| 94.74% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 16 | | adverbTagCount | 2 | | adverbTags | | 0 | "Quinn’s voice scraped like [like]" | | 1 | "she finally admitted [finally]" |
| | dialogueSentences | 38 | | tagDensity | 0.421 | | leniency | 0.842 | | rawRatio | 0.125 | | effectiveRatio | 0.105 | |
| 70.53% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1018 | | totalAiIsmAdverbs | 6 | | found | | | highlights | | 0 | "carefully" | | 1 | "gently" | | 2 | "very" |
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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) | |
| 31.24% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1018 | | totalAiIsms | 14 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | word | "down her spine" | | count | 1 |
| | 12 | |
| | highlights | | 0 | "gloom" | | 1 | "hulking" | | 2 | "velvet" | | 3 | "etched" | | 4 | "eyebrow" | | 5 | "whisper" | | 6 | "analyzed" | | 7 | "delved" | | 8 | "gleaming" | | 9 | "furrowed" | | 10 | "chill" | | 11 | "down her spine" | | 12 | "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 | 1 | | narrationSentences | 86 | | matches | | |
| 93.02% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 2 | | narrationSentences | 86 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 108 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 33 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 5 | | markdownWords | 5 | | totalWords | 1018 | | ratio | 0.005 | | matches | | 0 | "avoided" | | 1 | "you" | | 2 | "back" | | 3 | "something" | | 4 | "seal" |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 9 | | unquotedAttributions | 0 | | matches | (empty) | |
| 16.07% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 46 | | wordCount | 672 | | uniqueNames | 10 | | maxNameDensity | 2.68 | | worstName | "Quinn" | | maxWindowNameDensity | 4 | | worstWindowName | "Quinn" | | discoveredNames | | Tuesday | 1 | | Harlow | 1 | | Quinn | 18 | | Camden | 1 | | Veil | 1 | | Market | 1 | | Davies | 7 | | Finch | 7 | | Eva | 8 | | Kowalski | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Davies" | | 3 | "Finch" | | 4 | "Eva" | | 5 | "Kowalski" |
| | places | (empty) | | globalScore | 0.161 | | windowScore | 0.333 | |
| 66.67% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 60 | | glossingSentenceCount | 2 | | matches | | 0 | "felt like a dare" | | 1 | "seemed disturbed almost *avoided" |
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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 | 1018 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 108 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 47 | | mean | 21.66 | | std | 16.75 | | cv | 0.773 | | sampleLengths | | 0 | 80 | | 1 | 52 | | 2 | 29 | | 3 | 8 | | 4 | 39 | | 5 | 46 | | 6 | 16 | | 7 | 16 | | 8 | 44 | | 9 | 8 | | 10 | 16 | | 11 | 22 | | 12 | 9 | | 13 | 52 | | 14 | 6 | | 15 | 18 | | 16 | 1 | | 17 | 35 | | 18 | 24 | | 19 | 14 | | 20 | 16 | | 21 | 14 | | 22 | 27 | | 23 | 2 | | 24 | 26 | | 25 | 21 | | 26 | 12 | | 27 | 12 | | 28 | 16 | | 29 | 20 | | 30 | 19 | | 31 | 15 | | 32 | 23 | | 33 | 1 | | 34 | 4 | | 35 | 49 | | 36 | 1 | | 37 | 1 | | 38 | 13 | | 39 | 21 | | 40 | 4 | | 41 | 32 | | 42 | 47 | | 43 | 14 | | 44 | 7 | | 45 | 25 | | 46 | 41 |
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| 93.02% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 86 | | matches | | 0 | "was sprawled" | | 1 | "was etched" | | 2 | "been unleashed" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 124 | | matches | | |
| 89.95% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 3 | | semicolonCount | 0 | | flaggedSentences | 2 | | totalSentences | 108 | | ratio | 0.019 | | matches | | 0 | "Trinkets – glass eyes, tarnished lockets, oddments of bone – were scattered across the damp platform." | | 1 | "He clutched a single object - a small brass compass." |
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| 87.77% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 670 | | adjectiveStacks | 1 | | stackExamples | | 0 | "small, leather-bound notebook" |
| | adverbCount | 31 | | adverbRatio | 0.04626865671641791 | | lyAdverbCount | 14 | | lyAdverbRatio | 0.020895522388059702 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 108 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 108 | | mean | 9.43 | | std | 6.14 | | cv | 0.651 | | sampleLengths | | 0 | 8 | | 1 | 7 | | 2 | 23 | | 3 | 3 | | 4 | 7 | | 5 | 13 | | 6 | 19 | | 7 | 3 | | 8 | 2 | | 9 | 9 | | 10 | 16 | | 11 | 17 | | 12 | 3 | | 13 | 1 | | 14 | 1 | | 15 | 13 | | 16 | 9 | | 17 | 1 | | 18 | 6 | | 19 | 8 | | 20 | 6 | | 21 | 33 | | 22 | 12 | | 23 | 15 | | 24 | 3 | | 25 | 2 | | 26 | 14 | | 27 | 16 | | 28 | 4 | | 29 | 12 | | 30 | 19 | | 31 | 10 | | 32 | 15 | | 33 | 8 | | 34 | 3 | | 35 | 13 | | 36 | 9 | | 37 | 6 | | 38 | 7 | | 39 | 9 | | 40 | 18 | | 41 | 18 | | 42 | 16 | | 43 | 6 | | 44 | 10 | | 45 | 8 | | 46 | 1 | | 47 | 28 | | 48 | 7 | | 49 | 5 |
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| 76.54% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 4 | | diversityRatio | 0.48148148148148145 | | totalSentences | 108 | | uniqueOpeners | 52 | |
| 85.47% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 78 | | matches | | 0 | "Even the name felt like" | | 1 | "Of course he hadn’t." |
| | ratio | 0.026 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 20 | | totalSentences | 78 | | matches | | 0 | "He didn’t meet Quinn’s gaze," | | 1 | "He clutched a single object" | | 2 | "Its casing had a patina" | | 3 | "she asked, gesturing to the" | | 4 | "She gently pried Finch’s fingers" | | 5 | "She wore round glasses perched" | | 6 | "She tucked a strand of" | | 7 | "She pointed to the needle," | | 8 | "He wasn’t looking for it." | | 9 | "She walked over to the" | | 10 | "He began to gather the" | | 11 | "It wasn’t like the other" | | 12 | "she asked, holding up the" | | 13 | "It felt like a pause." | | 14 | "It was a cessation." | | 15 | "He pulled out a small," | | 16 | "He’d died chasing something dangerous." | | 17 | "It hadn't wanted anyone to" | | 18 | "She didn't answer immediately." | | 19 | "she finally admitted, tucking her" |
| | ratio | 0.256 | |
| 4.87% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 71 | | totalSentences | 78 | | matches | | 0 | "The air tasted of ozone" | | 1 | "Detective Harlow Quinn descended the" | | 2 | "The Veil Market." | | 3 | "Each full moon, it shifted," | | 4 | "A bone token had gotten" | | 5 | "The scene was…contained." | | 6 | "A single stall, draped in" | | 7 | "Trinkets – glass eyes, tarnished" | | 8 | "The victim, a man in" | | 9 | "PC Davies, young and eager," | | 10 | "He didn’t meet Quinn’s gaze," | | 11 | "Quinn’s voice scraped like flint" | | 12 | "Davies jerked, nearly dropping his" | | 13 | "Quinn circled the body, her" | | 14 | "Finch’s face was pale, his" | | 15 | "Heart attack felt…clean." | | 16 | "The station's usual grime coated" | | 17 | "Davies cleared his throat." | | 18 | "Quinn stopped, her gaze fixed" | | 19 | "He clutched a single object" |
| | ratio | 0.91 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 78 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 22 | | technicalSentenceCount | 1 | | matches | | 0 | "A bone token had gotten them past the initial gatekeeper, a hulking man who smelled of patchouli and regret." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 16 | | uselessAdditionCount | 4 | | matches | | 0 | "Quinn asked, not looking at him" | | 1 | "Quinn asked, her voice low and focused" | | 2 | "Eva trailed, her expression troubled" | | 3 | "Quinn asked, her tone sharper" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 8 | | fancyCount | 1 | | fancyTags | | 0 | "she finally admitted (admit)" |
| | dialogueSentences | 38 | | tagDensity | 0.211 | | leniency | 0.421 | | rawRatio | 0.125 | | effectiveRatio | 0.053 | |