| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 11 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 47 | | tagDensity | 0.234 | | leniency | 0.468 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 88.68% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1325 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | 0 | "slightly" | | 1 | "very" | | 2 | "sweetly" |
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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) | |
| 77.36% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1325 | | totalAiIsms | 6 | | found | | | highlights | | 0 | "silence" | | 1 | "weight" | | 2 | "clenching" | | 3 | "tracing" | | 4 | "stomach" | | 5 | "could feel" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "stomach dropped/sank" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 59 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 59 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 94 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 88 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1325 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 16 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 20 | | wordCount | 644 | | uniqueNames | 13 | | maxNameDensity | 0.62 | | worstName | "Rory" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Rory" | | discoveredNames | | Eva | 1 | | Charcoal | 1 | | French | 1 | | Three | 1 | | Rory | 4 | | Lucien | 4 | | Moreau | 2 | | March | 1 | | Golden | 1 | | Empress | 1 | | Carter | 1 | | Warm | 1 | | Evan | 1 |
| | persons | | 0 | "Eva" | | 1 | "Rory" | | 2 | "Lucien" | | 3 | "Moreau" | | 4 | "Carter" | | 5 | "Evan" |
| | places | | | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 36 | | 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 | 1325 | | matches | (empty) | |
| 95.74% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 2 | | totalSentences | 94 | | matches | | 0 | "hated that she" | | 1 | "used that name" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 50 | | mean | 26.5 | | std | 25.81 | | cv | 0.974 | | sampleLengths | | 0 | 9 | | 1 | 72 | | 2 | 21 | | 3 | 10 | | 4 | 3 | | 5 | 22 | | 6 | 31 | | 7 | 6 | | 8 | 5 | | 9 | 58 | | 10 | 20 | | 11 | 16 | | 12 | 1 | | 13 | 79 | | 14 | 5 | | 15 | 6 | | 16 | 48 | | 17 | 9 | | 18 | 49 | | 19 | 10 | | 20 | 11 | | 21 | 61 | | 22 | 10 | | 23 | 31 | | 24 | 24 | | 25 | 67 | | 26 | 6 | | 27 | 71 | | 28 | 15 | | 29 | 1 | | 30 | 20 | | 31 | 37 | | 32 | 10 | | 33 | 2 | | 34 | 80 | | 35 | 72 | | 36 | 8 | | 37 | 97 | | 38 | 30 | | 39 | 61 | | 40 | 1 | | 41 | 4 | | 42 | 8 | | 43 | 5 | | 44 | 1 | | 45 | 25 | | 46 | 33 | | 47 | 29 | | 48 | 19 | | 49 | 6 |
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| 99.32% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 59 | | matches | | |
| 0.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 4 | | totalVerbs | 112 | | matches | | 0 | "was tasting" | | 1 | "were drinking" | | 2 | "were shaking" | | 3 | "was coming" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 94 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 676 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 17 | | adverbRatio | 0.02514792899408284 | | lyAdverbCount | 4 | | lyAdverbRatio | 0.005917159763313609 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 94 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 94 | | mean | 14.1 | | std | 15.11 | | cv | 1.072 | | sampleLengths | | 0 | 9 | | 1 | 32 | | 2 | 5 | | 3 | 4 | | 4 | 31 | | 5 | 4 | | 6 | 17 | | 7 | 10 | | 8 | 3 | | 9 | 7 | | 10 | 7 | | 11 | 4 | | 12 | 4 | | 13 | 31 | | 14 | 6 | | 15 | 5 | | 16 | 24 | | 17 | 7 | | 18 | 14 | | 19 | 4 | | 20 | 9 | | 21 | 20 | | 22 | 16 | | 23 | 1 | | 24 | 18 | | 25 | 8 | | 26 | 9 | | 27 | 44 | | 28 | 5 | | 29 | 6 | | 30 | 5 | | 31 | 15 | | 32 | 28 | | 33 | 9 | | 34 | 49 | | 35 | 10 | | 36 | 11 | | 37 | 8 | | 38 | 53 | | 39 | 10 | | 40 | 5 | | 41 | 5 | | 42 | 21 | | 43 | 4 | | 44 | 20 | | 45 | 27 | | 46 | 40 | | 47 | 6 | | 48 | 54 | | 49 | 4 |
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| 86.17% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 4 | | diversityRatio | 0.5425531914893617 | | totalSentences | 94 | | uniqueOpeners | 51 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 49 | | matches | | 0 | "Of course it didn't." | | 1 | "Somewhere down there a dozen" |
| | ratio | 0.041 | |
| 56.73% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 20 | | totalSentences | 49 | | matches | | 0 | "She slammed the door." | | 1 | "His cane slid into the" | | 2 | "She leaned her weight into" | | 3 | "She eased the pressure off" | | 4 | "She filed that away." | | 5 | "She laughed, and it came" | | 6 | "She hadn't taken it off." | | 7 | "He tilted his head, and" | | 8 | "He straightened the cuff of" | | 9 | "She hated that she still" | | 10 | "He only used her full" | | 11 | "He didn't move" | | 12 | "He paused, and Lucien Moreau" | | 13 | "He spoke four languages and" | | 14 | "His voice dropped, and the" | | 15 | "His hand closed over hers" | | 16 | "His thumb found the small" | | 17 | "She snatched her hand back." | | 18 | "Her stomach dropped through the" | | 19 | "She pulled the door wide," |
| | ratio | 0.408 | |
| 62.04% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 39 | | totalSentences | 49 | | matches | | 0 | "The chain caught before she'd" | | 1 | "Rory had thrown the door" | | 2 | "The gap widened four inches." | | 3 | "Platinum hair, slicked back." | | 4 | "She slammed the door." | | 5 | "His cane slid into the" | | 6 | "She leaned her weight into" | | 7 | "The cane didn't so much" | | 8 | "She eased the pressure off" | | 9 | "Charcoal suit, pressed to a" | | 10 | "She filed that away." | | 11 | "The name in his mouth," | | 12 | "The shout surprised them both." | | 13 | "Lucien lowered his voice, and" | | 14 | "She laughed, and it came" | | 15 | "The chain was still on." | | 16 | "She hadn't taken it off." | | 17 | "That was the only reason" | | 18 | "He tilted his head, and" | | 19 | "He straightened the cuff of" |
| | ratio | 0.796 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 49 | | matches | | | ratio | 0.02 | |
| 23.81% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 18 | | technicalSentenceCount | 3 | | matches | | 0 | "Somewhere down there a dozen strangers were drinking and laughing and none of them could hear her heart slamming against her ribs like a fist on a door." | | 1 | "Nobody knew it, except the people from that night in March, the ones who'd seen what she'd done to the creature in the alley behind the Golden Empress, the ones…" | | 2 | "His thumb found the small crescent scar on her wrist without looking, the way he always found it, the way Evan had once found it too, tracing it with a knife he…" |
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| 79.55% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 11 | | uselessAdditionCount | 1 | | matches | | 0 | "She eased, enough to look at him through the gap properly" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 4 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 47 | | tagDensity | 0.085 | | leniency | 0.17 | | rawRatio | 0.25 | | effectiveRatio | 0.043 | |