| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 14 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 47 | | tagDensity | 0.298 | | leniency | 0.596 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 92.38% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1312 | | totalAiIsmAdverbs | 2 | | found | | 0 | | | 1 | | adverb | "deliberately" | | count | 1 |
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| | highlights | | |
| 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) | |
| 39.02% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1312 | | totalAiIsms | 16 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | word | "down her spine" | | count | 1 |
| | 9 | | | 10 | | | 11 | | | 12 | | | 13 | | | 14 | | | 15 | |
| | highlights | | 0 | "stark" | | 1 | "echoed" | | 2 | "vibrated" | | 3 | "rhythmic" | | 4 | "silk" | | 5 | "scanning" | | 6 | "electric" | | 7 | "chaotic" | | 8 | "down her spine" | | 9 | "fascinating" | | 10 | "intensity" | | 11 | "weight" | | 12 | "pulse" | | 13 | "racing" | | 14 | "familiar" | | 15 | "shattered" |
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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 | 76 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 76 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 109 | | 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 | 1312 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 14 | | unquotedAttributions | 0 | | matches | (empty) | |
| 66.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 33 | | wordCount | 924 | | uniqueNames | 11 | | maxNameDensity | 1.41 | | worstName | "Lucien" | | maxWindowNameDensity | 3 | | worstWindowName | "Lucien" | | discoveredNames | | Lucien | 13 | | Moreau | 1 | | London | 1 | | French | 2 | | Irish | 1 | | Eva | 2 | | Aramaic | 1 | | Avaros | 2 | | Rory | 7 | | Ptolemy | 2 | | Cardiff | 1 |
| | persons | | 0 | "Lucien" | | 1 | "Moreau" | | 2 | "Eva" | | 3 | "Rory" | | 4 | "Ptolemy" |
| | places | | | globalScore | 0.797 | | windowScore | 0.667 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 66 | | glossingSentenceCount | 1 | | matches | | 0 | "felt like sealing her own tomb" |
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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 | 1312 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 109 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 61 | | mean | 21.51 | | std | 18.14 | | cv | 0.843 | | sampleLengths | | 0 | 11 | | 1 | 29 | | 2 | 6 | | 3 | 55 | | 4 | 8 | | 5 | 7 | | 6 | 13 | | 7 | 51 | | 8 | 75 | | 9 | 47 | | 10 | 74 | | 11 | 33 | | 12 | 8 | | 13 | 13 | | 14 | 5 | | 15 | 9 | | 16 | 49 | | 17 | 40 | | 18 | 14 | | 19 | 6 | | 20 | 11 | | 21 | 7 | | 22 | 44 | | 23 | 7 | | 24 | 9 | | 25 | 15 | | 26 | 58 | | 27 | 11 | | 28 | 9 | | 29 | 6 | | 30 | 14 | | 31 | 34 | | 32 | 29 | | 33 | 5 | | 34 | 7 | | 35 | 10 | | 36 | 33 | | 37 | 21 | | 38 | 8 | | 39 | 7 | | 40 | 5 | | 41 | 2 | | 42 | 1 | | 43 | 36 | | 44 | 19 | | 45 | 50 | | 46 | 9 | | 47 | 13 | | 48 | 38 | | 49 | 14 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 76 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 140 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 109 | | ratio | 0 | | matches | (empty) | |
| 60.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 937 | | adjectiveStacks | 7 | | stackExamples | | 0 | "ancient leather-bound occult" | | 1 | "magnificent tall old rectangular black French" | | 2 | "beautiful small antique golden Irish" | | 3 | "hideous large modern blue plastic storage" | | 4 | "small crescent-shaped scar" | | 5 | "massive, ash-grey hand" | | 6 | "razor-sharp black talons" |
| | adverbCount | 25 | | adverbRatio | 0.026680896478121666 | | lyAdverbCount | 8 | | lyAdverbRatio | 0.008537886872998933 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 109 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 109 | | mean | 12.04 | | std | 6.03 | | cv | 0.501 | | sampleLengths | | 0 | 11 | | 1 | 19 | | 2 | 10 | | 3 | 6 | | 4 | 22 | | 5 | 4 | | 6 | 14 | | 7 | 15 | | 8 | 8 | | 9 | 7 | | 10 | 4 | | 11 | 6 | | 12 | 3 | | 13 | 18 | | 14 | 11 | | 15 | 11 | | 16 | 11 | | 17 | 7 | | 18 | 23 | | 19 | 16 | | 20 | 17 | | 21 | 12 | | 22 | 8 | | 23 | 14 | | 24 | 25 | | 25 | 12 | | 26 | 15 | | 27 | 22 | | 28 | 25 | | 29 | 22 | | 30 | 11 | | 31 | 8 | | 32 | 13 | | 33 | 5 | | 34 | 9 | | 35 | 17 | | 36 | 8 | | 37 | 14 | | 38 | 10 | | 39 | 10 | | 40 | 11 | | 41 | 19 | | 42 | 14 | | 43 | 6 | | 44 | 11 | | 45 | 7 | | 46 | 15 | | 47 | 10 | | 48 | 19 | | 49 | 7 |
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| 50.46% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 10 | | diversityRatio | 0.3577981651376147 | | totalSentences | 109 | | uniqueOpeners | 39 | |
| 47.62% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 70 | | matches | | 0 | "Instead, he took a step" |
| | ratio | 0.014 | |
| 54.29% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 29 | | totalSentences | 70 | | matches | | 0 | "Her heart did a sudden," | | 1 | "His amber eye gleamed." | | 2 | "His black eye, dark as" | | 3 | "He wore a tailored charcoal" | | 4 | "He didn't wait for an" | | 5 | "He never did." | | 6 | "He brushed against her in" | | 7 | "She followed his shadow into" | | 8 | "It forced them close, their" | | 9 | "His back arched instantly into" | | 10 | "He let out a low," | | 11 | "He stepped closer, domesticating the" | | 12 | "He smelled of expensive sandalwood," | | 13 | "She wanted to hide the" | | 14 | "She still carried the physical" | | 15 | "He reached out, his leather-gloved" | | 16 | "She pulled back, her spine" | | 17 | "He stepped into her personal" | | 18 | "He leaned in, his amber" | | 19 | "His gaze dropped to her" |
| | ratio | 0.414 | |
| 10.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 63 | | totalSentences | 70 | | matches | | 0 | "The third steel deadbolt slid" | | 1 | "Rory gripped the edge of" | | 2 | "Her heart did a sudden," | | 3 | "Lucien Moreau leaned elegantly on" | | 4 | "His amber eye gleamed." | | 5 | "His black eye, dark as" | | 6 | "He wore a tailored charcoal" | | 7 | "Lucien stepped past her." | | 8 | "He didn't wait for an" | | 9 | "He never did." | | 10 | "He brushed against her in" | | 11 | "A jolt of static electricity," | | 12 | "Rory closed the door, sliding" | | 13 | "Each turn of the key" | | 14 | "She followed his shadow into" | | 15 | "The cramped hallway smelled of" | | 16 | "Stacks of ancient leather-bound occult" | | 17 | "It forced them close, their" | | 18 | "Lucien leaned his cane against" | | 19 | "The click-clack of the ivory" |
| | ratio | 0.9 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 70 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 49 | | technicalSentenceCount | 1 | | matches | | 0 | "Below, the muffled bass of the curry house's sound system vibrated through the floorboards, a rhythmic thudding that matched the frantic beating of Rory's heart…" |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 14 | | uselessAdditionCount | 6 | | matches | | 0 | "Lucien asked, his French accent rolling over the syllables like heavy silk" | | 1 | "Lucien corrected, turning to face her" | | 2 | "Lucien said, his voice dropping to a low, smooth baritone" | | 3 | "He leaned in, his amber eye burning with a sudden, predatory intensity" | | 4 | "she said, her voice shaking despite her best efforts" | | 5 | "she whispered, her hands blindly searching the counter behind her" |
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| 43.62% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 11 | | fancyCount | 5 | | fancyTags | | 0 | "Lucien corrected (correct)" | | 1 | "Lucien murmured (murmur)" | | 2 | "she whispered (whisper)" | | 3 | "she whispered (whisper)" | | 4 | "he whispered (whisper)" |
| | dialogueSentences | 47 | | tagDensity | 0.234 | | leniency | 0.468 | | rawRatio | 0.455 | | effectiveRatio | 0.213 | |