| 97.44% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 16 | | adverbTagCount | 2 | | adverbTags | | 0 | "Eva said quietly [quietly]" | | 1 | "Quinn said slowly [slowly]" |
| | dialogueSentences | 39 | | tagDensity | 0.41 | | leniency | 0.821 | | rawRatio | 0.125 | | effectiveRatio | 0.103 | |
| 93.73% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1596 | | totalAiIsmAdverbs | 2 | | 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) | |
| 68.67% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1596 | | totalAiIsms | 10 | | found | | | highlights | | 0 | "measured" | | 1 | "standard" | | 2 | "etched" | | 3 | "trembled" | | 4 | "familiar" | | 5 | "scanning" | | 6 | "systematic" | | 7 | "quivered" | | 8 | "could feel" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 113 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 0 | | narrationSentences | 113 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 136 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 47 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1596 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 23 | | unquotedAttributions | 0 | | matches | (empty) | |
| 59.83% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 56 | | wordCount | 1109 | | uniqueNames | 15 | | maxNameDensity | 1.8 | | worstName | "Quinn" | | maxWindowNameDensity | 3 | | worstWindowName | "Quinn" | | discoveredNames | | Harlow | 1 | | Quinn | 20 | | Camden | 1 | | Met | 1 | | Tube | 1 | | Eva | 15 | | Kowalski | 1 | | British | 1 | | Museum | 1 | | Veil | 2 | | Market | 6 | | Morris | 3 | | Whitechapel | 1 | | One | 1 | | Compass | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Met" | | 3 | "Eva" | | 4 | "Kowalski" | | 5 | "Market" | | 6 | "Morris" |
| | places | | | globalScore | 0.598 | | windowScore | 0.667 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 79 | | glossingSentenceCount | 1 | | matches | | 0 | "It was as if the Market had folded around this one spot, leaving a clean room" |
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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 | 1596 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 136 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 47 | | mean | 33.96 | | std | 19.82 | | cv | 0.584 | | sampleLengths | | 0 | 56 | | 1 | 56 | | 2 | 69 | | 3 | 20 | | 4 | 44 | | 5 | 39 | | 6 | 57 | | 7 | 34 | | 8 | 52 | | 9 | 5 | | 10 | 27 | | 11 | 13 | | 12 | 63 | | 13 | 35 | | 14 | 35 | | 15 | 68 | | 16 | 43 | | 17 | 5 | | 18 | 9 | | 19 | 3 | | 20 | 23 | | 21 | 63 | | 22 | 16 | | 23 | 29 | | 24 | 21 | | 25 | 15 | | 26 | 5 | | 27 | 50 | | 28 | 16 | | 29 | 57 | | 30 | 61 | | 31 | 41 | | 32 | 12 | | 33 | 12 | | 34 | 33 | | 35 | 34 | | 36 | 44 | | 37 | 16 | | 38 | 48 | | 39 | 36 | | 40 | 20 | | 41 | 9 | | 42 | 63 | | 43 | 22 | | 44 | 33 | | 45 | 66 | | 46 | 18 |
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| 92.84% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 4 | | totalSentences | 113 | | matches | | 0 | "was supposed" | | 1 | "was positioned" | | 2 | "were dilated" | | 3 | "were gone" |
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| 95.29% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 3 | | totalVerbs | 191 | | matches | | 0 | "were kneeling" | | 1 | "was not pointing" | | 2 | "was pointing" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 136 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1116 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 28 | | adverbRatio | 0.025089605734767026 | | lyAdverbCount | 7 | | lyAdverbRatio | 0.0062724014336917565 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 136 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 136 | | mean | 11.74 | | std | 8.43 | | cv | 0.719 | | sampleLengths | | 0 | 30 | | 1 | 26 | | 2 | 14 | | 3 | 24 | | 4 | 16 | | 5 | 2 | | 6 | 17 | | 7 | 26 | | 8 | 26 | | 9 | 3 | | 10 | 9 | | 11 | 8 | | 12 | 20 | | 13 | 13 | | 14 | 11 | | 15 | 9 | | 16 | 10 | | 17 | 1 | | 18 | 6 | | 19 | 5 | | 20 | 8 | | 21 | 15 | | 22 | 42 | | 23 | 4 | | 24 | 21 | | 25 | 9 | | 26 | 5 | | 27 | 9 | | 28 | 3 | | 29 | 11 | | 30 | 13 | | 31 | 11 | | 32 | 5 | | 33 | 8 | | 34 | 19 | | 35 | 8 | | 36 | 5 | | 37 | 11 | | 38 | 10 | | 39 | 6 | | 40 | 9 | | 41 | 21 | | 42 | 6 | | 43 | 18 | | 44 | 17 | | 45 | 7 | | 46 | 7 | | 47 | 21 | | 48 | 6 | | 49 | 12 |
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| 43.70% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 11 | | diversityRatio | 0.3111111111111111 | | totalSentences | 135 | | uniqueOpeners | 42 | |
| 33.33% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 100 | | matches | | 0 | "Just a single abandoned bone" |
| | ratio | 0.01 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 26 | | totalSentences | 100 | | matches | | 0 | "It smelled of cold stone" | | 1 | "She hadn’t requested the researcher" | | 2 | "She hadn’t requested the Veil" | | 3 | "She checked her worn leather" | | 4 | "She remembered telling herself it" | | 5 | "She moved to the body." | | 6 | "His eyes were open, brown" | | 7 | "It was surprise, as if" | | 8 | "She noted the placement of" | | 9 | "She followed the needle with" | | 10 | "It trembled, but settled against" | | 11 | "She stood and walked the" | | 12 | "She looked up at the" | | 13 | "She pointed to the sigil" | | 14 | "It was as if the" | | 15 | "She crouched again, this time" | | 16 | "He hadn’t moved on the" | | 17 | "she said, more to herself" | | 18 | "She’d told herself it was" | | 19 | "She stood and pulled on" |
| | ratio | 0.26 | |
| 50.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 82 | | totalSentences | 100 | | matches | | 0 | "Detective Harlow Quinn descended the" | | 1 | "The air down here was" | | 2 | "It smelled of cold stone" | | 3 | "Emergency floodlights on tripods threw" | | 4 | "A transit worker in a" | | 5 | "Quinn’s jaw tightened." | | 6 | "She hadn’t requested the researcher" | | 7 | "She hadn’t requested the Veil" | | 8 | "Eva straightened as Quinn stepped" | | 9 | "The nervous habit made Quinn’s" | | 10 | "Quinn said, her voice low" | | 11 | "She checked her worn leather" | | 12 | "The Market moved every full" | | 13 | "Eva lifted a small, pale" | | 14 | "Quinn remembered DS Morris." | | 15 | "She remembered telling herself it" | | 16 | "She moved to the body." | | 17 | "His eyes were open, brown" | | 18 | "It was surprise, as if" | | 19 | "That was the first thing" |
| | ratio | 0.82 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 100 | | matches | (empty) | | ratio | 0 | |
| 80.75% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 46 | | technicalSentenceCount | 4 | | matches | | 0 | "It smelled of cold stone and ozone, with an undercurrent of burnt sugar and old incense that clung to the back of the throat." | | 1 | "Emergency floodlights on tripods threw hard white cones over a platform that should have been empty." | | 2 | "Remembered the file that went cold three years ago and the smell of something not human in the alley off Whitechapel." | | 3 | "She walked up the ladder, counting each step, her mind already cataloguing the things she hadn’t missed, only failed to see until now: the clean shoes, the unto…" |
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| 62.50% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 16 | | uselessAdditionCount | 2 | | matches | | 0 | "Quinn said, her voice low and even" | | 1 | "she said, more to herself than Eva" |
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| 98.72% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 14 | | fancyCount | 2 | | fancyTags | | 0 | "Eva murmured (murmur)" | | 1 | "Eva continued (continue)" |
| | dialogueSentences | 39 | | tagDensity | 0.359 | | leniency | 0.718 | | rawRatio | 0.143 | | effectiveRatio | 0.103 | |