| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 15 | | adverbTagCount | 1 | | adverbTags | | | dialogueSentences | 43 | | tagDensity | 0.349 | | leniency | 0.698 | | rawRatio | 0.067 | | effectiveRatio | 0.047 | |
| 88.70% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1327 | | totalAiIsmAdverbs | 3 | | 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) | |
| 51.02% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1327 | | totalAiIsms | 13 | | found | | | highlights | | 0 | "whisper" | | 1 | "rhythmic" | | 2 | "weight" | | 3 | "echoed" | | 4 | "processed" | | 5 | "predator" | | 6 | "throb" | | 7 | "could feel" | | 8 | "pulse" | | 9 | "racing" | | 10 | "unreadable" | | 11 | "tension" | | 12 | "silence" |
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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 | 86 | | matches | (empty) | |
| 93.02% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 2 | | narrationSentences | 86 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 114 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 37 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 1 | | markdownWords | 1 | | totalWords | 1315 | | ratio | 0.001 | | matches | | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 10 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 28 | | wordCount | 987 | | uniqueNames | 9 | | maxNameDensity | 0.91 | | worstName | "Lucien" | | maxWindowNameDensity | 2 | | worstWindowName | "Lucien" | | discoveredNames | | Eva | 2 | | Moreau | 1 | | Brick | 2 | | Lane | 2 | | Mayfair | 1 | | English | 1 | | Lucien | 9 | | Cardiff | 1 | | Aurora | 9 |
| | persons | | 0 | "Eva" | | 1 | "Moreau" | | 2 | "Lucien" | | 3 | "Aurora" |
| | places | | 0 | "Brick" | | 1 | "Lane" | | 2 | "Mayfair" | | 3 | "Cardiff" |
| | globalScore | 1 | | windowScore | 1 | |
| 39.71% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 68 | | glossingSentenceCount | 3 | | matches | | 0 | "looked like he was standing in a boardroo" | | 1 | "smelled like rain on burnt iron" | | 2 | "smelled like rain and burnt iron had found" |
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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 | 1315 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 2 | | totalSentences | 114 | | matches | | 0 | "knew that voice" | | 1 | "hated that it" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 52 | | mean | 25.29 | | std | 19.65 | | cv | 0.777 | | sampleLengths | | 0 | 25 | | 1 | 49 | | 2 | 1 | | 3 | 26 | | 4 | 56 | | 5 | 10 | | 6 | 37 | | 7 | 12 | | 8 | 76 | | 9 | 32 | | 10 | 31 | | 11 | 3 | | 12 | 4 | | 13 | 1 | | 14 | 48 | | 15 | 25 | | 16 | 18 | | 17 | 3 | | 18 | 46 | | 19 | 64 | | 20 | 2 | | 21 | 4 | | 22 | 49 | | 23 | 32 | | 24 | 6 | | 25 | 36 | | 26 | 45 | | 27 | 35 | | 28 | 54 | | 29 | 7 | | 30 | 34 | | 31 | 2 | | 32 | 42 | | 33 | 8 | | 34 | 3 | | 35 | 48 | | 36 | 5 | | 37 | 38 | | 38 | 7 | | 39 | 46 | | 40 | 4 | | 41 | 22 | | 42 | 4 | | 43 | 37 | | 44 | 36 | | 45 | 3 | | 46 | 20 | | 47 | 2 | | 48 | 13 | | 49 | 48 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 86 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 174 | | matches | | 0 | "was standing" | | 1 | "was sleeping" |
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| 17.54% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 5 | | semicolonCount | 0 | | flaggedSentences | 5 | | totalSentences | 114 | | ratio | 0.044 | | matches | | 0 | "She also knew the scent that accompanied it—cedar, leather, and something faintly metallic that smelled like rain on burnt iron." | | 1 | "He inspected the red stain on the ceramic counter—the remains of a takeaway curry spilled two days ago that she hadn't had the heart to scrub off." | | 2 | "The heterochromia caught the dim light from the window—amber and obsidian." | | 3 | "On it, there was no name, only a number and a symbol—a jagged sigil that looked uncomfortably like a closed eye." | | 4 | "She looked down at her reflection in the glass—dark hair, tired eyes, the scar on her wrist catching the light." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 998 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 26 | | adverbRatio | 0.026052104208416832 | | lyAdverbCount | 10 | | lyAdverbRatio | 0.01002004008016032 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 114 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 114 | | mean | 11.54 | | std | 7.55 | | cv | 0.655 | | sampleLengths | | 0 | 11 | | 1 | 14 | | 2 | 12 | | 3 | 17 | | 4 | 9 | | 5 | 11 | | 6 | 1 | | 7 | 11 | | 8 | 15 | | 9 | 6 | | 10 | 4 | | 11 | 26 | | 12 | 20 | | 13 | 10 | | 14 | 11 | | 15 | 5 | | 16 | 6 | | 17 | 15 | | 18 | 12 | | 19 | 16 | | 20 | 22 | | 21 | 17 | | 22 | 21 | | 23 | 11 | | 24 | 7 | | 25 | 14 | | 26 | 16 | | 27 | 15 | | 28 | 3 | | 29 | 4 | | 30 | 1 | | 31 | 20 | | 32 | 6 | | 33 | 3 | | 34 | 19 | | 35 | 9 | | 36 | 4 | | 37 | 12 | | 38 | 18 | | 39 | 3 | | 40 | 4 | | 41 | 15 | | 42 | 27 | | 43 | 8 | | 44 | 18 | | 45 | 32 | | 46 | 6 | | 47 | 2 | | 48 | 4 | | 49 | 21 |
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| 47.08% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 13 | | diversityRatio | 0.3508771929824561 | | totalSentences | 114 | | uniqueOpeners | 40 | |
| 40.65% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 82 | | matches | | 0 | "Then she checked the time." |
| | ratio | 0.012 | |
| 0.49% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 45 | | totalSentences | 82 | | matches | | 0 | "She cracked the wood-paneled door" | | 1 | "He didn't look like he" | | 2 | "He looked like he was" | | 3 | "His voice wasn't a whisper," | | 4 | "It slid through the crack" | | 5 | "She knew that voice." | | 6 | "She knew the way it" | | 7 | "She also knew the scent" | | 8 | "She unlocked the deadbolt fully" | | 9 | "He simply stepped past her." | | 10 | "He adjusted his umbrella, tapping" | | 11 | "He took in the shoe" | | 12 | "He didn't even flinch at" | | 13 | "He rested his ivory-handled cane" | | 14 | "She didn't offer him a" | | 15 | "It didn't wake up." | | 16 | "It wasn't a question." | | 17 | "He walked over to the" | | 18 | "He inspected the red stain" | | 19 | "she said, turning to face" |
| | ratio | 0.549 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 78 | | totalSentences | 82 | | matches | | 0 | "The deadbolt on Eva’s front" | | 1 | "Aurora pulled the steel bar" | | 2 | "She cracked the wood-paneled door" | | 3 | "Lucien Moreau stood there, a" | | 4 | "He didn't look like he" | | 5 | "He looked like he was" | | 6 | "His voice wasn't a whisper," | | 7 | "It slid through the crack" | | 8 | "Aurora’s hand tightened on the" | | 9 | "She knew that voice." | | 10 | "She knew the way it" | | 11 | "She also knew the scent" | | 12 | "She unlocked the deadbolt fully" | | 13 | "Lucien didn't step aside to" | | 14 | "He simply stepped past her." | | 15 | "The movement was too fluid," | | 16 | "He adjusted his umbrella, tapping" | | 17 | "Aurora said, pushing the door" | | 18 | "Lucien replied, his gaze sweeping" | | 19 | "He took in the shoe" |
| | ratio | 0.951 | |
| 60.98% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 82 | | matches | | 0 | "Now he was close enough" |
| | ratio | 0.012 | |
| 91.84% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 42 | | technicalSentenceCount | 3 | | matches | | 0 | "A half-demon fixer who smelled like rain and burnt iron had found her address from the vague movements of a golden delivery van." | | 1 | "She had spent three years forging a new life, one where she was just a quiet delivery girl and not the girl who had burned down the bridge between her and the s…" | | 2 | "It was a heat that didn't belong in a damp, curry-scented flat on Brick Lane." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 15 | | uselessAdditionCount | 5 | | matches | | 0 | "Lucien replied, his gaze sweeping the cramped entrance" | | 1 | "she said, turning to face him" | | 2 | "she said, her voice steadier than she felt" | | 3 | "He raised, his long fingers hovering near her cheek" | | 4 | "He reached, this time pulling out a card" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 6 | | fancyCount | 1 | | fancyTags | | 0 | "Aurora corrected (correct)" |
| | dialogueSentences | 43 | | tagDensity | 0.14 | | leniency | 0.279 | | rawRatio | 0.167 | | effectiveRatio | 0.047 | |