| 33.33% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 11 | | adverbTagCount | 2 | | adverbTags | | 0 | "green eyes widened slightly [slightly]" | | 1 | "Eva spoke quickly [quickly]" |
| | dialogueSentences | 24 | | tagDensity | 0.458 | | leniency | 0.917 | | rawRatio | 0.182 | | effectiveRatio | 0.167 | |
| 51.79% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 726 | | totalAiIsmAdverbs | 7 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | adverb | "barely above a whisper" | | count | 1 |
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| | highlights | | 0 | "slowly" | | 1 | "carefully" | | 2 | "slightly" | | 3 | "nervously" | | 4 | "quickly" | | 5 | "barely above a whisper" |
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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) | |
| 51.79% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 726 | | totalAiIsms | 7 | | found | | | highlights | | 0 | "weight" | | 1 | "familiar" | | 2 | "echoed" | | 3 | "etched" | | 4 | "intricate" | | 5 | "whisper" |
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| 66.67% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 2 | | maxInWindow | 2 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 2 |
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| | highlights | | 0 | "eyes narrowed" | | 1 | "eyes widened" |
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| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 51 | | matches | (empty) | |
| 58.82% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 2 | | narrationSentences | 51 | | filterMatches | | | hedgeMatches | | 0 | "seemed to" | | 1 | "happened to" |
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| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 65 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 44 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 729 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 8 | | unquotedAttributions | 0 | | matches | (empty) | |
| 42.37% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 29 | | wordCount | 511 | | uniqueNames | 13 | | maxNameDensity | 2.15 | | worstName | "Quinn" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Quinn" | | discoveredNames | | Harlow | 1 | | Quinn | 11 | | Tube | 1 | | Underground | 1 | | Bennett | 1 | | Camden | 1 | | Town | 1 | | Watson | 3 | | Italian | 1 | | Playing | 1 | | Eva | 5 | | Kowalski | 1 | | Morris | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Bennett" | | 3 | "Watson" | | 4 | "Playing" | | 5 | "Eva" | | 6 | "Kowalski" | | 7 | "Morris" |
| | places | | | globalScore | 0.424 | | windowScore | 0.5 | |
| 90.48% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 42 | | glossingSentenceCount | 1 | | matches | | 0 | "residue that seemed to shimmer" |
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| 62.83% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 1.372 | | wordCount | 729 | | matches | | 0 | "Not just debris, but evidence of something impossible" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 65 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 28 | | mean | 26.04 | | std | 13.04 | | cv | 0.501 | | sampleLengths | | 0 | 45 | | 1 | 15 | | 2 | 40 | | 3 | 35 | | 4 | 27 | | 5 | 23 | | 6 | 8 | | 7 | 22 | | 8 | 32 | | 9 | 32 | | 10 | 25 | | 11 | 13 | | 12 | 40 | | 13 | 34 | | 14 | 11 | | 15 | 44 | | 16 | 7 | | 17 | 10 | | 18 | 35 | | 19 | 58 | | 20 | 9 | | 21 | 16 | | 22 | 21 | | 23 | 8 | | 24 | 27 | | 25 | 36 | | 26 | 32 | | 27 | 24 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 51 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 92 | | matches | | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 6 | | semicolonCount | 0 | | flaggedSentences | 5 | | totalSentences | 65 | | ratio | 0.077 | | matches | | 0 | "Quinn's leather watch caught the dim emergency lighting as she checked the time - 3:47 AM." | | 1 | "Market debris littered the ground - scattered playing cards, broken glass vials, torn fabric awnings." | | 2 | "The victim's clothes were expensive - handmade Italian leather shoes, tailored wool coat." | | 3 | "And there - half-hidden under a fallen awning - a carved token made of bone." | | 4 | "Whatever secrets this underground market held, she would uncover them - no matter the cost." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 444 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 8 | | adverbRatio | 0.018018018018018018 | | lyAdverbCount | 4 | | lyAdverbRatio | 0.009009009009009009 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 65 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 65 | | mean | 11.22 | | std | 6.48 | | cv | 0.578 | | sampleLengths | | 0 | 20 | | 1 | 7 | | 2 | 18 | | 3 | 10 | | 4 | 5 | | 5 | 16 | | 6 | 11 | | 7 | 4 | | 8 | 9 | | 9 | 7 | | 10 | 13 | | 11 | 15 | | 12 | 11 | | 13 | 16 | | 14 | 11 | | 15 | 12 | | 16 | 5 | | 17 | 3 | | 18 | 22 | | 19 | 4 | | 20 | 3 | | 21 | 13 | | 22 | 3 | | 23 | 9 | | 24 | 9 | | 25 | 16 | | 26 | 7 | | 27 | 16 | | 28 | 9 | | 29 | 2 | | 30 | 11 | | 31 | 10 | | 32 | 6 | | 33 | 9 | | 34 | 15 | | 35 | 8 | | 36 | 18 | | 37 | 8 | | 38 | 11 | | 39 | 17 | | 40 | 22 | | 41 | 5 | | 42 | 4 | | 43 | 3 | | 44 | 5 | | 45 | 5 | | 46 | 23 | | 47 | 12 | | 48 | 15 | | 49 | 43 |
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| 91.79% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 2 | | diversityRatio | 0.5692307692307692 | | totalSentences | 65 | | uniqueOpeners | 37 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 50 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 4 | | totalSentences | 50 | | matches | | 0 | "She knelt down, carefully prying" | | 1 | "She trailed off, eyes fixed" | | 2 | "Her freckled face went pale." | | 3 | "She turned back to the" |
| | ratio | 0.08 | |
| 100.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 35 | | totalSentences | 50 | | matches | | 0 | "Detective Harlow Quinn descended the" | | 1 | "The metal stairs groaned under" | | 2 | "PC Bennett's voice echoed from" | | 3 | "Quinn's leather watch caught the" | | 4 | "The call had dragged her" | | 5 | "The passage opened into a" | | 6 | "Quinn approached, noting the lack" | | 7 | "DS Watson crouched beside the" | | 8 | "Quinn circled the scene slowly." | | 9 | "The detective's eyes narrowed." | | 10 | "Something wasn't right." | | 11 | "The victim's clothes were expensive" | | 12 | "She knelt down, carefully prying" | | 13 | "A small brass compass tumbled" | | 14 | "A strange green patina coated" | | 15 | "Quinn passed it to the" | | 16 | "Quinn's torch beam swept across" | | 17 | "A familiar voice called from" | | 18 | "Quinn turned to see Eva" | | 19 | "The research assistant clutched her" |
| | ratio | 0.7 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 50 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 20 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 34.09% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 11 | | uselessAdditionCount | 2 | | matches | | 0 | "She trailed, eyes fixed on the brass compass in the evidence bag" | | 1 | "Eva spoke quickly, voice barely above a whisper" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 2 | | fancyCount | 1 | | fancyTags | | 0 | "Eva spoke quickly (speak)" |
| | dialogueSentences | 24 | | tagDensity | 0.083 | | leniency | 0.167 | | rawRatio | 0.5 | | effectiveRatio | 0.083 | |