| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 1 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 9 | | tagDensity | 0.111 | | leniency | 0.222 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 95.84% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1201 | | totalAiIsmAdverbs | 1 | | 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) | |
| 79.18% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1201 | | totalAiIsms | 5 | | found | | | highlights | | 0 | "etched" | | 1 | "echoing" | | 2 | "dancing" | | 3 | "familiar" | | 4 | "glinting" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "blood ran cold" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 32 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 32 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 40 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 74 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1201 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 6 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 22 | | wordCount | 860 | | uniqueNames | 9 | | maxNameDensity | 0.93 | | worstName | "Lucien" | | maxWindowNameDensity | 2 | | worstWindowName | "Lucien" | | discoveredNames | | Eva | 4 | | Lucien | 8 | | Cardiff | 2 | | Brick | 1 | | Lane | 1 | | Golden | 1 | | Empress | 1 | | Whitechapel | 1 | | Evan | 3 |
| | persons | | | places | | 0 | "Cardiff" | | 1 | "Brick" | | 2 | "Lane" | | 3 | "Whitechapel" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 29 | | 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 | 1201 | | matches | (empty) | |
| 83.33% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 40 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 15 | | mean | 80.07 | | std | 41.5 | | cv | 0.518 | | sampleLengths | | 0 | 100 | | 1 | 66 | | 2 | 25 | | 3 | 25 | | 4 | 97 | | 5 | 106 | | 6 | 31 | | 7 | 108 | | 8 | 104 | | 9 | 127 | | 10 | 168 | | 11 | 80 | | 12 | 64 | | 13 | 15 | | 14 | 85 |
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| 50.44% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 5 | | totalSentences | 32 | | matches | | 0 | "was supposed" | | 1 | "was supposed" | | 2 | "was stacked" | | 3 | "were clenched" | | 4 | "been scared" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 141 | | matches | | 0 | "was fighting" | | 1 | "was playing" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 40 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 865 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 19 | | adverbRatio | 0.021965317919075144 | | lyAdverbCount | 3 | | lyAdverbRatio | 0.003468208092485549 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 40 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 40 | | mean | 30.03 | | std | 16.41 | | cv | 0.547 | | sampleLengths | | 0 | 35 | | 1 | 30 | | 2 | 35 | | 3 | 28 | | 4 | 38 | | 5 | 25 | | 6 | 25 | | 7 | 9 | | 8 | 18 | | 9 | 35 | | 10 | 14 | | 11 | 21 | | 12 | 21 | | 13 | 21 | | 14 | 28 | | 15 | 36 | | 16 | 22 | | 17 | 9 | | 18 | 70 | | 19 | 38 | | 20 | 24 | | 21 | 29 | | 22 | 51 | | 23 | 11 | | 24 | 42 | | 25 | 74 | | 26 | 3 | | 27 | 51 | | 28 | 52 | | 29 | 39 | | 30 | 23 | | 31 | 25 | | 32 | 55 | | 33 | 42 | | 34 | 22 | | 35 | 15 | | 36 | 4 | | 37 | 4 | | 38 | 40 | | 39 | 37 |
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| 69.17% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 4 | | diversityRatio | 0.475 | | totalSentences | 40 | | uniqueOpeners | 19 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 32 | | matches | (empty) | | ratio | 0 | |
| 0.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 20 | | totalSentences | 32 | | matches | | 0 | "I wrenched the third deadbolt" | | 1 | "I pulled the door wide," | | 2 | "He stood on the landing," | | 3 | "His heterochromatic eyes, one molten" | | 4 | "I froze, my knuckles white" | | 5 | "I stepped back, and Lucien" | | 6 | "I slammed the door shut," | | 7 | "I leaned against the door," | | 8 | "He tapped his cane on" | | 9 | "I pushed off the door," | | 10 | "My thumb brushed the small" | | 11 | "His jaw tightened, the only" | | 12 | "He crossed the three feet" | | 13 | "My breath caught." | | 14 | "I’d spent the three weeks" | | 15 | "We’d spent months dancing around" | | 16 | "I’d hidden it to help" | | 17 | "We’d screamed at each other" | | 18 | "I opened my mouth to" | | 19 | "My blood ran cold." |
| | ratio | 0.625 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 31 | | totalSentences | 32 | | matches | | 0 | "I wrenched the third deadbolt" | | 1 | "The smell of spiced rice" | | 2 | "I pulled the door wide," | | 3 | "He stood on the landing," | | 4 | "His heterochromatic eyes, one molten" | | 5 | "I froze, my knuckles white" | | 6 | "Evan, the abusive ex I’d" | | 7 | "Eva had etched a ward" | | 8 | "I stepped back, and Lucien" | | 9 | "I slammed the door shut," | | 10 | "Every surface in the space" | | 11 | "Ptolemy, Eva’s plump tabby cat," | | 12 | "The cat hated every stranger" | | 13 | "The fact that he rubbed" | | 14 | "I leaned against the door," | | 15 | "He tapped his cane on" | | 16 | "I pushed off the door," | | 17 | "My thumb brushed the small" | | 18 | "His jaw tightened, the only" | | 19 | "He crossed the three feet" |
| | ratio | 0.969 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 32 | | matches | | 0 | "Before I could grab the" |
| | ratio | 0.031 | |
| 37.04% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 27 | | technicalSentenceCount | 4 | | matches | | 0 | "Eva had etched a ward into the doorframe of her cramped Brick Lane flat that was supposed to hide me from anyone who meant me harm, to keep them from even notic…" | | 1 | "My thumb brushed the small crescent scar on my left wrist, a nervous tick I’d never been able to shake, from the childhood bike crash that left the mark." | | 2 | "I’d spent the three weeks since our fight convincing myself he’d gone back to his life as an information broker, forgotten all about the part-time delivery driv…" | | 3 | "Lucien lifted a hand, brushing a strand of hair off my face, his thumb brushing the edge of my jaw, and I didn’t pull away." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 1 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |