| 63.64% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 15 | | adverbTagCount | 3 | | adverbTags | | 0 | "she said quietly [quietly]" | | 1 | "she said softly [softly]" | | 2 | "she asked quietly [quietly]" |
| | dialogueSentences | 44 | | tagDensity | 0.341 | | leniency | 0.682 | | rawRatio | 0.2 | | effectiveRatio | 0.136 | |
| 88.14% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1265 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | 0 | "slowly" | | 1 | "quickly" | | 2 | "softly" |
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| 80.00% | AI-ism character names | Target: 0 AI-default names (17 tracked, −20% each) | | codexExemptions | (empty) | | found | | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 68.38% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1265 | | totalAiIsms | 8 | | found | | | highlights | | 0 | "weight" | | 1 | "stomach" | | 2 | "perfect" | | 3 | "etched" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "clenched jaw/fists" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 87 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 0 | | narrationSentences | 87 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 114 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 32 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1264 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 25 | | unquotedAttributions | 0 | | matches | (empty) | |
| 39.92% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 46 | | wordCount | 863 | | uniqueNames | 9 | | maxNameDensity | 2.2 | | worstName | "Quinn" | | maxWindowNameDensity | 3 | | worstWindowName | "Quinn" | | discoveredNames | | Harlow | 1 | | Quinn | 19 | | Tube | 1 | | Morris | 4 | | Evans | 13 | | Veil | 2 | | Market | 2 | | Metropolitan | 1 | | Things | 3 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Morris" | | 3 | "Evans" | | 4 | "Market" |
| | places | | | globalScore | 0.399 | | windowScore | 0.667 | |
| 68.03% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 61 | | glossingSentenceCount | 2 | | matches | | 0 | "quite fear" | | 1 | "as if reaching for something that wasn't there" |
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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 | 1264 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 114 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 53 | | mean | 23.85 | | std | 17.22 | | cv | 0.722 | | sampleLengths | | 0 | 58 | | 1 | 30 | | 2 | 53 | | 3 | 2 | | 4 | 40 | | 5 | 48 | | 6 | 27 | | 7 | 22 | | 8 | 46 | | 9 | 9 | | 10 | 18 | | 11 | 29 | | 12 | 20 | | 13 | 37 | | 14 | 11 | | 15 | 14 | | 16 | 53 | | 17 | 17 | | 18 | 1 | | 19 | 16 | | 20 | 18 | | 21 | 22 | | 22 | 6 | | 23 | 40 | | 24 | 3 | | 25 | 55 | | 26 | 13 | | 27 | 9 | | 28 | 57 | | 29 | 15 | | 30 | 15 | | 31 | 50 | | 32 | 4 | | 33 | 31 | | 34 | 11 | | 35 | 15 | | 36 | 37 | | 37 | 34 | | 38 | 27 | | 39 | 37 | | 40 | 7 | | 41 | 10 | | 42 | 56 | | 43 | 43 | | 44 | 9 | | 45 | 6 | | 46 | 9 | | 47 | 34 | | 48 | 15 | | 49 | 1 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 87 | | matches | | |
| 32.29% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 4 | | totalVerbs | 159 | | matches | | 0 | "was studying" | | 1 | "was twitching" | | 2 | "wasn't pointing" | | 3 | "was coming" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 1 | | semicolonCount | 0 | | flaggedSentences | 1 | | totalSentences | 114 | | ratio | 0.009 | | matches | | 0 | "The clothes were expensive but generic—nothing that screamed \"drug dealer.\" And the watch on the victim's wrist..." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 865 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 34 | | adverbRatio | 0.03930635838150289 | | lyAdverbCount | 13 | | lyAdverbRatio | 0.015028901734104046 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 114 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 114 | | mean | 11.09 | | std | 6.87 | | cv | 0.62 | | sampleLengths | | 0 | 21 | | 1 | 20 | | 2 | 17 | | 3 | 10 | | 4 | 7 | | 5 | 13 | | 6 | 21 | | 7 | 10 | | 8 | 6 | | 9 | 16 | | 10 | 2 | | 11 | 17 | | 12 | 23 | | 13 | 21 | | 14 | 8 | | 15 | 10 | | 16 | 5 | | 17 | 4 | | 18 | 10 | | 19 | 13 | | 20 | 2 | | 21 | 2 | | 22 | 16 | | 23 | 6 | | 24 | 4 | | 25 | 24 | | 26 | 6 | | 27 | 12 | | 28 | 9 | | 29 | 9 | | 30 | 9 | | 31 | 8 | | 32 | 17 | | 33 | 4 | | 34 | 20 | | 35 | 6 | | 36 | 12 | | 37 | 11 | | 38 | 5 | | 39 | 3 | | 40 | 11 | | 41 | 8 | | 42 | 6 | | 43 | 22 | | 44 | 6 | | 45 | 12 | | 46 | 13 | | 47 | 6 | | 48 | 11 | | 49 | 1 |
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| 58.48% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 15 | | diversityRatio | 0.4298245614035088 | | totalSentences | 114 | | uniqueOpeners | 49 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 81 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 19 | | totalSentences | 81 | | matches | | 0 | "His breath fogged in the" | | 1 | "They walked past the skeletal" | | 2 | "She was studying the pattern" | | 3 | "she said quietly" | | 4 | "She'd served with Evans for" | | 5 | "It was twitching now." | | 6 | "She walked to the platform's" | | 7 | "she called over her shoulder" | | 8 | "She crouched beside the body" | | 9 | "Her breath caught." | | 10 | "It was identical to the" | | 11 | "she said, her voice low" | | 12 | "It hadn't been pointing north" | | 13 | "It pointed steadily toward the" | | 14 | "She'd heard stories, whispers in" | | 15 | "she said softly" | | 16 | "His voice broke" | | 17 | "she asked quietly" | | 18 | "she whispered into the darkness" |
| | ratio | 0.235 | |
| 34.07% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 69 | | totalSentences | 81 | | matches | | 0 | "Detective Harlow Quinn pressed her" | | 1 | "The abandoned platform stretched before" | | 2 | "DS Morris had called it" | | 3 | "DC Evans said, stepping from" | | 4 | "His breath fogged in the" | | 5 | "Quinn's hand drifted to the" | | 6 | "Military precision had taught her" | | 7 | "The way Evans shifted his" | | 8 | "The way he avoided looking" | | 9 | "They walked past the skeletal" | | 10 | "The smell hit Quinn first:" | | 11 | "The body lay sprawled near" | | 12 | "Quinn crouched, her knee cracking" | | 13 | "The victim was young, couldn't" | | 14 | "Clothes torn and stained." | | 15 | "The arms were arranged in" | | 16 | "Evans said, his voice carrying" | | 17 | "Quinn didn't look up." | | 18 | "She was studying the pattern" | | 19 | "Lightning might, but not the" |
| | ratio | 0.852 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 81 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 36 | | technicalSentenceCount | 1 | | matches | | 0 | "The body lay sprawled near the disused platform edge, one arm flung out as if reaching for something that wasn't there." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 15 | | uselessAdditionCount | 4 | | matches | | 0 | "Evans said, his voice carrying too much certainty" | | 1 | "Quinn pulled out, her trained eye catching details Evans had missed" | | 2 | "she said, her voice low" | | 3 | "Evans interrupted, his voice cracking" |
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| 81.82% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 12 | | fancyCount | 3 | | fancyTags | | 0 | "Quinn pulled out (pull out)" | | 1 | "Evans interrupted (interrupt)" | | 2 | "she whispered (whisper)" |
| | dialogueSentences | 44 | | tagDensity | 0.273 | | leniency | 0.545 | | rawRatio | 0.25 | | effectiveRatio | 0.136 | |