| 46.15% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 6 | | adverbTagCount | 2 | | adverbTags | | 0 | "she said flatly [flatly]" | | 1 | "Eva said quickly [quickly]" |
| | dialogueSentences | 26 | | tagDensity | 0.231 | | leniency | 0.462 | | rawRatio | 0.333 | | effectiveRatio | 0.154 | |
| 92.09% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 632 | | totalAiIsmAdverbs | 1 | | 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) | |
| 76.27% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 632 | | totalAiIsms | 3 | | found | | | highlights | | 0 | "scanning" | | 1 | "weight" | | 2 | "etched" |
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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 | 1 | | narrationSentences | 52 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 52 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 71 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 28 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 626 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 6 | | unquotedAttributions | 0 | | matches | (empty) | |
| 9.61% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 35 | | wordCount | 463 | | uniqueNames | 9 | | maxNameDensity | 2.81 | | worstName | "Eva" | | maxWindowNameDensity | 4 | | worstWindowName | "Eva" | | discoveredNames | | Tube | 1 | | Harlow | 1 | | Quinn | 12 | | Kowalski | 1 | | Veil | 2 | | Market | 1 | | Eva | 13 | | Morris | 3 | | Compass | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Kowalski" | | 3 | "Market" | | 4 | "Eva" | | 5 | "Morris" | | 6 | "Compass" |
| | places | (empty) | | globalScore | 0.096 | | windowScore | 0.333 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 30 | | 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 | 626 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 71 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 30 | | mean | 20.87 | | std | 17.7 | | cv | 0.848 | | sampleLengths | | 0 | 62 | | 1 | 49 | | 2 | 12 | | 3 | 8 | | 4 | 27 | | 5 | 1 | | 6 | 14 | | 7 | 35 | | 8 | 3 | | 9 | 26 | | 10 | 56 | | 11 | 11 | | 12 | 3 | | 13 | 28 | | 14 | 11 | | 15 | 2 | | 16 | 24 | | 17 | 40 | | 18 | 10 | | 19 | 7 | | 20 | 17 | | 21 | 60 | | 22 | 10 | | 23 | 18 | | 24 | 15 | | 25 | 6 | | 26 | 42 | | 27 | 15 | | 28 | 9 | | 29 | 5 |
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| 98.52% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 52 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 90 | | matches | (empty) | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 6 | | semicolonCount | 0 | | flaggedSentences | 6 | | totalSentences | 71 | | ratio | 0.085 | | matches | | 0 | "The air in the abandoned Tube station was thick with the scent of damp stone and something metallic underneath—blood, maybe." | | 1 | "She glanced up as Quinn approached, tucking a loose curl of red hair behind her ear—her tell when she was nervous." | | 2 | "The tiles were cracked, but clean—no blood spatter, no drag marks." | | 3 | "The station was abandoned, but not empty—this was the Veil Market’s territory." | | 4 | "She’d heard it before—whispers after Morris died, the kind of stories cops told each other over bad coffee when they couldn’t explain what they’d seen." | | 5 | "Quinn reached into her coat pocket and pulled out a small brass compass—the Veil Compass, picked up from an informant last month." |
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| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 469 | | adjectiveStacks | 1 | | stackExamples | | | adverbCount | 12 | | adverbRatio | 0.0255863539445629 | | lyAdverbCount | 4 | | lyAdverbRatio | 0.008528784648187633 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 71 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 71 | | mean | 8.82 | | std | 6.77 | | cv | 0.767 | | sampleLengths | | 0 | 20 | | 1 | 25 | | 2 | 17 | | 3 | 28 | | 4 | 21 | | 5 | 12 | | 6 | 4 | | 7 | 4 | | 8 | 15 | | 9 | 12 | | 10 | 1 | | 11 | 6 | | 12 | 8 | | 13 | 2 | | 14 | 3 | | 15 | 6 | | 16 | 11 | | 17 | 13 | | 18 | 3 | | 19 | 15 | | 20 | 11 | | 21 | 15 | | 22 | 12 | | 23 | 15 | | 24 | 10 | | 25 | 4 | | 26 | 7 | | 27 | 4 | | 28 | 2 | | 29 | 1 | | 30 | 22 | | 31 | 6 | | 32 | 6 | | 33 | 5 | | 34 | 2 | | 35 | 10 | | 36 | 14 | | 37 | 3 | | 38 | 2 | | 39 | 25 | | 40 | 6 | | 41 | 4 | | 42 | 4 | | 43 | 6 | | 44 | 3 | | 45 | 4 | | 46 | 3 | | 47 | 6 | | 48 | 3 | | 49 | 5 |
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| 71.36% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 1 | | diversityRatio | 0.43661971830985913 | | totalSentences | 71 | | uniqueOpeners | 31 | |
| 68.03% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 49 | | matches | | | ratio | 0.02 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 11 | | totalSentences | 49 | | matches | | 0 | "She glanced up as Quinn" | | 1 | "She moved closer, scanning the" | | 2 | "She’d heard whispers of it," | | 3 | "It was a message." | | 4 | "She stood, brushing dust from" | | 5 | "She’d heard it before—whispers after" | | 6 | "she said flatly" | | 7 | "She believed it." | | 8 | "She hadn’t known what to" | | 9 | "Her grip was tight, her" | | 10 | "She pulled free." |
| | ratio | 0.224 | |
| 11.02% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 44 | | totalSentences | 49 | | matches | | 0 | "The air in the abandoned" | | 1 | "Detective Harlow Quinn adjusted the" | | 2 | "The platform was dimly lit" | | 3 | "Eva Kowalski stood near the" | | 4 | "She glanced up as Quinn" | | 5 | "Eva said, though there was" | | 6 | "Quinn ignored the jab." | | 7 | "Eva gestured to the center" | | 8 | "Eva hesitated, then lowered her" | | 9 | "That didn't track." | | 10 | "She moved closer, scanning the" | | 11 | "The tiles were cracked, but" | | 12 | "Eva shifted her weight" | | 13 | "Quinn crouched beside the outline," | | 14 | "The station was abandoned, but" | | 15 | "She’d heard whispers of it," | | 16 | "It was a message." | | 17 | "She stood, brushing dust from" | | 18 | "Quinn kept her voice level," | | 19 | "Eva’s fingers tightened around her" |
| | ratio | 0.898 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 49 | | matches | | 0 | "If this was their doing," | | 1 | "Now, watching the needle spin" |
| | ratio | 0.041 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 17 | | technicalSentenceCount | 1 | | matches | | 0 | "The platform was dimly lit by flickering emergency lights, casting long shadows that stretched like grasping fingers." |
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| 41.67% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 6 | | uselessAdditionCount | 1 | | matches | | 0 | "Quinn kept, but her gaze sharpened" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 3 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 26 | | tagDensity | 0.115 | | leniency | 0.231 | | rawRatio | 0 | | effectiveRatio | 0 | |