| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 7 | | adverbTagCount | 1 | | adverbTags | | 0 | "she said slowly [slowly]" |
| | dialogueSentences | 42 | | tagDensity | 0.167 | | leniency | 0.333 | | rawRatio | 0.143 | | effectiveRatio | 0.048 | |
| 89.14% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1381 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | 0 | "precisely" | | 1 | "slightly" | | 2 | "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) | |
| 78.28% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1381 | | totalAiIsms | 6 | | found | | | highlights | | 0 | "calculating" | | 1 | "tracing" | | 2 | "vibrated" | | 3 | "silence" | | 4 | "echo" | | 5 | "could feel" |
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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 | 75 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 2 | | narrationSentences | 75 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 110 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 58 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1371 | | ratio | 0 | | matches | (empty) | |
| 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 | 16 | | wordCount | 866 | | uniqueNames | 5 | | maxNameDensity | 0.58 | | worstName | "Lucien" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Lucien" | | discoveredNames | | French | 2 | | English | 1 | | Lucien | 5 | | Ptolemy | 4 | | Eva | 4 |
| | persons | | 0 | "Lucien" | | 1 | "Ptolemy" | | 2 | "Eva" |
| | places | | | globalScore | 1 | | windowScore | 1 | |
| 59.09% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 55 | | glossingSentenceCount | 2 | | matches | | 0 | "as though boiling water could transform this moment into something manageable" | | 1 | "raitor cat had apparently decided sides" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.729 | | wordCount | 1371 | | matches | | 0 | "not touching, but near enough" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 110 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 60 | | mean | 22.85 | | std | 18.76 | | cv | 0.821 | | sampleLengths | | 0 | 56 | | 1 | 11 | | 2 | 21 | | 3 | 40 | | 4 | 42 | | 5 | 1 | | 6 | 7 | | 7 | 46 | | 8 | 4 | | 9 | 36 | | 10 | 12 | | 11 | 3 | | 12 | 50 | | 13 | 6 | | 14 | 1 | | 15 | 35 | | 16 | 33 | | 17 | 7 | | 18 | 36 | | 19 | 3 | | 20 | 4 | | 21 | 22 | | 22 | 1 | | 23 | 57 | | 24 | 9 | | 25 | 22 | | 26 | 25 | | 27 | 32 | | 28 | 3 | | 29 | 23 | | 30 | 1 | | 31 | 49 | | 32 | 30 | | 33 | 5 | | 34 | 4 | | 35 | 47 | | 36 | 51 | | 37 | 4 | | 38 | 11 | | 39 | 19 | | 40 | 7 | | 41 | 73 | | 42 | 3 | | 43 | 32 | | 44 | 12 | | 45 | 22 | | 46 | 8 | | 47 | 34 | | 48 | 58 | | 49 | 2 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 75 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 151 | | matches | | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 7 | | semicolonCount | 1 | | flaggedSentences | 7 | | totalSentences | 110 | | ratio | 0.064 | | matches | | 0 | "He turned at the sound of his name, and she saw the heterochromatic eyes—amber and black—settle on the narrow opening of the door." | | 1 | "Lucien stood in the hallway in full evening dress—tailored suit, crisp shirt, pocket square." | | 2 | "The cane wasn't affectation; it was performance." | | 3 | "\"I counted.\" Lucien moved deeper into the space, and she caught the smell of him—expensive cologne and something underneath it, something darker and older that she'd never been able to place." | | 4 | "When she turned around, he was examining her research—a manuscript page from the fifteenth century spread across her desk, notes in her cramped handwriting crowding the margins." | | 5 | "Lucien straightened, and something shifted in his expression—relief, perhaps, or satisfaction." | | 6 | "He produced a photograph from his jacket pocket—a small, ancient thing, cloth-wrapped and barely identifiable from the image." |
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| 97.96% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 874 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 37 | | adverbRatio | 0.04233409610983982 | | lyAdverbCount | 14 | | lyAdverbRatio | 0.016018306636155607 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 110 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 110 | | mean | 12.46 | | std | 10.62 | | cv | 0.852 | | sampleLengths | | 0 | 7 | | 1 | 20 | | 2 | 29 | | 3 | 11 | | 4 | 4 | | 5 | 1 | | 6 | 16 | | 7 | 25 | | 8 | 11 | | 9 | 4 | | 10 | 23 | | 11 | 19 | | 12 | 1 | | 13 | 7 | | 14 | 23 | | 15 | 7 | | 16 | 16 | | 17 | 4 | | 18 | 14 | | 19 | 20 | | 20 | 2 | | 21 | 12 | | 22 | 3 | | 23 | 10 | | 24 | 14 | | 25 | 7 | | 26 | 19 | | 27 | 6 | | 28 | 1 | | 29 | 8 | | 30 | 13 | | 31 | 14 | | 32 | 31 | | 33 | 2 | | 34 | 7 | | 35 | 9 | | 36 | 27 | | 37 | 3 | | 38 | 4 | | 39 | 11 | | 40 | 11 | | 41 | 1 | | 42 | 18 | | 43 | 15 | | 44 | 9 | | 45 | 15 | | 46 | 9 | | 47 | 22 | | 48 | 4 | | 49 | 21 |
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| 61.21% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 6 | | diversityRatio | 0.4 | | totalSentences | 110 | | uniqueOpeners | 44 | |
| 49.75% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 67 | | matches | | 0 | "Apparently, she'd been wrong." |
| | ratio | 0.015 | |
| 46.87% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 29 | | totalSentences | 67 | | matches | | 0 | "She sat at her desk," | | 1 | "She undid the first deadbolt," | | 2 | "She didn't pose it as" | | 3 | "He turned at the sound" | | 4 | "His accent curved the edges" | | 5 | "She'd spent enough time around" | | 6 | "She undid the chain and" | | 7 | "He stepped inside without waiting" | | 8 | "She shut the door and" | | 9 | "He smiled at that, the" | | 10 | "She moved to the kitchenette," | | 11 | "Her hands needed something to" | | 12 | "She stared at it as" | | 13 | "She turned to face him." | | 14 | "He set his cane against" | | 15 | "He had made her a" | | 16 | "She'd thought they were goodbye." | | 17 | "He bent down, running a" | | 18 | "She moved to the desk" | | 19 | "Her hands shook slightly as" |
| | ratio | 0.433 | |
| 49.55% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 55 | | totalSentences | 67 | | matches | | 0 | "The knock came at half" | | 1 | "Eva didn't answer to midnight" | | 2 | "She sat at her desk," | | 3 | "Ptolemy's ears perked up from" | | 4 | "The knock came again." | | 5 | "Eva pushed her reading glasses" | | 6 | "She undid the first deadbolt," | | 7 | "The chain stayed locked." | | 8 | "She didn't pose it as" | | 9 | "He turned at the sound" | | 10 | "The chain between them felt" | | 11 | "His accent curved the edges" | | 12 | "She'd spent enough time around" | | 13 | "She undid the chain and" | | 14 | "Lucien stood in the hallway" | | 15 | "The cane wasn't affectation; it" | | 16 | "Everything about him was performance," | | 17 | "He stepped inside without waiting" | | 18 | "The flat seemed to shrink" | | 19 | "Ptolemy lifted his head, studying" |
| | ratio | 0.821 | |
| 74.63% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 67 | | matches | | 0 | "Even in the hallway's weak" |
| | ratio | 0.015 | |
| 67.67% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 38 | | technicalSentenceCount | 4 | | matches | | 0 | "Eva pushed her reading glasses up into her hair and moved through the cramped space, sidestepping stacks of books that had accumulated like geological layers." | | 1 | "Even in the hallway's weak lighting, his platinum hair gleamed like something that didn't belong in the real world." | | 2 | "She stared at it as though it might reveal secrets, as though boiling water could transform this moment into something manageable." | | 3 | "He set his cane against the desk with careful precision, as though the act required concentration." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 7 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 4 | | fancyCount | 1 | | fancyTags | | 0 | "Eva whispered (whisper)" |
| | dialogueSentences | 42 | | tagDensity | 0.095 | | leniency | 0.19 | | rawRatio | 0.25 | | effectiveRatio | 0.048 | |