| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 14 | | adverbTagCount | 1 | | adverbTags | | 0 | "she said softly [softly]" |
| | dialogueSentences | 37 | | tagDensity | 0.378 | | leniency | 0.757 | | rawRatio | 0.071 | | effectiveRatio | 0.054 | |
| 73.89% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1149 | | totalAiIsmAdverbs | 6 | | found | | | highlights | | 0 | "sharply" | | 1 | "slowly" | | 2 | "softly" | | 3 | "gently" |
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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) | |
| 65.19% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1149 | | totalAiIsms | 8 | | found | | | highlights | | 0 | "stark" | | 1 | "echoed" | | 2 | "glinting" | | 3 | "familiar" | | 4 | "flicked" | | 5 | "mechanical" | | 6 | "tracing" | | 7 | "weight" |
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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 | 72 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 72 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 95 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 47 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 8 | | markdownWords | 13 | | totalWords | 1169 | | ratio | 0.011 | | matches | | 0 | "I’m sorry, I can’t do this" | | 1 | "you" | | 2 | "can’t" | | 3 | "our" | | 4 | "our" | | 5 | "mean" | | 6 | "are" | | 7 | "You’re" |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 18 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 24 | | wordCount | 745 | | uniqueNames | 13 | | maxNameDensity | 0.81 | | worstName | "Rory" | | maxWindowNameDensity | 2 | | worstWindowName | "Rory" | | discoveredNames | | Brick | 1 | | Lane | 1 | | Golden | 1 | | Empress | 1 | | General | 1 | | Tso | 1 | | Eva | 3 | | Rory | 6 | | Prague | 1 | | Ptolemy | 1 | | Moreau | 1 | | French | 1 | | Lucien | 5 |
| | persons | | 0 | "Tso" | | 1 | "Eva" | | 2 | "Rory" | | 3 | "Moreau" | | 4 | "Lucien" |
| | places | | 0 | "Brick" | | 1 | "Lane" | | 2 | "Golden" | | 3 | "Prague" |
| | globalScore | 1 | | windowScore | 1 | |
| 89.02% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 41 | | glossingSentenceCount | 1 | | matches | | 0 | "looked like he’d stepped out of a dream —" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.855 | | wordCount | 1169 | | matches | | 0 | "Not the usual dim reading lamp, but the overhead fixture, casting a stark white rectangle throug" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 95 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 43 | | mean | 27.19 | | std | 21.47 | | cv | 0.79 | | sampleLengths | | 0 | 97 | | 1 | 5 | | 2 | 10 | | 3 | 50 | | 4 | 4 | | 5 | 57 | | 6 | 44 | | 7 | 2 | | 8 | 16 | | 9 | 56 | | 10 | 44 | | 11 | 42 | | 12 | 6 | | 13 | 36 | | 14 | 34 | | 15 | 9 | | 16 | 25 | | 17 | 18 | | 18 | 3 | | 19 | 24 | | 20 | 34 | | 21 | 3 | | 22 | 47 | | 23 | 48 | | 24 | 27 | | 25 | 9 | | 26 | 57 | | 27 | 6 | | 28 | 36 | | 29 | 62 | | 30 | 17 | | 31 | 23 | | 32 | 10 | | 33 | 29 | | 34 | 20 | | 35 | 63 | | 36 | 15 | | 37 | 8 | | 38 | 35 | | 39 | 7 | | 40 | 2 | | 41 | 6 | | 42 | 23 |
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| 95.52% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 72 | | matches | | 0 | "was locked" | | 1 | "was slicked" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 127 | | matches | (empty) | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 15 | | semicolonCount | 0 | | flaggedSentences | 12 | | totalSentences | 95 | | ratio | 0.126 | | matches | | 0 | "She’d just dropped off her last delivery from the Golden Empress — two orders of General Tso’s and a pot of jasmine tea — and the cold had seeped into her bones." | | 1 | "And though the door below was locked, the upper stairwell was never properly secured — Eva, brilliant with spells and sigils but indifferent to mundane security, relied on the triple deadbolts." | | 2 | "Dressed in a charcoal suit that looked untouched by the storm outside, he looked like he’d stepped out of a dream — or a threat." | | 3 | "Years of instinct flared — fight, flight, or freeze." | | 4 | "Lucien knew everything — or made sure he did." | | 5 | "“I know.” He didn’t move from the chair, but his amber eye caught the low light, the other — the inhuman black one — seeming to absorb it." | | 6 | "Hated that after all this, after learning to walk without flinching at loud noises, after building a life where she wasn’t afraid of the man in her bed — hated that he could still do this to her." | | 7 | "He stepped closer, slow, careful — like approaching a wounded animal." | | 8 | "Not her face, not her waist — her left hand." | | 9 | "His hair was slicked back as always, severe, framing a face carved with the weight of centuries — he wasn’t fully human, and time moved differently for him." | | 10 | "Around his left temple, barely visible beneath the blond strands, was a jagged mark — the brand of his father’s bloodline, he’d once told her in a rare moment of vulnerability." | | 11 | "His heartbeat — slower than a human’s, steady as ancient stone — thrummed beneath her ear." |
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| 88.25% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 730 | | adjectiveStacks | 1 | | stackExamples | | 0 | "closer, slow, careful — like" |
| | adverbCount | 34 | | adverbRatio | 0.04657534246575343 | | lyAdverbCount | 13 | | lyAdverbRatio | 0.01780821917808219 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 95 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 95 | | mean | 12.31 | | std | 10.02 | | cv | 0.815 | | sampleLengths | | 0 | 33 | | 1 | 20 | | 2 | 32 | | 3 | 12 | | 4 | 5 | | 5 | 10 | | 6 | 19 | | 7 | 31 | | 8 | 4 | | 9 | 12 | | 10 | 7 | | 11 | 17 | | 12 | 21 | | 13 | 19 | | 14 | 25 | | 15 | 2 | | 16 | 7 | | 17 | 9 | | 18 | 3 | | 19 | 8 | | 20 | 9 | | 21 | 12 | | 22 | 24 | | 23 | 4 | | 24 | 16 | | 25 | 24 | | 26 | 3 | | 27 | 4 | | 28 | 4 | | 29 | 9 | | 30 | 8 | | 31 | 14 | | 32 | 6 | | 33 | 28 | | 34 | 8 | | 35 | 7 | | 36 | 27 | | 37 | 5 | | 38 | 4 | | 39 | 8 | | 40 | 17 | | 41 | 12 | | 42 | 6 | | 43 | 3 | | 44 | 7 | | 45 | 17 | | 46 | 7 | | 47 | 27 | | 48 | 3 | | 49 | 47 |
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| 68.07% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 2 | | diversityRatio | 0.42105263157894735 | | totalSentences | 95 | | uniqueOpeners | 40 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 4 | | totalSentences | 64 | | matches | | 0 | "Of course he did." | | 1 | "Gently, he turned it over," | | 2 | "Somewhere below, a pot clanged" | | 3 | "Instead, she stepped forward, closed" |
| | ratio | 0.063 | |
| 13.75% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 33 | | totalSentences | 64 | | matches | | 0 | "She’d just dropped off her" | | 1 | "Her fingers, stiff from gripping" | | 2 | "She didn’t expect to find" | | 3 | "he said, voice low, familiar" | | 4 | "She didn’t move." | | 5 | "Her heart slammed once, hard," | | 6 | "she asked, stepping inside and" | | 7 | "He gestured to a drawer" | | 8 | "She knew the story." | | 9 | "She flicked the deadbolts back" | | 10 | "He didn’t move from the" | | 11 | "She leaned against the bookshelf," | | 12 | "He closed his eyes briefly." | | 13 | "She let out a bitter" | | 14 | "He stood then, slowly, gracefully," | | 15 | "He took a step forward" | | 16 | "She turned, facing him fully" | | 17 | "Her voice cracked on the" | | 18 | "She hated that." | | 19 | "It clattered softly against the" |
| | ratio | 0.516 | |
| 77.19% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 49 | | totalSentences | 64 | | matches | | 0 | "The rain had turned Brick" | | 1 | "Rory stood under the crooked" | | 2 | "She’d just dropped off her" | | 3 | "Her fingers, stiff from gripping" | | 4 | "The light from Eva’s flat" | | 5 | "She didn’t expect to find" | | 6 | "Eva was in Prague, chasing" | | 7 | "The man sat with one" | | 8 | "he said, voice low, familiar" | | 9 | "The French accent curled around" | | 10 | "She didn’t move." | | 11 | "Her heart slammed once, hard," | | 12 | "Years of instinct flared —" | | 13 | "she asked, stepping inside and" | | 14 | "Lucien tilted his head." | | 15 | "He gestured to a drawer" | | 16 | "Rory exhaled sharply." | | 17 | "She knew the story." | | 18 | "Lucien knew everything — or" | | 19 | "Information was his trade, his" |
| | ratio | 0.766 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 64 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 25 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 89.29% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 14 | | uselessAdditionCount | 1 | | matches | | 0 | "he said, voice low, familiar" |
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| 68.92% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 9 | | fancyCount | 3 | | fancyTags | | 0 | "she whispered (whisper)" | | 1 | "she murmured (murmur)" | | 2 | "he whispered (whisper)" |
| | dialogueSentences | 37 | | tagDensity | 0.243 | | leniency | 0.486 | | rawRatio | 0.333 | | effectiveRatio | 0.162 | |