| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 16 | | adverbTagCount | 1 | | adverbTags | | 0 | "Rory's voice cracked just [just]" |
| | dialogueSentences | 43 | | tagDensity | 0.372 | | leniency | 0.744 | | rawRatio | 0.063 | | effectiveRatio | 0.047 | |
| 84.83% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1318 | | totalAiIsmAdverbs | 4 | | found | | | highlights | | 0 | "suddenly" | | 1 | "precisely" | | 2 | "really" | | 3 | "slightly" |
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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) | |
| 73.44% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1318 | | totalAiIsms | 7 | | found | | | highlights | | 0 | "symphony" | | 1 | "echoed" | | 2 | "navigated" | | 3 | "silence" | | 4 | "intensity" | | 5 | "navigate" |
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| 66.67% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 2 | | maxInWindow | 2 | | found | | 0 | | label | "knuckles turned white" | | count | 1 |
| | 1 | | label | "hung in the air" | | count | 1 |
|
| | highlights | | 0 | "knuckles turned white" | | 1 | "hung in the air" |
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| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 71 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 71 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 98 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 44 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1313 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 12 | | unquotedAttributions | 0 | | matches | (empty) | |
| 95.98% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 26 | | wordCount | 833 | | uniqueNames | 8 | | maxNameDensity | 1.08 | | worstName | "Rory" | | maxWindowNameDensity | 2 | | worstWindowName | "Lucien" | | discoveredNames | | Rory | 9 | | Moreau | 1 | | London | 1 | | Ptolemy | 3 | | Lucien | 9 | | Celtic | 1 | | Brick | 1 | | Lane | 1 |
| | persons | | 0 | "Rory" | | 1 | "Moreau" | | 2 | "Ptolemy" | | 3 | "Lucien" |
| | places | | | globalScore | 0.96 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 61 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1313 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 98 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 38 | | mean | 34.55 | | std | 20.4 | | cv | 0.59 | | sampleLengths | | 0 | 75 | | 1 | 48 | | 2 | 34 | | 3 | 36 | | 4 | 25 | | 5 | 1 | | 6 | 54 | | 7 | 21 | | 8 | 35 | | 9 | 23 | | 10 | 54 | | 11 | 41 | | 12 | 15 | | 13 | 50 | | 14 | 31 | | 15 | 45 | | 16 | 50 | | 17 | 10 | | 18 | 43 | | 19 | 72 | | 20 | 26 | | 21 | 40 | | 22 | 9 | | 23 | 33 | | 24 | 21 | | 25 | 75 | | 26 | 20 | | 27 | 1 | | 28 | 3 | | 29 | 2 | | 30 | 68 | | 31 | 60 | | 32 | 53 | | 33 | 14 | | 34 | 32 | | 35 | 34 | | 36 | 25 | | 37 | 34 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 71 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 145 | | matches | (empty) | |
| 84.55% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 2 | | flaggedSentences | 2 | | totalSentences | 98 | | ratio | 0.02 | | matches | | 0 | "The amber one seemed to burn; the black one swallowed it." | | 1 | "His amber eye swirled with gold; the black one remained void." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 836 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 21 | | adverbRatio | 0.025119617224880382 | | lyAdverbCount | 6 | | lyAdverbRatio | 0.007177033492822967 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 98 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 98 | | mean | 13.4 | | std | 8.65 | | cv | 0.645 | | sampleLengths | | 0 | 3 | | 1 | 19 | | 2 | 15 | | 3 | 8 | | 4 | 7 | | 5 | 23 | | 6 | 16 | | 7 | 19 | | 8 | 13 | | 9 | 6 | | 10 | 16 | | 11 | 12 | | 12 | 6 | | 13 | 4 | | 14 | 5 | | 15 | 14 | | 16 | 7 | | 17 | 12 | | 18 | 11 | | 19 | 2 | | 20 | 1 | | 21 | 5 | | 22 | 15 | | 23 | 5 | | 24 | 29 | | 25 | 18 | | 26 | 3 | | 27 | 19 | | 28 | 16 | | 29 | 17 | | 30 | 6 | | 31 | 11 | | 32 | 14 | | 33 | 29 | | 34 | 3 | | 35 | 14 | | 36 | 24 | | 37 | 15 | | 38 | 8 | | 39 | 42 | | 40 | 12 | | 41 | 4 | | 42 | 15 | | 43 | 6 | | 44 | 9 | | 45 | 17 | | 46 | 13 | | 47 | 11 | | 48 | 6 | | 49 | 33 |
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| 60.20% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 6 | | diversityRatio | 0.3979591836734694 | | totalSentences | 98 | | uniqueOpeners | 39 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 69 | | matches | (empty) | | ratio | 0 | |
| 28.70% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 33 | | totalSentences | 69 | | matches | | 0 | "His charcoal suit looked immaculate" | | 1 | "He leaned on his ivory-handled" | | 2 | "His voice carried that smooth," | | 3 | "She didn't step back." | | 4 | "She didn't invite him in." | | 5 | "He pushed past her anyway." | | 6 | "He navigated the maze of" | | 7 | "he observed, running a gloved" | | 8 | "He turned to face her," | | 9 | "She stepped forward, forcing him" | | 10 | "He laughed, a short, sharp" | | 11 | "She hated the sound." | | 12 | "He towered over her, the" | | 13 | "He smelled of sandalwood and" | | 14 | "He reached out, his bare" | | 15 | "He didn't touch her, not" | | 16 | "He dropped his hand, gripping" | | 17 | "She shoved past him, pacing" | | 18 | "He moved again, cornering her" | | 19 | "She glared up at him," |
| | ratio | 0.478 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 66 | | totalSentences | 69 | | matches | | 0 | "The chain rattled." | | 1 | "The door swung inward, revealing" | | 2 | "Books stacked like precarious towers" | | 3 | "Scrolls spilled from baskets onto" | | 4 | "Ptolemy, the tabby cat, wove" | | 5 | "Lucien Moreau stood there, rain" | | 6 | "His charcoal suit looked immaculate" | | 7 | "He leaned on his ivory-handled" | | 8 | "His voice carried that smooth," | | 9 | "Rory gripped the door, knuckles" | | 10 | "She didn't step back." | | 11 | "She didn't invite him in." | | 12 | "The air between them crackled," | | 13 | "Lucien tilted his head, his" | | 14 | "The amber one seemed to" | | 15 | "He pushed past her anyway." | | 16 | "The cane hooked the door" | | 17 | "The movement was fluid, predatory." | | 18 | "He navigated the maze of" | | 19 | "he observed, running a gloved" |
| | ratio | 0.957 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 69 | | matches | (empty) | | ratio | 0 | |
| 12.99% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 33 | | technicalSentenceCount | 6 | | matches | | 0 | "Three deadbolts slammed back in rapid succession, a metallic symphony of paranoia that echoed off the narrow hallway walls." | | 1 | "His charcoal suit looked immaculate despite the London drizzle, the fabric repelling water as if offended by the weather." | | 2 | "His voice carried that smooth, continental edge that used to make her forget her own name." | | 3 | "He navigated the maze of research notes and ancient texts without knocking a single paper to the floor, as if he had mapped the chaos in his mind beforehand." | | 4 | "He broke the kiss only to trail his mouth down her neck, eliciting a gasp that echoed in the small room." | | 5 | "A genuine smile touched his lips, transforming his face from brooding fixer to the man she remembered." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 16 | | uselessAdditionCount | 5 | | matches | | 0 | "Lucien tilted, his heterochromatic eyes catching the light" | | 1 | "He reached out, his bare hand hovering near her cheek" | | 2 | "he began, his gaze dropping to her mouth" | | 3 | "she whispered, her fingers digging into his platinum hair" | | 4 | "Rory said, her voice steady despite the tremor in her hands," |
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| 80.23% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 5 | | fancyCount | 3 | | fancyTags | | 0 | "he observed (observe)" | | 1 | "she demanded (demand)" | | 2 | "she whispered (whisper)" |
| | dialogueSentences | 43 | | tagDensity | 0.116 | | leniency | 0.233 | | rawRatio | 0.6 | | effectiveRatio | 0.14 | |