| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 7 | | adverbTagCount | 1 | | adverbTags | | 0 | "Eva’s fingers tightened around [around]" |
| | dialogueSentences | 32 | | tagDensity | 0.219 | | leniency | 0.438 | | rawRatio | 0.143 | | effectiveRatio | 0.063 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 911 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 100.00% | AI-ism character names | Target: 0 AI-default names (16 tracked, −20% each) | | codexExemptions | | | found | (empty) | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 61.58% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 911 | | totalAiIsms | 7 | | found | | | highlights | | 0 | "flickered" | | 1 | "weight" | | 2 | "flicked" | | 3 | "glinting" | | 4 | "traced" | | 5 | "silence" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "sent a shiver through" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 77 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 77 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 103 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 28 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 906 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 5 | | unquotedAttributions | 0 | | matches | (empty) | |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 58 | | wordCount | 747 | | uniqueNames | 7 | | maxNameDensity | 3.21 | | worstName | "Eva" | | maxWindowNameDensity | 5.5 | | worstWindowName | "Eva" | | discoveredNames | | Raven | 1 | | Nest | 3 | | Rory | 21 | | Soho | 1 | | Cardiff | 2 | | Eva | 24 | | Silas | 6 |
| | persons | | 0 | "Raven" | | 1 | "Nest" | | 2 | "Rory" | | 3 | "Eva" | | 4 | "Silas" |
| | places | | | globalScore | 0 | | windowScore | 0 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 52 | | glossingSentenceCount | 1 | | matches | | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 906 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 103 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 41 | | mean | 22.1 | | std | 14.65 | | cv | 0.663 | | sampleLengths | | 0 | 68 | | 1 | 49 | | 2 | 37 | | 3 | 5 | | 4 | 36 | | 5 | 4 | | 6 | 13 | | 7 | 48 | | 8 | 15 | | 9 | 22 | | 10 | 16 | | 11 | 28 | | 12 | 13 | | 13 | 12 | | 14 | 43 | | 15 | 41 | | 16 | 26 | | 17 | 10 | | 18 | 6 | | 19 | 28 | | 20 | 11 | | 21 | 20 | | 22 | 9 | | 23 | 4 | | 24 | 16 | | 25 | 34 | | 26 | 6 | | 27 | 28 | | 28 | 11 | | 29 | 28 | | 30 | 11 | | 31 | 20 | | 32 | 6 | | 33 | 27 | | 34 | 34 | | 35 | 29 | | 36 | 8 | | 37 | 8 | | 38 | 16 | | 39 | 20 | | 40 | 40 |
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| 96.15% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 77 | | matches | | 0 | "were traded" | | 1 | "were lined" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 135 | | matches | | 0 | "was listening" | | 1 | "wasn’t just talking" |
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| 31.90% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 4 | | semicolonCount | 0 | | flaggedSentences | 4 | | totalSentences | 103 | | ratio | 0.039 | | matches | | 0 | "She shook the rain from her jacket, fingers brushing the crescent scar on her wrist—a habit she’d never quite shaken." | | 1 | "She was taller than Rory recalled, or maybe it was just the way she carried herself now—shoulders squared, jaw set." | | 2 | "Rory touched her hair—straight, black, cut just past her shoulders." | | 3 | "Rory studied Eva’s face—the new hardness in her jaw, the way her eyes didn’t quite meet hers." |
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| 90.94% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 278 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 14 | | adverbRatio | 0.050359712230215826 | | lyAdverbCount | 0 | | lyAdverbRatio | 0 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 103 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 103 | | mean | 8.8 | | std | 6.16 | | cv | 0.7 | | sampleLengths | | 0 | 25 | | 1 | 20 | | 2 | 23 | | 3 | 16 | | 4 | 5 | | 5 | 4 | | 6 | 14 | | 7 | 10 | | 8 | 22 | | 9 | 15 | | 10 | 5 | | 11 | 17 | | 12 | 3 | | 13 | 3 | | 14 | 13 | | 15 | 4 | | 16 | 9 | | 17 | 4 | | 18 | 12 | | 19 | 20 | | 20 | 16 | | 21 | 6 | | 22 | 9 | | 23 | 3 | | 24 | 7 | | 25 | 9 | | 26 | 3 | | 27 | 8 | | 28 | 8 | | 29 | 18 | | 30 | 10 | | 31 | 10 | | 32 | 3 | | 33 | 10 | | 34 | 2 | | 35 | 28 | | 36 | 15 | | 37 | 7 | | 38 | 23 | | 39 | 8 | | 40 | 3 | | 41 | 8 | | 42 | 18 | | 43 | 8 | | 44 | 2 | | 45 | 4 | | 46 | 2 | | 47 | 9 | | 48 | 19 | | 49 | 6 |
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| 57.93% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 2 | | diversityRatio | 0.3592233009708738 | | totalSentences | 103 | | uniqueOpeners | 37 | |
| 44.44% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 75 | | matches | | 0 | "Then the door opened again." |
| | ratio | 0.013 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 11 | | totalSentences | 75 | | matches | | 0 | "She shook the rain from" | | 1 | "He didn’t need them." | | 2 | "She slid onto a stool" | | 3 | "She didn’t turn." | | 4 | "She was taller than Rory" | | 5 | "She shook her head, but" | | 6 | "She hadn’t asked for it," | | 7 | "His back was to them," | | 8 | "She watched as Eva pulled" | | 9 | "He wiped the counter, the" | | 10 | "She knew he wasn’t just" |
| | ratio | 0.147 | |
| 6.67% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 68 | | totalSentences | 75 | | matches | | 0 | "The green neon sign of" | | 1 | "She shook the rain from" | | 2 | "The bar smelled of aged" | | 3 | "Silas looked up from polishing" | | 4 | "A slow nod, no words." | | 5 | "He didn’t need them." | | 6 | "The Nest was his domain," | | 7 | "Rory wasn’t a regular, but" | | 8 | "She slid onto a stool" | | 9 | "The bar was quiet tonight," | | 10 | "A gust of wind sent" | | 11 | "She didn’t turn." | | 12 | "The way the air shifted," | | 13 | "The voice was rougher than" | | 14 | "Rory exhaled, then turned." | | 15 | "Eva stood in the doorway," | | 16 | "She was taller than Rory" | | 17 | "The years had carved lines" | | 18 | "Eva said, stepping forward" | | 19 | "Rory’s throat tightened." |
| | ratio | 0.907 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 75 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 29 | | technicalSentenceCount | 1 | | matches | | 0 | "The Nest was his domain, and he knew every face that belonged in it." |
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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 | 2 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 32 | | tagDensity | 0.063 | | leniency | 0.125 | | rawRatio | 0 | | effectiveRatio | 0 | |