| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 13 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 33 | | tagDensity | 0.394 | | leniency | 0.788 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 87.08% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1161 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | 0 | "quickly" | | 1 | "softly" | | 2 | "suddenly" |
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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) | |
| 56.93% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1161 | | totalAiIsms | 10 | | found | | | highlights | | 0 | "mechanical" | | 1 | "intensity" | | 2 | "weight" | | 3 | "silk" | | 4 | "tracing" | | 5 | "tenderness" | | 6 | "echoed" | | 7 | "silence" | | 8 | "footsteps" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 47 | | matches | (empty) | |
| 82.07% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 1 | | narrationSentences | 47 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 67 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 41 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1161 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 14 | | unquotedAttributions | 0 | | matches | (empty) | |
| 66.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 40 | | wordCount | 790 | | uniqueNames | 13 | | maxNameDensity | 1.65 | | worstName | "Aurora" | | maxWindowNameDensity | 3 | | worstWindowName | "Aurora" | | discoveredNames | | Aurora | 13 | | Carter | 1 | | Lucien | 1 | | Moreau | 1 | | Eva | 4 | | Brick | 2 | | Lane | 2 | | Ptolemy | 2 | | Luc | 10 | | Cardiff | 1 | | London | 1 | | Marseille | 1 | | Avaros | 1 |
| | persons | | 0 | "Aurora" | | 1 | "Carter" | | 2 | "Lucien" | | 3 | "Moreau" | | 4 | "Eva" | | 5 | "Luc" |
| | places | | 0 | "Brick" | | 1 | "Lane" | | 2 | "Cardiff" | | 3 | "London" | | 4 | "Marseille" | | 5 | "Avaros" |
| | globalScore | 0.677 | | windowScore | 0.667 | |
| 18.42% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 38 | | glossingSentenceCount | 2 | | matches | | 0 | "suit that seemed to drink the dim light, his slicked-back platinum hair catching the faint glow from the paper lantern inside" | | 1 | "felt like a threat" |
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| 0.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 7 | | per1kWords | 6.029 | | wordCount | 1161 | | matches | | 0 | "not roughly, but with the certainty of a man who had crossed realms" | | 1 | "not from pain, but from the sudden, violent pull of attraction" | | 2 | "not gentle, not an apology, but a possession, dark" | | 3 | "not an apology, but a possession, dark" | | 4 | "not to push him away, but to hold him, to anchor herself in the reality of this danger" | | 5 | "not casual, not random, but deliberate, matched to the rhythm of three deadbolts being t" | | 6 | "not random, but deliberate, matched to the rhythm of three deadbolts being t" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 67 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 41 | | mean | 28.32 | | std | 16.01 | | cv | 0.565 | | sampleLengths | | 0 | 31 | | 1 | 48 | | 2 | 4 | | 3 | 20 | | 4 | 26 | | 5 | 44 | | 6 | 8 | | 7 | 11 | | 8 | 26 | | 9 | 22 | | 10 | 50 | | 11 | 33 | | 12 | 14 | | 13 | 43 | | 14 | 29 | | 15 | 20 | | 16 | 37 | | 17 | 1 | | 18 | 23 | | 19 | 20 | | 20 | 31 | | 21 | 27 | | 22 | 40 | | 23 | 15 | | 24 | 40 | | 25 | 10 | | 26 | 64 | | 27 | 42 | | 28 | 11 | | 29 | 45 | | 30 | 1 | | 31 | 67 | | 32 | 29 | | 33 | 19 | | 34 | 28 | | 35 | 60 | | 36 | 31 | | 37 | 27 | | 38 | 11 | | 39 | 32 | | 40 | 21 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 47 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 124 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 67 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 800 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 23 | | adverbRatio | 0.02875 | | lyAdverbCount | 4 | | lyAdverbRatio | 0.005 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 67 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 67 | | mean | 17.33 | | std | 9.9 | | cv | 0.571 | | sampleLengths | | 0 | 31 | | 1 | 26 | | 2 | 22 | | 3 | 4 | | 4 | 20 | | 5 | 18 | | 6 | 8 | | 7 | 23 | | 8 | 21 | | 9 | 8 | | 10 | 11 | | 11 | 8 | | 12 | 18 | | 13 | 8 | | 14 | 14 | | 15 | 3 | | 16 | 18 | | 17 | 29 | | 18 | 9 | | 19 | 24 | | 20 | 14 | | 21 | 30 | | 22 | 13 | | 23 | 12 | | 24 | 17 | | 25 | 13 | | 26 | 7 | | 27 | 4 | | 28 | 19 | | 29 | 14 | | 30 | 1 | | 31 | 23 | | 32 | 10 | | 33 | 10 | | 34 | 9 | | 35 | 22 | | 36 | 18 | | 37 | 9 | | 38 | 21 | | 39 | 19 | | 40 | 7 | | 41 | 8 | | 42 | 40 | | 43 | 10 | | 44 | 36 | | 45 | 28 | | 46 | 3 | | 47 | 39 | | 48 | 11 | | 49 | 23 |
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| 50.75% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 1 | | diversityRatio | 0.31343283582089554 | | totalSentences | 67 | | uniqueOpeners | 21 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 42 | | matches | | 0 | "Then his mouth found hers," | | 1 | "Then the door swung open" |
| | ratio | 0.048 | |
| 67.62% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 16 | | totalSentences | 42 | | matches | | 0 | "He wore a tailored charcoal" | | 1 | "His eyes, one amber and" | | 2 | "His voice carried the polished" | | 3 | "She moved past him into" | | 4 | "She caught his movement out" | | 5 | "She was not the girl" | | 6 | "She glanced at Ptolemy, who" | | 7 | "He reached for her, not" | | 8 | "His fingers closed around her" | | 9 | "He stepped closer, his tailored" | | 10 | "She should have pushed him" | | 11 | "she asked, her voice low," | | 12 | "His thumb brushed her wrist" | | 13 | "He pulled her closer, and" | | 14 | "She was cool-headed, intelligent, quick" | | 15 | "she said, but her voice" |
| | ratio | 0.381 | |
| 31.43% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 36 | | totalSentences | 42 | | matches | | 0 | "The deadbolt slid back with" | | 1 | "He wore a tailored charcoal" | | 2 | "His eyes, one amber and" | | 3 | "Luc stepped inside, closing the" | | 4 | "His voice carried the polished" | | 5 | "Aurora pulled her straight shoulder-length" | | 6 | "The scent of turmeric and" | | 7 | "Luc's ivory-handled cane tapped once" | | 8 | "The thin blade concealed within" | | 9 | "Aurora's jaw tightened." | | 10 | "She moved past him into" | | 11 | "Every surface was covered with" | | 12 | "She caught his movement out" | | 13 | "The flat smelled of ink" | | 14 | "Luc stopped near the bookshelf," | | 15 | "Aurora lifted her chin." | | 16 | "She was not the girl" | | 17 | "Aurora felt the blood drain" | | 18 | "She glanced at Ptolemy, who" | | 19 | "Luc corrected, his voice soft" |
| | ratio | 0.857 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 42 | | matches | (empty) | | ratio | 0 | |
| 37.04% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 27 | | technicalSentenceCount | 4 | | matches | | 0 | "He wore a tailored charcoal suit that seemed to drink the dim light, his slicked-back platinum hair catching the faint glow from the paper lantern inside." | | 1 | "His eyes, one amber and one black, locked onto her bright blue ones with an intensity that made her straighten her shoulders." | | 2 | "She was not the girl who had fled Cardiff for London at Eva's behest." | | 3 | "His fingers closed around her left wrist, tracing the crescent scar with a tenderness that felt like a threat." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 13 | | uselessAdditionCount | 4 | | matches | | 0 | "Luc corrected, his voice soft and relentless" | | 1 | "she asked, her voice low, dangerous" | | 2 | "He pulled, and the world shrank to the space between them, to the books and scrolls, to the cat's hissing and the distant noise of Brick Lane" | | 3 | "she said, but her voice had lost its sharp edge" |
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| 89.39% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 8 | | fancyCount | 2 | | fancyTags | | 0 | "Luc corrected (correct)" | | 1 | "Luc murmured (murmur)" |
| | dialogueSentences | 33 | | tagDensity | 0.242 | | leniency | 0.485 | | rawRatio | 0.25 | | effectiveRatio | 0.121 | |