| 94.74% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 23 | | adverbTagCount | 4 | | adverbTags | | 0 | "Lucien turned away [away]" | | 1 | "She turned away [away]" | | 2 | "Lucien said finally [finally]" | | 3 | "he said softly [softly]" |
| | dialogueSentences | 76 | | tagDensity | 0.303 | | leniency | 0.605 | | rawRatio | 0.174 | | effectiveRatio | 0.105 | |
| 76.84% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1727 | | totalAiIsmAdverbs | 8 | | found | | | highlights | | 0 | "precisely" | | 1 | "truly" | | 2 | "slowly" | | 3 | "very" | | 4 | "really" | | 5 | "carefully" | | 6 | "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) | |
| 73.94% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1727 | | totalAiIsms | 9 | | found | | | highlights | | 0 | "perfect" | | 1 | "otherworldly" | | 2 | "warmth" | | 3 | "silence" | | 4 | "potential" | | 5 | "grave" | | 6 | "constructed" |
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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 | 126 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 126 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 179 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 39 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 5 | | markdownWords | 66 | | totalWords | 1713 | | ratio | 0.039 | | matches | | 0 | "Ms. Carter," | | 1 | "A mutual acquaintance informs us you seek answers about your lineage. We possess documentation regarding your maternal grandmother’s service contract with House Morgenstern from 1958 to 1963." | | 2 | "Should you wish to review these materials, present yourself at 47 St. Mary’s Path, Bloomsbury, tomorrow evening at nine o’clock sharp." | | 3 | "Come alone. Bring this letter as proof of invitation." | | 4 | "P.S. Your companion’s interference would be... unwise." |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 32 | | unquotedAttributions | 0 | | matches | (empty) | |
| 83.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 51 | | wordCount | 1120 | | uniqueNames | 23 | | maxNameDensity | 1.25 | | worstName | "Lucien" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Lucien" | | discoveredNames | | Aurora | 8 | | Moreau | 3 | | London | 1 | | Marseille | 1 | | One | 1 | | Cardiff | 2 | | Eva | 2 | | Brick | 2 | | Lane | 2 | | Lucien | 14 | | House | 1 | | Morgenstern | 1 | | St | 1 | | Path | 1 | | Bloomsbury | 1 | | Brendan | 1 | | Carter | 2 | | Evan | 2 | | Mrs | 1 | | Cheung | 1 | | Rory | 1 | | Silence | 1 | | Friday | 1 |
| | persons | | 0 | "Aurora" | | 1 | "Moreau" | | 2 | "One" | | 3 | "Eva" | | 4 | "Lucien" | | 5 | "Brendan" | | 6 | "Carter" | | 7 | "Evan" | | 8 | "Mrs" | | 9 | "Cheung" | | 10 | "Rory" | | 11 | "Silence" |
| | places | | 0 | "London" | | 1 | "Marseille" | | 2 | "Cardiff" | | 3 | "Brick" | | 4 | "Lane" | | 5 | "House" | | 6 | "Morgenstern" | | 7 | "Friday" |
| | globalScore | 0.875 | | windowScore | 0.833 | |
| 0.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 66 | | glossingSentenceCount | 5 | | matches | | 0 | "looked like someone had taken her memory" | | 1 | "looked like the kind of place you could d" | | 2 | "felt like admitting defeat" | | 3 | "looked like actual blood pressed into the" | | 4 | "felt like a guest in her own life, why" |
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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 | 1713 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 179 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 102 | | mean | 16.79 | | std | 14.84 | | cv | 0.883 | | sampleLengths | | 0 | 20 | | 1 | 6 | | 2 | 79 | | 3 | 1 | | 4 | 22 | | 5 | 9 | | 6 | 5 | | 7 | 3 | | 8 | 43 | | 9 | 67 | | 10 | 12 | | 11 | 7 | | 12 | 43 | | 13 | 6 | | 14 | 1 | | 15 | 25 | | 16 | 5 | | 17 | 12 | | 18 | 37 | | 19 | 13 | | 20 | 16 | | 21 | 28 | | 22 | 18 | | 23 | 5 | | 24 | 34 | | 25 | 5 | | 26 | 38 | | 27 | 4 | | 28 | 18 | | 29 | 5 | | 30 | 2 | | 31 | 27 | | 32 | 21 | | 33 | 9 | | 34 | 7 | | 35 | 8 | | 36 | 23 | | 37 | 14 | | 38 | 26 | | 39 | 6 | | 40 | 12 | | 41 | 20 | | 42 | 8 | | 43 | 9 | | 44 | 26 | | 45 | 20 | | 46 | 3 | | 47 | 31 | | 48 | 9 | | 49 | 20 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 126 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 202 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 3 | | semicolonCount | 0 | | flaggedSentences | 2 | | totalSentences | 179 | | ratio | 0.011 | | matches | | 0 | "Not fear—not exactly—but the coiled readiness of someone who’d learned the hard way that gifts from men like Lucien Moreau always came with strings attached." | | 1 | "The wax seal bore a symbol she didn’t recognize—three interlocking circles with a drop of what looked like actual blood pressed into the center." |
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| 88.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1046 | | adjectiveStacks | 2 | | stackExamples | | 0 | "small crescent-shaped scar" | | 1 | "flat, cream-colored envelope" |
| | adverbCount | 38 | | adverbRatio | 0.036328871892925434 | | lyAdverbCount | 8 | | lyAdverbRatio | 0.0076481835564053535 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 179 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 179 | | mean | 9.57 | | std | 8.16 | | cv | 0.853 | | sampleLengths | | 0 | 20 | | 1 | 6 | | 2 | 29 | | 3 | 18 | | 4 | 32 | | 5 | 1 | | 6 | 7 | | 7 | 5 | | 8 | 10 | | 9 | 9 | | 10 | 5 | | 11 | 3 | | 12 | 7 | | 13 | 32 | | 14 | 4 | | 15 | 11 | | 16 | 11 | | 17 | 15 | | 18 | 30 | | 19 | 3 | | 20 | 6 | | 21 | 3 | | 22 | 7 | | 23 | 21 | | 24 | 22 | | 25 | 6 | | 26 | 1 | | 27 | 23 | | 28 | 2 | | 29 | 5 | | 30 | 9 | | 31 | 3 | | 32 | 15 | | 33 | 22 | | 34 | 13 | | 35 | 6 | | 36 | 10 | | 37 | 3 | | 38 | 25 | | 39 | 11 | | 40 | 7 | | 41 | 4 | | 42 | 1 | | 43 | 20 | | 44 | 14 | | 45 | 5 | | 46 | 4 | | 47 | 10 | | 48 | 24 | | 49 | 4 |
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| 60.34% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 7 | | diversityRatio | 0.3854748603351955 | | totalSentences | 179 | | uniqueOpeners | 69 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 4 | | totalSentences | 111 | | matches | | 0 | "Then she thought of Mrs." | | 1 | "More than the burn scars" | | 2 | "More than the need to" | | 3 | "Then she pulled back." |
| | ratio | 0.036 | |
| 25.41% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 54 | | totalSentences | 111 | | matches | | 0 | "He looked like someone had" | | 1 | "She leaned against the doorframe," | | 2 | "His heterochromatic eyes watched her" | | 3 | "It looked like the kind" | | 4 | "She didn’t offer to take" | | 5 | "He entered, his ivory-handled cane" | | 6 | "He paused by the window" | | 7 | "They stood a meter apart" | | 8 | "He reached into his inner" | | 9 | "Her body tensed." | | 10 | "He produced a flat, cream-colored" | | 11 | "She didn't take it." | | 12 | "She took the envelope." | | 13 | "She slid out a single" | | 14 | "We possess documentation regarding your" | | 15 | "Your companion’s interference would be..." | | 16 | "She looked up." | | 17 | "she said, her throat tight" | | 18 | "She folded the letter back" | | 19 | "Her hands were steady." |
| | ratio | 0.486 | |
| 23.06% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 97 | | totalSentences | 111 | | matches | | 0 | "The third deadbolt clicked open," | | 1 | "Lucien Moreau stood on the" | | 2 | "The smell of rain clung" | | 3 | "He looked like someone had" | | 4 | "The tailored charcoal suit was" | | 5 | "The accent was softer than" | | 6 | "She leaned against the doorframe," | | 7 | "His heterochromatic eyes watched her" | | 8 | "The flat behind her was" | | 9 | "Books on demonic contracts spilled" | | 10 | "Ptolemy the tabby was curled" | | 11 | "It looked like the kind" | | 12 | "Aurora stepped back." | | 13 | "The movement felt like admitting" | | 14 | "She didn’t offer to take" | | 15 | "He entered, his ivory-handled cane" | | 16 | "He paused by the window" | | 17 | "Lucien turned away from the" | | 18 | "They stood a meter apart" | | 19 | "Aurora crossed her arms over" |
| | ratio | 0.874 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 111 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 35 | | technicalSentenceCount | 2 | | matches | | 0 | "He entered, his ivory-handled cane tapping a rhythm on the floorboards that matched the ticking of the clock above Eva’s fireplace." | | 1 | "Yu-Fei Cheung, who’d hired her as a delivery girl despite the restaurant having no such position open until Rory walked in." |
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| 81.52% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 23 | | uselessAdditionCount | 2 | | matches | | 0 | "she said, her throat tight" | | 1 | "he whispered, his breath stirring the hair at her temple," |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 9 | | fancyCount | 2 | | fancyTags | | 0 | "she repeated (repeat)" | | 1 | "he whispered (whisper)" |
| | dialogueSentences | 76 | | tagDensity | 0.118 | | leniency | 0.237 | | rawRatio | 0.222 | | effectiveRatio | 0.053 | |