| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 17 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 45 | | tagDensity | 0.378 | | leniency | 0.756 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 86.91% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1528 | | totalAiIsmAdverbs | 4 | | found | | 0 | | | 1 | | adverb | "deliberately" | | count | 1 |
| | 2 | | | 3 | |
| | highlights | | 0 | "lightly" | | 1 | "deliberately" | | 2 | "very" | | 3 | "softly" |
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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) | |
| 28.01% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1528 | | totalAiIsms | 22 | | found | | | highlights | | 0 | "weight" | | 1 | "familiar" | | 2 | "comforting" | | 3 | "tinged" | | 4 | "chaotic" | | 5 | "whisper" | | 6 | "traced" | | 7 | "complex" | | 8 | "flicker" | | 9 | "charm" | | 10 | "stomach" | | 11 | "chill" | | 12 | "silence" | | 13 | "pulse" | | 14 | "pawn" | | 15 | "depths" | | 16 | "navigate" |
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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 | 1 | | narrationSentences | 113 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 2 | | narrationSentences | 113 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 138 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 32 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 1 | | markdownWords | 1 | | totalWords | 1513 | | ratio | 0.001 | | matches | | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 15 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 24 | | wordCount | 1102 | | uniqueNames | 12 | | maxNameDensity | 0.54 | | worstName | "Lucien" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Eva" | | discoveredNames | | Eva | 5 | | Moreau | 1 | | French | 1 | | Aurora | 1 | | Golden | 1 | | Empress | 1 | | Oxfords | 1 | | Lucien | 6 | | Marseille | 1 | | London | 1 | | Silas | 2 | | Ptolemy | 3 |
| | persons | | 0 | "Eva" | | 1 | "Moreau" | | 2 | "Aurora" | | 3 | "Empress" | | 4 | "Lucien" | | 5 | "Silas" | | 6 | "Ptolemy" |
| | places | | 0 | "Golden" | | 1 | "Marseille" | | 2 | "London" |
| | globalScore | 1 | | windowScore | 1 | |
| 89.76% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 83 | | glossingSentenceCount | 2 | | matches | | 0 | "felt like a shield she’d built" | | 1 | "looked like scabs on stone" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.661 | | wordCount | 1513 | | matches | | 0 | "Not for a weapon, but for a simple, cream-coloured envelope" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 138 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 53 | | mean | 28.55 | | std | 18.1 | | cv | 0.634 | | sampleLengths | | 0 | 7 | | 1 | 53 | | 2 | 9 | | 3 | 7 | | 4 | 52 | | 5 | 74 | | 6 | 27 | | 7 | 30 | | 8 | 6 | | 9 | 48 | | 10 | 14 | | 11 | 39 | | 12 | 23 | | 13 | 49 | | 14 | 70 | | 15 | 26 | | 16 | 13 | | 17 | 40 | | 18 | 53 | | 19 | 25 | | 20 | 26 | | 21 | 5 | | 22 | 20 | | 23 | 12 | | 24 | 32 | | 25 | 17 | | 26 | 54 | | 27 | 58 | | 28 | 9 | | 29 | 24 | | 30 | 14 | | 31 | 51 | | 32 | 13 | | 33 | 25 | | 34 | 40 | | 35 | 11 | | 36 | 16 | | 37 | 35 | | 38 | 54 | | 39 | 6 | | 40 | 23 | | 41 | 44 | | 42 | 35 | | 43 | 2 | | 44 | 27 | | 45 | 26 | | 46 | 3 | | 47 | 14 | | 48 | 34 | | 49 | 39 |
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| 99.05% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 113 | | matches | | 0 | "was slicked" | | 1 | "was gone" |
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| 83.72% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 3 | | totalVerbs | 172 | | matches | | 0 | "was fighting" | | 1 | "was laughing" | | 2 | "was being" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 4 | | semicolonCount | 0 | | flaggedSentences | 2 | | totalSentences | 138 | | ratio | 0.014 | | matches | | 0 | "And his eyes—one amber, one fathomless black—turned to meet hers." | | 1 | "He stopped inches from her spilled soup, his cane—that elegant prop that hid a thin, wicked blade—tapping once on the floor." |
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| 88.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 887 | | adjectiveStacks | 2 | | stackExamples | | 0 | "faint, ozone-tinged scent" | | 1 | "simple, cream-coloured envelope." |
| | adverbCount | 24 | | adverbRatio | 0.02705749718151071 | | lyAdverbCount | 8 | | lyAdverbRatio | 0.009019165727170236 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 138 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 138 | | mean | 10.96 | | std | 6.21 | | cv | 0.566 | | sampleLengths | | 0 | 7 | | 1 | 10 | | 2 | 20 | | 3 | 7 | | 4 | 16 | | 5 | 9 | | 6 | 7 | | 7 | 5 | | 8 | 12 | | 9 | 5 | | 10 | 1 | | 11 | 2 | | 12 | 10 | | 13 | 17 | | 14 | 18 | | 15 | 13 | | 16 | 20 | | 17 | 13 | | 18 | 10 | | 19 | 4 | | 20 | 14 | | 21 | 9 | | 22 | 10 | | 23 | 20 | | 24 | 6 | | 25 | 7 | | 26 | 20 | | 27 | 18 | | 28 | 3 | | 29 | 13 | | 30 | 1 | | 31 | 11 | | 32 | 7 | | 33 | 10 | | 34 | 11 | | 35 | 13 | | 36 | 10 | | 37 | 13 | | 38 | 22 | | 39 | 12 | | 40 | 2 | | 41 | 16 | | 42 | 11 | | 43 | 16 | | 44 | 7 | | 45 | 12 | | 46 | 8 | | 47 | 15 | | 48 | 11 | | 49 | 13 |
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| 50.00% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 11 | | diversityRatio | 0.34782608695652173 | | totalSentences | 138 | | uniqueOpeners | 48 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 105 | | matches | (empty) | | ratio | 0 | |
| 2.86% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 57 | | totalSentences | 105 | | matches | | 0 | "Her key jammed in the" | | 1 | "She’d left Eva’s only half" | | 2 | "She leaned her forehead against" | | 3 | "She pushed the door open" | | 4 | "It was out of place" | | 5 | "He stood by the cramped" | | 6 | "His charcoal suit was immaculate," | | 7 | "His voice was a low," | | 8 | "He hadn’t called her that" | | 9 | "Her own name, Aurora, felt" | | 10 | "Her bag, heavy with leftover" | | 11 | "He didn’t flinch." | | 12 | "It was a stupid thing" | | 13 | "He’d clearly bypassed three industrial-grade" | | 14 | "He didn’t smile" | | 15 | "She let out a short," | | 16 | "She used the old, familiar" | | 17 | "She kicked the door shut" | | 18 | "He sighed, a whisper of" | | 19 | "His gaze drifted from her" |
| | ratio | 0.543 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 97 | | totalSentences | 105 | | matches | | 0 | "Her key jammed in the" | | 1 | "Rory jiggled it, the worn" | | 2 | "She’d left Eva’s only half" | | 3 | "She leaned her forehead against" | | 4 | "The final bolt slid back" | | 5 | "She pushed the door open" | | 6 | "The scent hit her first." | | 7 | "This was something else entirely." | | 8 | "The faint, ozone-tinged scent of" | | 9 | "It was out of place" | | 10 | "He stood by the cramped" | | 11 | "His charcoal suit was immaculate," | | 12 | "The platinum blond hair was" | | 13 | "Lucien Moreau said" | | 14 | "His voice was a low," | | 15 | "He hadn’t called her that" | | 16 | "Her own name, Aurora, felt" | | 17 | "Laila belonged to a different" | | 18 | "All the air left the" | | 19 | "The word came out flat," |
| | ratio | 0.924 | |
| 95.24% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 105 | | matches | | 0 | "Now the damn lock was" | | 1 | "As if he’d been waiting" |
| | ratio | 0.019 | |
| 59.80% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 43 | | technicalSentenceCount | 5 | | matches | | 0 | "Laila belonged to a different girl, a girl who’d believed a charming stranger with mismatched eyes and an ivory-handled cane." | | 1 | "He finally moved, a slow, deliberate pacing that made the small room feel even smaller." | | 2 | "He stopped inches from her spilled soup, his cane—that elegant prop that hid a thin, wicked blade—tapping once on the floor." | | 3 | "The gruff, kind man who owned the bar downstairs, who’d rented her this flat without a deposit when she’d arrived in London with nothing but a bruised heart and…" | | 4 | "The one thing that would override her pride, her hurt, her very sensible fear." |
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| 66.18% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 17 | | uselessAdditionCount | 2 | | matches | | 0 | "The word came out, dead" | | 1 | "She took, the soup seeping into the toe of her boot" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 5 | | fancyCount | 2 | | fancyTags | | 0 | "she whispered (whisper)" | | 1 | "he agreed (agree)" |
| | dialogueSentences | 45 | | tagDensity | 0.111 | | leniency | 0.222 | | rawRatio | 0.4 | | effectiveRatio | 0.089 | |