| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 17 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 40 | | tagDensity | 0.425 | | leniency | 0.85 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 87.23% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1175 | | 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) | |
| 91.49% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1175 | | totalAiIsms | 2 | | found | | | highlights | | |
| 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 | 62 | | matches | | |
| 96.77% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 1 | | narrationSentences | 62 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 83 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 59 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 3 | | markdownWords | 15 | | totalWords | 1185 | | ratio | 0.013 | | matches | | 0 | "I have nothing to say to you." | | 1 | "charm" | | 2 | "I am not here to fight you." |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 20 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 23 | | wordCount | 808 | | uniqueNames | 8 | | maxNameDensity | 0.99 | | worstName | "Lucien" | | maxWindowNameDensity | 2 | | worstWindowName | "Rory" | | discoveredNames | | Moreau | 1 | | Lucien | 8 | | Rory | 7 | | Ptolemy | 2 | | Edinburgh | 1 | | Eva | 2 | | Five | 1 | | Smaller | 1 |
| | persons | | 0 | "Moreau" | | 1 | "Lucien" | | 2 | "Rory" | | 3 | "Eva" |
| | places | | | globalScore | 1 | | windowScore | 1 | |
| 28.05% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 41 | | glossingSentenceCount | 2 | | matches | | 0 | "not quite a smile" | | 1 | "felt like another woman's life" |
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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 | 1185 | | matches | (empty) | |
| 86.35% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 2 | | totalSentences | 83 | | matches | | 0 | "hated that her" | | 1 | "chose that moment" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 39 | | mean | 30.38 | | std | 27.05 | | cv | 0.89 | | sampleLengths | | 0 | 45 | | 1 | 7 | | 2 | 85 | | 3 | 31 | | 4 | 6 | | 5 | 38 | | 6 | 64 | | 7 | 7 | | 8 | 5 | | 9 | 2 | | 10 | 28 | | 11 | 9 | | 12 | 66 | | 13 | 20 | | 14 | 67 | | 15 | 7 | | 16 | 90 | | 17 | 5 | | 18 | 3 | | 19 | 4 | | 20 | 64 | | 21 | 17 | | 22 | 35 | | 23 | 59 | | 24 | 72 | | 25 | 25 | | 26 | 9 | | 27 | 38 | | 28 | 56 | | 29 | 4 | | 30 | 90 | | 31 | 20 | | 32 | 4 | | 33 | 29 | | 34 | 22 | | 35 | 7 | | 36 | 5 | | 37 | 24 | | 38 | 16 |
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| 99.60% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 62 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 152 | | matches | (empty) | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 9 | | semicolonCount | 1 | | flaggedSentences | 9 | | totalSentences | 83 | | ratio | 0.108 | | matches | | 0 | "Lucien Moreau filled the narrow stairwell like he'd been poured into it — charcoal suit immaculate despite the rain that had clearly chased him here, water beading on the shoulders and sliding off as if the fabric itself disdained to be touched." | | 1 | "His amber eye caught the hallway's weak bulb and gleamed; the black one drank the light entirely." | | 2 | "He could have simply waited her out — Lucien was very good at waiting." | | 3 | "The amusement faded from his face, and that was worse, somehow — Lucien without his armor of irony was a man she'd only glimpsed a handful of times, and never on purpose." | | 4 | "She'd rehearsed it, in the weeks after Edinburgh — the cool, clean refusal she'd deliver if he ever turned up again, the door closing with a satisfying finality." | | 5 | "Eva's research had colonized every flat surface — towers of books, scrolls weighted down with chipped mugs, sheaves of notes annotated in three different inks." | | 6 | "Lucien set his cane against the edge of the cluttered table, deliberate, and the gesture undid her a little — because he never let go of that cane, not in company, not when there was the faintest chance he might need the blade inside it." | | 7 | "The rain had darkened his platinum hair at the temples, and a single drop ran down the side of his neck, and she wanted — absurdly, infuriatingly — to wipe it away with her thumb." | | 8 | "Something eased in his shoulders — relief, carefully hidden, but she'd learned to read him once, and the skill hadn't left her." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 800 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 31 | | adverbRatio | 0.03875 | | lyAdverbCount | 10 | | lyAdverbRatio | 0.0125 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 83 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 83 | | mean | 14.28 | | std | 11.48 | | cv | 0.804 | | sampleLengths | | 0 | 8 | | 1 | 37 | | 2 | 7 | | 3 | 42 | | 4 | 10 | | 5 | 16 | | 6 | 17 | | 7 | 10 | | 8 | 14 | | 9 | 7 | | 10 | 4 | | 11 | 2 | | 12 | 20 | | 13 | 14 | | 14 | 4 | | 15 | 6 | | 16 | 37 | | 17 | 7 | | 18 | 14 | | 19 | 7 | | 20 | 5 | | 21 | 2 | | 22 | 7 | | 23 | 21 | | 24 | 5 | | 25 | 4 | | 26 | 32 | | 27 | 11 | | 28 | 23 | | 29 | 6 | | 30 | 14 | | 31 | 5 | | 32 | 28 | | 33 | 24 | | 34 | 9 | | 35 | 1 | | 36 | 7 | | 37 | 17 | | 38 | 25 | | 39 | 24 | | 40 | 24 | | 41 | 5 | | 42 | 3 | | 43 | 4 | | 44 | 4 | | 45 | 28 | | 46 | 8 | | 47 | 24 | | 48 | 9 | | 49 | 8 |
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| 64.66% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 8 | | diversityRatio | 0.4457831325301205 | | totalSentences | 83 | | uniqueOpeners | 37 | |
| 66.67% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 50 | | matches | | 0 | "Then he turned to face" |
| | ratio | 0.02 | |
| 36.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 23 | | totalSentences | 50 | | matches | | 0 | "Her breath stopped somewhere behind" | | 1 | "His amber eye caught the" | | 2 | "he said, by way of" | | 3 | "His voice carried that low," | | 4 | "She kept one hand on" | | 5 | "He could have charmed his" | | 6 | "He could have simply waited" | | 7 | "His mouth curved, not quite" | | 8 | "She lifted her chin" | | 9 | "She should have said no." | | 10 | "She'd rehearsed it, in the" | | 11 | "She'd practiced it in the" | | 12 | "*I have nothing to say" | | 13 | "She stepped back and let" | | 14 | "He moved past her into" | | 15 | "His voice was very quiet" | | 16 | "It meant *I am not" | | 17 | "he said, He spread his" | | 18 | "She looked away, at Ptolemy" | | 19 | "She turned back to him." |
| | ratio | 0.46 | |
| 20.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 44 | | totalSentences | 50 | | matches | | 0 | "The third deadbolt was always" | | 1 | "Rory had to wrench it" | | 2 | "Her breath stopped somewhere behind" | | 3 | "Lucien Moreau filled the narrow" | | 4 | "The other he'd raised, knuckles" | | 5 | "His amber eye caught the" | | 6 | "he said, by way of" | | 7 | "His voice carried that low," | | 8 | "Lucien tilted his head toward" | | 9 | "Ptolemy regarded the visitor with" | | 10 | "Rory didn't move from the" | | 11 | "She kept one hand on" | | 12 | "He could have charmed his" | | 13 | "He could have simply waited" | | 14 | "His mouth curved, not quite" | | 15 | "She lifted her chin" | | 16 | "The amusement faded from his" | | 17 | "Rain ticked against the window" | | 18 | "She should have said no." | | 19 | "She'd rehearsed it, in the" |
| | ratio | 0.88 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 50 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 27 | | technicalSentenceCount | 1 | | matches | | 0 | "Lucien Moreau filled the narrow stairwell like he'd been poured into it — charcoal suit immaculate despite the rain that had clearly chased him here, water bead…" |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 17 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 12 | | fancyCount | 2 | | fancyTags | | 0 | "she whispered (whisper)" | | 1 | "Lucien agreed (agree)" |
| | dialogueSentences | 40 | | tagDensity | 0.3 | | leniency | 0.6 | | rawRatio | 0.167 | | effectiveRatio | 0.1 | |