| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 30 | | adverbTagCount | 3 | | adverbTags | | 0 | "He gestured vaguely [vaguely]" | | 1 | "He corrected smoothly [smoothly]" | | 2 | "He turned back [back]" |
| | dialogueSentences | 74 | | tagDensity | 0.405 | | leniency | 0.811 | | rawRatio | 0.1 | | effectiveRatio | 0.081 | |
| 78.79% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1650 | | totalAiIsmAdverbs | 7 | | found | | | highlights | | 0 | "perfectly" | | 1 | "suddenly" | | 2 | "slightly" | | 3 | "very" | | 4 | "slowly" | | 5 | "sharply" |
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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) | |
| 57.58% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1650 | | totalAiIsms | 14 | | found | | | highlights | | 0 | "abyssal" | | 1 | "scanned" | | 2 | "weight" | | 3 | "comforting" | | 4 | "pristine" | | 5 | "resonance" | | 6 | "stomach" | | 7 | "magnetic" | | 8 | "whisper" | | 9 | "footsteps" | | 10 | "gleaming" | | 11 | "vibrated" | | 12 | "echoed" | | 13 | "glint" |
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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 | 116 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 2 | | narrationSentences | 116 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 160 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 35 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1642 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 17 | | unquotedAttributions | 0 | | matches | (empty) | |
| 94.49% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 19 | | wordCount | 1171 | | uniqueNames | 6 | | maxNameDensity | 1.11 | | worstName | "Lucien" | | maxWindowNameDensity | 2 | | worstWindowName | "Lucien" | | discoveredNames | | Eva | 2 | | Moreau | 1 | | Oxford | 1 | | Lucien | 13 | | Varkolak | 1 | | Alpha | 1 |
| | persons | | 0 | "Eva" | | 1 | "Moreau" | | 2 | "Lucien" | | 3 | "Alpha" |
| | places | | | globalScore | 0.945 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 87 | | glossingSentenceCount | 1 | | matches | | 0 | "looked like a man, but wrong—too tall, li" |
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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 | 1642 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 160 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 89 | | mean | 18.45 | | std | 15.21 | | cv | 0.824 | | sampleLengths | | 0 | 37 | | 1 | 13 | | 2 | 3 | | 3 | 50 | | 4 | 13 | | 5 | 4 | | 6 | 29 | | 7 | 20 | | 8 | 43 | | 9 | 5 | | 10 | 6 | | 11 | 26 | | 12 | 3 | | 13 | 5 | | 14 | 43 | | 15 | 31 | | 16 | 3 | | 17 | 11 | | 18 | 31 | | 19 | 2 | | 20 | 47 | | 21 | 2 | | 22 | 5 | | 23 | 8 | | 24 | 1 | | 25 | 12 | | 26 | 7 | | 27 | 26 | | 28 | 3 | | 29 | 29 | | 30 | 2 | | 31 | 44 | | 32 | 7 | | 33 | 8 | | 34 | 61 | | 35 | 7 | | 36 | 36 | | 37 | 18 | | 38 | 13 | | 39 | 46 | | 40 | 25 | | 41 | 3 | | 42 | 7 | | 43 | 3 | | 44 | 56 | | 45 | 44 | | 46 | 21 | | 47 | 14 | | 48 | 32 | | 49 | 10 |
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| 96.19% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 116 | | matches | | 0 | "was slicked" | | 1 | "was tailored" | | 2 | "was ruined" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 193 | | matches | | |
| 89.29% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 4 | | semicolonCount | 0 | | flaggedSentences | 3 | | totalSentences | 160 | | ratio | 0.019 | | matches | | 0 | "His platinum blond hair was slicked back with surgical precision, and his mismatched eyes—one amber, one abyssal black—scanned my face with the detached interest of a jeweller assessing a flawed gem." | | 1 | "Up close, the scent of him was intoxicating—sandalwood and something metallic, like blood on a blade." | | 2 | "It looked like a man, but wrong—too tall, limbs too long, skin the colour of a bruised plum." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1178 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 34 | | adverbRatio | 0.028862478777589132 | | lyAdverbCount | 13 | | lyAdverbRatio | 0.011035653650254669 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 160 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 160 | | mean | 10.26 | | std | 6.9 | | cv | 0.672 | | sampleLengths | | 0 | 10 | | 1 | 27 | | 2 | 13 | | 3 | 3 | | 4 | 19 | | 5 | 31 | | 6 | 6 | | 7 | 7 | | 8 | 4 | | 9 | 18 | | 10 | 11 | | 11 | 11 | | 12 | 9 | | 13 | 13 | | 14 | 19 | | 15 | 11 | | 16 | 5 | | 17 | 6 | | 18 | 14 | | 19 | 12 | | 20 | 3 | | 21 | 5 | | 22 | 4 | | 23 | 24 | | 24 | 15 | | 25 | 13 | | 26 | 18 | | 27 | 3 | | 28 | 11 | | 29 | 15 | | 30 | 16 | | 31 | 2 | | 32 | 13 | | 33 | 4 | | 34 | 26 | | 35 | 4 | | 36 | 2 | | 37 | 5 | | 38 | 8 | | 39 | 1 | | 40 | 8 | | 41 | 4 | | 42 | 2 | | 43 | 5 | | 44 | 11 | | 45 | 15 | | 46 | 3 | | 47 | 7 | | 48 | 22 | | 49 | 2 |
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| 47.29% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 11 | | diversityRatio | 0.325 | | totalSentences | 160 | | uniqueOpeners | 52 | |
| 64.10% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 104 | | matches | | 0 | "Instead, a wall of charcoal" | | 1 | "Instead, he plucked a loose" |
| | ratio | 0.019 | |
| 16.15% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 53 | | totalSentences | 104 | | matches | | 0 | "I yanked the door open," | | 1 | "His platinum blond hair was" | | 2 | "I moved to slam the" | | 3 | "I leaned my weight against" | | 4 | "He stepped forward, forcing me" | | 5 | "He pushed inside, the ivory" | | 6 | "I crossed my arms." | | 7 | "He walked to the cluttered" | | 8 | "I said, my voice steady" | | 9 | "He turned, his amber eye" | | 10 | "He leaned against the desk," | | 11 | "He looked too pristine." | | 12 | "His suit was tailored to" | | 13 | "He gestured vaguely towards the" | | 14 | "He sighed, a sound of" | | 15 | "He pushed off the desk" | | 16 | "I stood my ground, tilting" | | 17 | "He reached out, his hand" | | 18 | "I flinched, but he didn't" | | 19 | "He corrected smoothly" |
| | ratio | 0.51 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 97 | | totalSentences | 104 | | matches | | 0 | "The third deadbolt slid back" | | 1 | "I yanked the door open," | | 2 | "Lucien Moreau stood in the" | | 3 | "His platinum blond hair was" | | 4 | "I moved to slam the" | | 5 | "A polished Oxford shoe stopped" | | 6 | "I leaned my weight against" | | 7 | "He stepped forward, forcing me" | | 8 | "He pushed inside, the ivory" | | 9 | "The small living room, already" | | 10 | "Lucien ducked slightly to avoid" | | 11 | "The ginger tabby wound around" | | 12 | "Lucien ignored me to stroke" | | 13 | "The cat hissed at me." | | 14 | "I crossed my arms." | | 15 | "The flat smelled of cardamom" | | 16 | "He walked to the cluttered" | | 17 | "I said, my voice steady" | | 18 | "He turned, his amber eye" | | 19 | "He leaned against the desk," |
| | ratio | 0.933 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 104 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 43 | | technicalSentenceCount | 2 | | matches | | 0 | "Instead, he plucked a loose hair from my shoulder, inspecting it with mild curiosity before letting it fall to the floor." | | 1 | "He looked back at me, the amber eye burning with a ferocity that made my breath hitch." |
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| 8.33% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 30 | | uselessAdditionCount | 7 | | matches | | 0 | "I said, my voice steady despite the thudding in my chest" | | 1 | "He reached out, his hand hovering near my face" | | 2 | "He looked, his gaze lingering on my wrists" | | 3 | "Lucien’s voice dropped, the black eye seeming to expand" | | 4 | "I asked, my voice barely a whisper" | | 5 | "he commanded, his voice losing the lazy drawl" | | 6 | "I grabbed, his grip crushing mine as he hauled me up" |
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| 28.38% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 12 | | fancyCount | 9 | | fancyTags | | 0 | "I muttered (mutter)" | | 1 | "He corrected smoothly (correct)" | | 2 | "I laughed (laugh)" | | 3 | "I whispered (whisper)" | | 4 | "Lucien corrected (correct)" | | 5 | "Lucien snarled (snarl)" | | 6 | "he whispered (whisper)" | | 7 | "I screamed (scream)" | | 8 | "he roared (roar)" |
| | dialogueSentences | 74 | | tagDensity | 0.162 | | leniency | 0.324 | | rawRatio | 0.75 | | effectiveRatio | 0.243 | |