| 94.74% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 4 | | adverbTagCount | 1 | | adverbTags | | 0 | "He stepped aside [aside]" |
| | dialogueSentences | 19 | | tagDensity | 0.211 | | leniency | 0.421 | | rawRatio | 0.25 | | effectiveRatio | 0.105 | |
| 88.08% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 839 | | totalAiIsmAdverbs | 2 | | 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) | |
| 46.36% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 839 | | totalAiIsms | 9 | | found | | 0 | | | 1 | | | 2 | | word | "practiced ease" | | count | 1 |
| | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | word | "down her spine" | | count | 1 |
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| | highlights | | 0 | "scanned" | | 1 | "glinting" | | 2 | "practiced ease" | | 3 | "intricate" | | 4 | "echoed" | | 5 | "gleaming" | | 6 | "scanning" | | 7 | "chill" | | 8 | "down her spine" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "sent a shiver through" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 74 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 74 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 88 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 23 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 1 | | markdownWords | 5 | | totalWords | 838 | | ratio | 0.006 | | matches | | 0 | "Veil Market, Last Entry Midnight." |
| |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 4 | | unquotedAttributions | 0 | | matches | (empty) | |
| 73.40% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 32 | | wordCount | 718 | | uniqueNames | 13 | | maxNameDensity | 1.53 | | worstName | "Quinn" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Herrera" | | discoveredNames | | Soho | 1 | | Raven | 1 | | Nest | 1 | | Harlow | 1 | | Quinn | 11 | | Saint | 1 | | Christopher | 1 | | Herrera | 10 | | Market | 1 | | Last | 1 | | Entry | 1 | | Tube | 1 | | Camden | 1 |
| | persons | | 0 | "Raven" | | 1 | "Harlow" | | 2 | "Quinn" | | 3 | "Saint" | | 4 | "Christopher" | | 5 | "Herrera" | | 6 | "Camden" |
| | places | | | globalScore | 0.734 | | windowScore | 0.833 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 59 | | glossingSentenceCount | 1 | | matches | | 0 | "smelled like burnt sugar" |
| |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 838 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 88 | | matches | (empty) | |
| 98.28% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 27 | | mean | 31.04 | | std | 15.33 | | cv | 0.494 | | sampleLengths | | 0 | 62 | | 1 | 49 | | 2 | 41 | | 3 | 41 | | 4 | 27 | | 5 | 12 | | 6 | 52 | | 7 | 21 | | 8 | 42 | | 9 | 41 | | 10 | 53 | | 11 | 60 | | 12 | 34 | | 13 | 29 | | 14 | 10 | | 15 | 28 | | 16 | 4 | | 17 | 18 | | 18 | 38 | | 19 | 34 | | 20 | 14 | | 21 | 19 | | 22 | 15 | | 23 | 18 | | 24 | 29 | | 25 | 25 | | 26 | 22 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 74 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 132 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 88 | | ratio | 0 | | matches | (empty) | |
| 99.71% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 719 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 29 | | adverbRatio | 0.04033379694019471 | | lyAdverbCount | 11 | | lyAdverbRatio | 0.015299026425591099 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 88 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 88 | | mean | 9.52 | | std | 5.12 | | cv | 0.538 | | sampleLengths | | 0 | 23 | | 1 | 18 | | 2 | 1 | | 3 | 11 | | 4 | 2 | | 5 | 7 | | 6 | 15 | | 7 | 13 | | 8 | 21 | | 9 | 10 | | 10 | 14 | | 11 | 3 | | 12 | 14 | | 13 | 17 | | 14 | 14 | | 15 | 10 | | 16 | 5 | | 17 | 3 | | 18 | 7 | | 19 | 5 | | 20 | 7 | | 21 | 9 | | 22 | 3 | | 23 | 2 | | 24 | 12 | | 25 | 13 | | 26 | 8 | | 27 | 7 | | 28 | 6 | | 29 | 4 | | 30 | 10 | | 31 | 11 | | 32 | 9 | | 33 | 19 | | 34 | 14 | | 35 | 12 | | 36 | 14 | | 37 | 13 | | 38 | 2 | | 39 | 11 | | 40 | 13 | | 41 | 16 | | 42 | 13 | | 43 | 10 | | 44 | 8 | | 45 | 12 | | 46 | 23 | | 47 | 7 | | 48 | 9 | | 49 | 15 |
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| 57.20% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 3 | | diversityRatio | 0.36363636363636365 | | totalSentences | 88 | | uniqueOpeners | 32 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 68 | | matches | | 0 | "Instead, he disappeared through a" | | 1 | "Finally, she cornered him near" | | 2 | "Instead, he slipped something into" |
| | ratio | 0.044 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 20 | | totalSentences | 68 | | matches | | 0 | "He’d moved fast, but not" | | 1 | "She broke into a jog," | | 2 | "He bolted, weaving through the" | | 3 | "He ducked into an alley," | | 4 | "She glanced down." | | 5 | "She pocketed the token and" | | 6 | "She hesitated, her instincts screaming" | | 7 | "She wasn’t about to let" | | 8 | "She moved cautiously, scanning the" | | 9 | "She spotted him near a" | | 10 | "She turned to see a" | | 11 | "She pulled her wrist free." | | 12 | "He smiled, revealing too many" | | 13 | "He stepped aside, his gaze" | | 14 | "She didn’t waste time responding." | | 15 | "He smirked, though there was" | | 16 | "He barked a laugh." | | 17 | "His smile faded." | | 18 | "He glanced over her shoulder," | | 19 | "She stepped back, her hand" |
| | ratio | 0.294 | |
| 4.12% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 62 | | totalSentences | 68 | | matches | | 0 | "The Soho pavement glistened under" | | 1 | "Detective Harlow Quinn wiped the" | | 2 | "The flash of a Saint" | | 3 | "He’d moved fast, but not" | | 4 | "She broke into a jog," | | 5 | "Herrera glanced over his shoulder," | | 6 | "He bolted, weaving through the" | | 7 | "Quinn shouted, though she knew" | | 8 | "The words barely carried over" | | 9 | "Herrera didn’t falter." | | 10 | "He ducked into an alley," | | 11 | "Quinn followed, her worn leather" | | 12 | "The alley narrowed, the walls" | | 13 | "Herrera was already halfway across," | | 14 | "Something crunched under her boot." | | 15 | "She glanced down." | | 16 | "A bone token, carved with" | | 17 | "Herrera’s voice echoed faintly ahead." | | 18 | "She pocketed the token and" | | 19 | "Quinn reached it seconds later," |
| | ratio | 0.912 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 68 | | matches | (empty) | | ratio | 0 | |
| 83.33% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 36 | | technicalSentenceCount | 3 | | matches | | 0 | "He bolted, weaving through the crowd with the practiced ease of someone who knew these streets better than his own shadow." | | 1 | "A woman with violet eyes and a snake coiled around her neck offered her a vial of something that smelled like burnt sugar." | | 2 | "Herrera leaned against the wall, his chest rising and falling rapidly." |
| |
| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 4 | | uselessAdditionCount | 2 | | matches | | 0 | "He stepped aside, his gaze lingering" | | 1 | "He glanced, his expression hardening" |
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| 44.74% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 2 | | fancyCount | 2 | | fancyTags | | 0 | "Quinn shouted (shout)" | | 1 | "he whispered (whisper)" |
| | dialogueSentences | 19 | | tagDensity | 0.105 | | leniency | 0.211 | | rawRatio | 1 | | effectiveRatio | 0.211 | |