| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 6 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 34 | | tagDensity | 0.176 | | leniency | 0.353 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1171 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 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) | |
| 57.30% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1171 | | totalAiIsms | 10 | | found | | | highlights | | 0 | "traced" | | 1 | "pulsed" | | 2 | "thundered" | | 3 | "trembled" | | 4 | "flickered" | | 5 | "pulse" | | 6 | "silence" | | 7 | "velvet" |
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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 | 105 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 105 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 135 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 33 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1162 | | 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 | 34 | | wordCount | 915 | | uniqueNames | 18 | | maxNameDensity | 0.98 | | worstName | "Lucien" | | maxWindowNameDensity | 2 | | worstWindowName | "Lucien" | | discoveredNames | | Carter | 1 | | Moreau | 1 | | Sichuan | 1 | | Golden | 2 | | Empress | 2 | | Lucien | 9 | | Cardiff | 2 | | Water | 1 | | Yu-Fei | 1 | | Irish | 1 | | Evan | 1 | | Tuesday | 1 | | Marseille-born | 1 | | French | 1 | | Arabic | 1 | | Brick | 1 | | Lane | 1 | | Rory | 6 |
| | persons | | 0 | "Carter" | | 1 | "Moreau" | | 2 | "Empress" | | 3 | "Lucien" | | 4 | "Water" | | 5 | "Evan" | | 6 | "Marseille-born" | | 7 | "Rory" |
| | places | | 0 | "Sichuan" | | 1 | "Golden" | | 2 | "Cardiff" | | 3 | "Yu-Fei" | | 4 | "French" | | 5 | "Brick" | | 6 | "Lane" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 62 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 27.88% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 2 | | per1kWords | 1.721 | | wordCount | 1162 | | matches | | 0 | "neither his coat nor" | | 1 | "not from fear of him, but from the want" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 135 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 50 | | mean | 23.24 | | std | 21.61 | | cv | 0.93 | | sampleLengths | | 0 | 9 | | 1 | 60 | | 2 | 52 | | 3 | 3 | | 4 | 62 | | 5 | 45 | | 6 | 7 | | 7 | 2 | | 8 | 5 | | 9 | 25 | | 10 | 66 | | 11 | 16 | | 12 | 8 | | 13 | 9 | | 14 | 32 | | 15 | 11 | | 16 | 2 | | 17 | 23 | | 18 | 4 | | 19 | 63 | | 20 | 7 | | 21 | 9 | | 22 | 60 | | 23 | 24 | | 24 | 40 | | 25 | 8 | | 26 | 15 | | 27 | 5 | | 28 | 59 | | 29 | 32 | | 30 | 9 | | 31 | 2 | | 32 | 60 | | 33 | 16 | | 34 | 37 | | 35 | 27 | | 36 | 5 | | 37 | 3 | | 38 | 62 | | 39 | 34 | | 40 | 2 | | 41 | 6 | | 42 | 8 | | 43 | 19 | | 44 | 60 | | 45 | 7 | | 46 | 4 | | 47 | 3 | | 48 | 3 | | 49 | 32 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 105 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 149 | | matches | (empty) | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 8 | | semicolonCount | 2 | | flaggedSentences | 8 | | totalSentences | 135 | | ratio | 0.059 | | matches | | 0 | "One eye burned amber; the other drank the light, black as a burnt-out wick." | | 1 | "Sesame oil and Sichuan pepper ghosted her clothes; the Golden Empress did not rinse out." | | 2 | "The crescent scar on her left wrist—the childhood souvenir from a Cardiff bicycle chain—faced outward, silver in the dim light." | | 3 | "He stood close enough that she caught the scent of him—dark cologne cut with sulphur, the signature of wherever he’d spent his night." | | 4 | "A thin red line crosshatched her thumb—paper cut from flattening delivery boxes at Yu-Fei’s." | | 5 | "Platinum hair, slicked back severe, drew all attention to the hunger in his stare—one eye amber as a warning light, the other an abyss." | | 6 | "The unsaid thing hung between them—older than Evan, older than demon blood." | | 7 | "A laugh—low, startled—escaped him." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 146 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 3 | | adverbRatio | 0.02054794520547945 | | lyAdverbCount | 0 | | lyAdverbRatio | 0 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 135 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 135 | | mean | 8.61 | | std | 6.43 | | cv | 0.747 | | sampleLengths | | 0 | 3 | | 1 | 6 | | 2 | 12 | | 3 | 5 | | 4 | 11 | | 5 | 18 | | 6 | 14 | | 7 | 11 | | 8 | 16 | | 9 | 15 | | 10 | 10 | | 11 | 3 | | 12 | 4 | | 13 | 3 | | 14 | 13 | | 15 | 27 | | 16 | 8 | | 17 | 7 | | 18 | 8 | | 19 | 16 | | 20 | 21 | | 21 | 4 | | 22 | 3 | | 23 | 2 | | 24 | 3 | | 25 | 2 | | 26 | 11 | | 27 | 14 | | 28 | 5 | | 29 | 6 | | 30 | 12 | | 31 | 20 | | 32 | 10 | | 33 | 6 | | 34 | 7 | | 35 | 9 | | 36 | 5 | | 37 | 2 | | 38 | 8 | | 39 | 9 | | 40 | 5 | | 41 | 23 | | 42 | 3 | | 43 | 1 | | 44 | 8 | | 45 | 3 | | 46 | 2 | | 47 | 3 | | 48 | 14 | | 49 | 6 |
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| 55.31% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 7 | | diversityRatio | 0.362962962962963 | | totalSentences | 135 | | uniqueOpeners | 49 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 99 | | matches | (empty) | | ratio | 0 | |
| 30.10% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 47 | | totalSentences | 99 | | matches | | 0 | "Her straight black hair, damp" | | 1 | "Her bright blue eyes held" | | 2 | "She did not move." | | 3 | "He stepped forward." | | 4 | "His chest brushed hers, wool" | | 5 | "His cane tapped once against" | | 6 | "She’d scrubbed the kitchenette twice" | | 7 | "Her jaw tightened." | | 8 | "She walked to the sink." | | 9 | "Her flats squeaked on the" | | 10 | "She gripped the laminate edge" | | 11 | "He knew the geography of" | | 12 | "She cranked the tap" | | 13 | "He stood close enough that" | | 14 | "She didn’t look." | | 15 | "She raised it to her" | | 16 | "He caught her wrist." | | 17 | "His thumb pressed the scar’s" | | 18 | "His skin ran fever-hot, demon-hot," | | 19 | "She’d trembled then, not from" |
| | ratio | 0.475 | |
| 50.91% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 81 | | totalSentences | 99 | | matches | | 0 | "The deadbolt turned." | | 1 | "Aurora Carter pulled the door" | | 2 | "Lucien Moreau filled the threshold." | | 3 | "Rainwater dripped from his charcoal" | | 4 | "Rory braced her shoulder against" | | 5 | "Her straight black hair, damp" | | 6 | "Sesame oil and Sichuan pepper" | | 7 | "Her bright blue eyes held" | | 8 | "She did not move." | | 9 | "He stepped forward." | | 10 | "His chest brushed hers, wool" | | 11 | "The flat above" | | 12 | "Lucien removed neither his coat" | | 13 | "His cane tapped once against" | | 14 | "She’d scrubbed the kitchenette twice" | | 15 | "Rory shut the door." | | 16 | "The latch clicked." | | 17 | "Her jaw tightened." | | 18 | "Lucien’s jaw tightened" | | 19 | "She walked to the sink." |
| | ratio | 0.818 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 99 | | matches | | 0 | "To knee his thigh." | | 1 | "To crawl out the rattling" |
| | ratio | 0.02 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 36 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 6 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |