| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 14 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 54 | | tagDensity | 0.259 | | leniency | 0.519 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 95.88% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1214 | | 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) | |
| 42.34% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1214 | | totalAiIsms | 14 | | found | | | highlights | | 0 | "perfect" | | 1 | "pristine" | | 2 | "traced" | | 3 | "silk" | | 4 | "footsteps" | | 5 | "etched" | | 6 | "trembled" | | 7 | "quivered" | | 8 | "unwavering" | | 9 | "echoed" |
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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 | 140 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 140 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 179 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 28 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 1 | | markdownWords | 24 | | totalWords | 1214 | | ratio | 0.02 | | matches | | 0 | "There's a market beneath the city, Harlow. A place where things trade that shouldn't exist. I found it. God help me, I found it." |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 5 | | unquotedAttributions | 0 | | matches | (empty) | |
| 62.39% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 33 | | wordCount | 799 | | uniqueNames | 8 | | maxNameDensity | 1.75 | | worstName | "Quinn" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Quinn" | | discoveredNames | | Camden | 1 | | Simmonds | 9 | | Quinn | 14 | | Victorian | 1 | | Morris | 3 | | Met | 1 | | Harlow | 1 | | Three | 3 |
| | persons | | 0 | "Simmonds" | | 1 | "Quinn" | | 2 | "Morris" | | 3 | "Met" |
| | places | (empty) | | globalScore | 0.624 | | windowScore | 0.833 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 65 | | 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 | 1214 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 179 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 62 | | mean | 19.58 | | std | 17.31 | | cv | 0.884 | | sampleLengths | | 0 | 5 | | 1 | 19 | | 2 | 64 | | 3 | 7 | | 4 | 4 | | 5 | 12 | | 6 | 40 | | 7 | 2 | | 8 | 50 | | 9 | 4 | | 10 | 40 | | 11 | 22 | | 12 | 52 | | 13 | 1 | | 14 | 1 | | 15 | 54 | | 16 | 3 | | 17 | 2 | | 18 | 35 | | 19 | 19 | | 20 | 12 | | 21 | 4 | | 22 | 19 | | 23 | 49 | | 24 | 59 | | 25 | 3 | | 26 | 1 | | 27 | 1 | | 28 | 7 | | 29 | 12 | | 30 | 28 | | 31 | 11 | | 32 | 2 | | 33 | 5 | | 34 | 36 | | 35 | 34 | | 36 | 12 | | 37 | 1 | | 38 | 44 | | 39 | 17 | | 40 | 42 | | 41 | 31 | | 42 | 25 | | 43 | 6 | | 44 | 23 | | 45 | 4 | | 46 | 25 | | 47 | 35 | | 48 | 15 | | 49 | 28 |
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| 97.74% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 140 | | matches | | 0 | "was unbuttoned" | | 1 | "been dragged" | | 2 | "been pried" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 129 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 179 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 800 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 7 | | adverbRatio | 0.00875 | | lyAdverbCount | 1 | | lyAdverbRatio | 0.00125 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 179 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 179 | | mean | 6.78 | | std | 5.15 | | cv | 0.759 | | sampleLengths | | 0 | 5 | | 1 | 4 | | 2 | 1 | | 3 | 14 | | 4 | 7 | | 5 | 7 | | 6 | 17 | | 7 | 10 | | 8 | 6 | | 9 | 17 | | 10 | 7 | | 11 | 4 | | 12 | 11 | | 13 | 1 | | 14 | 23 | | 15 | 13 | | 16 | 4 | | 17 | 2 | | 18 | 21 | | 19 | 4 | | 20 | 10 | | 21 | 15 | | 22 | 4 | | 23 | 28 | | 24 | 12 | | 25 | 2 | | 26 | 5 | | 27 | 15 | | 28 | 5 | | 29 | 3 | | 30 | 4 | | 31 | 3 | | 32 | 7 | | 33 | 4 | | 34 | 5 | | 35 | 11 | | 36 | 7 | | 37 | 1 | | 38 | 1 | | 39 | 1 | | 40 | 1 | | 41 | 1 | | 42 | 19 | | 43 | 4 | | 44 | 4 | | 45 | 12 | | 46 | 3 | | 47 | 12 | | 48 | 3 | | 49 | 2 |
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| 53.26% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 18 | | diversityRatio | 0.37988826815642457 | | totalSentences | 179 | | uniqueOpeners | 68 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 116 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 31 | | totalSentences | 116 | | matches | | 0 | "Her knees popped against the" | | 1 | "Her sharp jaw set." | | 2 | "She adjusted the worn leather" | | 3 | "She traced a gloved finger" | | 4 | "He flipped his notepad shut." | | 5 | "She lifted his right hand." | | 6 | "She brought it closer to" | | 7 | "She looked at the victim's" | | 8 | "She parted the wool." | | 9 | "She walked toward it" | | 10 | "Her torch beam cut through" | | 11 | "She had missed it in" | | 12 | "It bore symbols she recognized." | | 13 | "Her throat tightened." | | 14 | "He crouched beside her, his" | | 15 | "It gave way like wet" | | 16 | "She gripped the loose brick" | | 17 | "It slid out with a" | | 18 | "She recognised the sigils." | | 19 | "Her hand trembled." |
| | ratio | 0.267 | |
| 46.21% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 96 | | totalSentences | 116 | | matches | | 0 | "Simmonds clicked his pen." | | 1 | "Her knees popped against the" | | 2 | "The fluorescent work lights the" | | 3 | "A young man, mid-thirties, dressed" | | 4 | "Simmonds leaned in, his polished" | | 5 | "Quinn gestured to the tunnel" | | 6 | "A thick layer of dust," | | 7 | "Her sharp jaw set." | | 8 | "She adjusted the worn leather" | | 9 | "She traced a gloved finger" | | 10 | "He flipped his notepad shut." | | 11 | "Quinn examined the victim's hands." | | 12 | "A man who cared about" | | 13 | "She lifted his right hand." | | 14 | "She brought it closer to" | | 15 | "She looked at the victim's" | | 16 | "The coat was unbuttoned." | | 17 | "She parted the wool." | | 18 | "A single puncture wound, clean," | | 19 | "The knife had slipped through" |
| | ratio | 0.828 | |
| 43.10% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 116 | | matches | | 0 | "As if something had been" |
| | ratio | 0.009 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 19 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 14 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 2 | | fancyCount | 2 | | fancyTags | | 0 | "She murmured (murmur)" | | 1 | "Quinn pressed (press)" |
| | dialogueSentences | 54 | | tagDensity | 0.037 | | leniency | 0.074 | | rawRatio | 1 | | effectiveRatio | 0.074 | |