| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 9 | | adverbTagCount | 2 | | adverbTags | | 0 | "Eva whirled back [back]" | | 1 | "Rory said quietly [quietly]" |
| | dialogueSentences | 45 | | tagDensity | 0.2 | | leniency | 0.4 | | rawRatio | 0.222 | | effectiveRatio | 0.089 | |
| 89.37% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 941 | | totalAiIsmAdverbs | 2 | | found | | | 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) | |
| 62.81% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 941 | | totalAiIsms | 7 | | found | | | highlights | | 0 | "chaotic" | | 1 | "charged" | | 2 | "tension" | | 3 | "flickered" | | 4 | "silence" | | 5 | "weight" | | 6 | "echoed" |
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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 | 73 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 73 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 108 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 46 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 6 | | markdownWords | 12 | | totalWords | 936 | | ratio | 0.013 | | matches | | 0 | "The Occult in Modern London" | | 1 | "see" | | 2 | "help" | | 3 | "had" | | 4 | "had" | | 5 | "Was that enough?" |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 13 | | unquotedAttributions | 0 | | matches | (empty) | |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 49 | | wordCount | 581 | | uniqueNames | 5 | | maxNameDensity | 4.99 | | worstName | "Eva" | | maxWindowNameDensity | 8.5 | | worstWindowName | "Eva" | | discoveredNames | | Rory | 17 | | Eva | 29 | | Occult | 1 | | Modern | 1 | | Lucien | 1 |
| | persons | | | places | | | globalScore | 0 | | windowScore | 0 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 42 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 936 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 108 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 53 | | mean | 17.66 | | std | 14.54 | | cv | 0.823 | | sampleLengths | | 0 | 43 | | 1 | 8 | | 2 | 57 | | 3 | 4 | | 4 | 28 | | 5 | 34 | | 6 | 2 | | 7 | 12 | | 8 | 32 | | 9 | 5 | | 10 | 7 | | 11 | 26 | | 12 | 29 | | 13 | 21 | | 14 | 35 | | 15 | 8 | | 16 | 13 | | 17 | 2 | | 18 | 18 | | 19 | 6 | | 20 | 17 | | 21 | 4 | | 22 | 48 | | 23 | 6 | | 24 | 28 | | 25 | 3 | | 26 | 27 | | 27 | 9 | | 28 | 13 | | 29 | 16 | | 30 | 3 | | 31 | 3 | | 32 | 24 | | 33 | 2 | | 34 | 53 | | 35 | 30 | | 36 | 5 | | 37 | 9 | | 38 | 2 | | 39 | 28 | | 40 | 16 | | 41 | 10 | | 42 | 22 | | 43 | 19 | | 44 | 15 | | 45 | 1 | | 46 | 23 | | 47 | 4 | | 48 | 9 | | 49 | 53 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 73 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 122 | | matches | (empty) | |
| 37.04% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 5 | | semicolonCount | 0 | | flaggedSentences | 4 | | totalSentences | 108 | | ratio | 0.037 | | matches | | 0 | "The flat smelled of stale coffee and something sharper—burnt paper, maybe." | | 1 | "The flat was exactly as she remembered—cluttered, chaotic, alive." | | 2 | "Rory picked up a book from the counter—*The Occult in Modern London*—and flipped through it." | | 3 | "Eva’s eyes flickered with something—fear, maybe, or recognition." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 586 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 20 | | adverbRatio | 0.034129692832764506 | | lyAdverbCount | 6 | | lyAdverbRatio | 0.010238907849829351 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 108 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 108 | | mean | 8.67 | | std | 7.29 | | cv | 0.841 | | sampleLengths | | 0 | 15 | | 1 | 15 | | 2 | 11 | | 3 | 2 | | 4 | 8 | | 5 | 3 | | 6 | 13 | | 7 | 9 | | 8 | 19 | | 9 | 13 | | 10 | 4 | | 11 | 4 | | 12 | 16 | | 13 | 6 | | 14 | 2 | | 15 | 13 | | 16 | 21 | | 17 | 2 | | 18 | 12 | | 19 | 8 | | 20 | 17 | | 21 | 3 | | 22 | 4 | | 23 | 4 | | 24 | 1 | | 25 | 7 | | 26 | 26 | | 27 | 15 | | 28 | 10 | | 29 | 4 | | 30 | 16 | | 31 | 5 | | 32 | 2 | | 33 | 9 | | 34 | 6 | | 35 | 13 | | 36 | 5 | | 37 | 8 | | 38 | 12 | | 39 | 1 | | 40 | 2 | | 41 | 8 | | 42 | 5 | | 43 | 5 | | 44 | 4 | | 45 | 2 | | 46 | 9 | | 47 | 8 | | 48 | 4 | | 49 | 11 |
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| 48.77% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 4 | | diversityRatio | 0.3148148148148148 | | totalSentences | 108 | | uniqueOpeners | 34 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 61 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 12 | | totalSentences | 61 | | matches | | 0 | "She shouldered past, the strap" | | 1 | "She wiped it on her" | | 2 | "She didn’t apologise." | | 3 | "She hadn’t planned on coming" | | 4 | "She knew what that meant." | | 5 | "They both did." | | 6 | "She *had* left." | | 7 | "She *had* run." | | 8 | "She opened her mouth, but" | | 9 | "She leaned against the wall," | | 10 | "She wasn’t the same girl" | | 11 | "She wasn’t the same girl" |
| | ratio | 0.197 | |
| 0.98% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 56 | | totalSentences | 61 | | matches | | 0 | "The door swung open before" | | 1 | "Eva stood there, barefoot in" | | 2 | "The flat smelled of stale" | | 3 | "Eva said, stepping aside" | | 4 | "Rory didn’t answer." | | 5 | "She shouldered past, the strap" | | 6 | "The flat was exactly as" | | 7 | "Scrolls and books spilled across" | | 8 | "Ptolemy, Eva’s tabby, eyed her" | | 9 | "Rory touched her wrist." | | 10 | "The crescent scar had split" | | 11 | "She wiped it on her" | | 12 | "Eva exhaled through her nose," | | 13 | "Rory dropped her bag onto" | | 14 | "The flat was small enough" | | 15 | "She didn’t apologise." | | 16 | "Eva crossed her arms." | | 17 | "Rory picked up a book" | | 18 | "The pages were dog-eared, margins" | | 19 | "Eva grabbed the book back" |
| | ratio | 0.918 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 61 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 25 | | technicalSentenceCount | 1 | | matches | | 0 | "Eva exhaled through her nose, a sound that was half laugh, half frustration." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 9 | | uselessAdditionCount | 3 | | matches | | 0 | "Eva whirled back, her voice rising" | | 1 | "Eva’s chest heaved, her cheeks flushed" | | 2 | "Eva asked, her voice low" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 6 | | fancyCount | 2 | | fancyTags | | 0 | "Rory snapped (snap)" | | 1 | "Eva breathed (breathe)" |
| | dialogueSentences | 45 | | tagDensity | 0.133 | | leniency | 0.267 | | rawRatio | 0.333 | | effectiveRatio | 0.089 | |