 12 | | 24 | 9 | | 25 | 1 | | 26 | 16 | | 27 | 17 | | 28 | 5 | | 29 | 2 | | 30 | 11 | | 31 | 13 | | 32 | 11 | | 33 | 10 | | 34 | 9 | | 35 | 7 | | 36 | 4 | | 37 | 1 | | 38 | 13 | | 39 | 3 | | 40 | 3 | | 41 | 10 | | 42 | 3 | | 43 | 2 | | 44 | 11 | | 45 | 9 | | 46 | 6 | | 47 | 4 | | 48 | 3 | | 49 | 2 |
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| 43.82% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 11 | | diversityRatio | 0.28651685393258425 | | totalSentences | 178 | | uniqueOpeners | 51 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 9 | | totalSentences | 91 | | matches | | 0 | "Then she stepped aside, just" | | 1 | "Just stared at the envelope" | | 2 | "Then she grabbed the nearest" | | 3 | "Then, without warning, she closed" | | 4 | "Then she turned away, her" | | 5 | "Then, without another word, she" | | 6 | "Then I pulled out my" | | 7 | "Then Eva sighed." | | 8 | "Then I went to find" |
| | ratio | 0.099 | |
| 52.97% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 38 | | totalSentences | 91 | | matches | | 0 | "Her black hair was damp" | | 1 | "she said, voice flat" | | 2 | "I turned to face her." | | 3 | "She hadn’t changed much in" | | 4 | "She dumped the takeaway bag" | | 5 | "I reached into my coat" | | 6 | "she asked, voice low" | | 7 | "Her head snapped up." | | 8 | "She didn’t laugh." | | 9 | "She exhaled sharply, then snatched" | | 10 | "Her fingers trembled as she" | | 11 | "She unfolded it with the" | | 12 | "I watched her face as" | | 13 | "I didn’t answer." | | 14 | "I stepped closer, close enough" | | 15 | "She whirled on me, eyes" | | 16 | "Her voice cracked" | | 17 | "I’d seen the reports." | | 18 | "She laughed, sharp and humourless." | | 19 | "I said quietly" |
| | ratio | 0.418 | |
| 80.88% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 69 | | totalSentences | 91 | | matches | | 0 | "The door swung open before" | | 1 | "Aurora stood there, her bright" | | 2 | "The scent of soy sauce" | | 3 | "Her black hair was damp" | | 4 | "she said, voice flat" | | 5 | "A beat of silence." | | 6 | "The contact sent a jolt" | | 7 | "The flat smelled of old" | | 8 | "Ptolemy, the tabby cat, wound" | | 9 | "Aurora shut the door harder" | | 10 | "The three deadbolts clicked into" | | 11 | "I turned to face her." | | 12 | "She hadn’t changed much in" | | 13 | "A laugh escaped me before" | | 14 | "She dumped the takeaway bag" | | 15 | "I reached into my coat" | | 16 | "The paper was thin, flimsy," | | 17 | "Aurora’s fingers stilled on the" | | 18 | "she asked, voice low" | | 19 | "Her head snapped up." |
| | ratio | 0.758 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 91 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 43 | | technicalSentenceCount | 2 | | matches | | 0 | "Aurora stared at me, her chest rising and falling too fast." | | 1 | "Then, without warning, she closed the distance between us, her hands fisting in the lapels of my coat." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 14 | | uselessAdditionCount | 4 | | matches | | 0 | "she said, voice flat" | | 1 | "she asked, voice low" | | 2 | "She whirled, eyes blazing" | | 3 | "She gestured, her hand shaking" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 9 | | fancyCount | 2 | | fancyTags | | 0 | "she breathed (breathe)" | | 1 | "she demanded (demand)" |
| | dialogueSentences | 89 | | tagDensity | 0.101 | | leniency | 0.202 | | rawRatio | 0.222 | | effectiveRatio | 0.045 | |