| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 3 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 9 | | tagDensity | 0.333 | | leniency | 0.667 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 89.07% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 915 | | totalAiIsmAdverbs | 2 | | found | | | highlights | | 0 | "cautiously" | | 1 | "perfectly" |
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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) | |
| 50.82% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 915 | | totalAiIsms | 9 | | found | | | highlights | | 0 | "treacherous" | | 1 | "standard" | | 2 | "shimmered" | | 3 | "gloom" | | 4 | "comfortable" | | 5 | "scanning" | | 6 | "stomach" | | 7 | "familiar" |
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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 | 83 | | matches | (empty) | |
| 91.22% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 2 | | narrationSentences | 83 | | filterMatches | | | hedgeMatches | | |
| 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 | 40 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 902 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 2 | | unquotedAttributions | 0 | | matches | (empty) | |
| 66.86% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 28 | | wordCount | 842 | | uniqueNames | 11 | | maxNameDensity | 1.66 | | worstName | "Harlow" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Harlow" | | discoveredNames | | Harlow | 14 | | Quinn | 1 | | London | 1 | | Veil | 1 | | Market | 1 | | Morris | 5 | | Tube | 1 | | Saint | 1 | | Christopher | 1 | | Tomás | 1 | | Herrera | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Morris" | | 3 | "Saint" | | 4 | "Christopher" | | 5 | "Tomás" | | 6 | "Herrera" |
| | places | | | globalScore | 0.669 | | windowScore | 0.833 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 60 | | glossingSentenceCount | 1 | | matches | | 0 | "sections that seemed to cater to different supernatural needs—fairy artifacts, werewolf suppression charms, vampire blood substitutes" |
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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 | 902 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 88 | | matches | (empty) | |
| 86.35% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 28 | | mean | 32.21 | | std | 14.57 | | cv | 0.452 | | sampleLengths | | 0 | 50 | | 1 | 3 | | 2 | 41 | | 3 | 38 | | 4 | 34 | | 5 | 37 | | 6 | 36 | | 7 | 42 | | 8 | 36 | | 9 | 43 | | 10 | 44 | | 11 | 39 | | 12 | 40 | | 13 | 46 | | 14 | 50 | | 15 | 29 | | 16 | 23 | | 17 | 8 | | 18 | 39 | | 19 | 17 | | 20 | 4 | | 21 | 8 | | 22 | 30 | | 23 | 4 | | 24 | 33 | | 25 | 53 | | 26 | 40 | | 27 | 35 |
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| 92.58% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 83 | | matches | | 0 | "been mentioned" | | 1 | "was gone" | | 2 | "was blocked" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 142 | | matches | | |
| 12.99% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 6 | | semicolonCount | 0 | | flaggedSentences | 4 | | totalSentences | 88 | | ratio | 0.045 | | matches | | 0 | "The suspect—a lanky youth with a distinctive snake tattoo curling around his neck—laughed over his shoulder and darted down a narrow alley." | | 1 | "The entry requirement—a bone token—had been mentioned in a report she'd memorized." | | 2 | "Harlow removed the pendant she kept in her pocket—a small carved piece of bone confiscated from an unrelated case months ago." | | 3 | "They passed through sections that seemed to cater to different supernatural needs—fairy artifacts, werewolf suppression charms, vampire blood substitutes." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 855 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 23 | | adverbRatio | 0.026900584795321637 | | lyAdverbCount | 10 | | lyAdverbRatio | 0.011695906432748537 | |
| 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 | 10.25 | | std | 6.84 | | cv | 0.667 | | sampleLengths | | 0 | 14 | | 1 | 20 | | 2 | 16 | | 3 | 3 | | 4 | 22 | | 5 | 19 | | 6 | 16 | | 7 | 9 | | 8 | 6 | | 9 | 5 | | 10 | 2 | | 11 | 5 | | 12 | 10 | | 13 | 1 | | 14 | 7 | | 15 | 11 | | 16 | 7 | | 17 | 8 | | 18 | 2 | | 19 | 14 | | 20 | 3 | | 21 | 3 | | 22 | 9 | | 23 | 9 | | 24 | 18 | | 25 | 13 | | 26 | 3 | | 27 | 14 | | 28 | 12 | | 29 | 7 | | 30 | 10 | | 31 | 19 | | 32 | 21 | | 33 | 10 | | 34 | 12 | | 35 | 13 | | 36 | 9 | | 37 | 22 | | 38 | 14 | | 39 | 11 | | 40 | 14 | | 41 | 7 | | 42 | 22 | | 43 | 11 | | 44 | 4 | | 45 | 19 | | 46 | 11 | | 47 | 12 | | 48 | 7 | | 49 | 3 |
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| 65.91% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 2 | | diversityRatio | 0.4090909090909091 | | totalSentences | 88 | | uniqueOpeners | 36 | |
| 44.44% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 75 | | matches | | 0 | "Instead, a figure with close-cropped" |
| | ratio | 0.013 | |
| 97.33% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 23 | | totalSentences | 75 | | matches | | 0 | "He knew these streets too" | | 1 | "He disappeared around a corner." | | 2 | "Her fingers closed around the" | | 3 | "Her gaze swept the area," | | 4 | "She heard the muffled sounds" | | 5 | "She'd heard whispers of it," | | 6 | "It fit perfectly into a" | | 7 | "She drew her torch, its" | | 8 | "He stood at a stall," | | 9 | "She moved forward, keeping to" | | 10 | "Her suspect finished his transaction" | | 11 | "They passed through sections that" | | 12 | "She risked a glance through" | | 13 | "Her suspect was gone." | | 14 | "Her former partner." | | 15 | "He dropped the dagger he'd" | | 16 | "He reached a dead-end corridor" | | 17 | "Her voice was raw" | | 18 | "He raised a hand, and" | | 19 | "His form began to dissolve," |
| | ratio | 0.307 | |
| 46.67% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 62 | | totalSentences | 75 | | matches | | 0 | "The suspect vaulted over the" | | 1 | "Detective Harlow Quinn followed without" | | 2 | "The rain had turned London's" | | 3 | "The suspect—a lanky youth with" | | 4 | "Harlow's sharp jaw tightened as" | | 5 | "The alley opened briefly onto" | | 6 | "Harlow's brown eyes tracked the" | | 7 | "He knew these streets too" | | 8 | "He disappeared around a corner." | | 9 | "Harlow picked up speed, her" | | 10 | "Her fingers closed around the" | | 11 | "The corner led to a" | | 12 | "Her gaze swept the area," | | 13 | "A loose brick." | | 14 | "A hidden entrance." | | 15 | "Harlow approached cautiously, her years" | | 16 | "The brick was warm to" | | 17 | "She heard the muffled sounds" | | 18 | "The Veil Market." | | 19 | "She'd heard whispers of it," |
| | ratio | 0.827 | |
| 66.67% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 75 | | matches | | 0 | "If she followed, she'd be" |
| | ratio | 0.013 | |
| 69.60% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 39 | | technicalSentenceCount | 4 | | matches | | 0 | "She'd heard whispers of it, the supernatural underground market that moved with the moon." | | 1 | "Creatures that shouldn't exist moved alongside humans who looked too comfortable in their presence." | | 2 | "They passed through sections that seemed to cater to different supernatural needs—fairy artifacts, werewolf suppression charms, vampire blood substitutes." | | 3 | "In his place lay a single object on the dusty floor: a Saint Christopher medallion, identical to one she'd seen in a case file months ago, connected to a parame…" |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 3 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |