| 85.71% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 13 | | adverbTagCount | 2 | | adverbTags | | 0 | "she said finally [finally]" | | 1 | "she said slowly [slowly]" |
| | dialogueSentences | 35 | | tagDensity | 0.371 | | leniency | 0.743 | | rawRatio | 0.154 | | effectiveRatio | 0.114 | |
| 94.41% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1790 | | 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) | |
| 58.10% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1790 | | totalAiIsms | 15 | | found | | | highlights | | 0 | "silence" | | 1 | "gloom" | | 2 | "familiar" | | 3 | "weight" | | 4 | "oppressive" | | 5 | "etched" | | 6 | "intricate" | | 7 | "wavered" | | 8 | "echoing" | | 9 | "pulse" | | 10 | "raced" | | 11 | "racing" | | 12 | "could feel" |
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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 | 187 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 1 | | narrationSentences | 187 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 209 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 39 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 7 | | markdownWords | 13 | | totalWords | 1777 | | ratio | 0.007 | | matches | | 0 | "found" | | 1 | "there" | | 2 | "another dimension" | | 3 | "ignore" | | 4 | "consultant" | | 5 | "interdimensional" | | 6 | "Eva Kowalski, Research Assistant, British Museum." |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 15 | | unquotedAttributions | 0 | | matches | (empty) | |
| 92.91% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 77 | | wordCount | 1489 | | uniqueNames | 19 | | maxNameDensity | 1.14 | | worstName | "Harlow" | | maxWindowNameDensity | 2 | | worstWindowName | "Harlow" | | discoveredNames | | Tube | 1 | | Camden | 1 | | Harlow | 17 | | Quinn | 3 | | Underground | 1 | | Detective | 2 | | Sergeant | 1 | | Jamie | 1 | | Cole | 16 | | Morris | 11 | | Since | 1 | | Veil | 5 | | Market | 5 | | Eva | 5 | | Kowalski | 3 | | Met | 1 | | Research | 1 | | Assistant | 1 | | British | 1 |
| | persons | | 0 | "Camden" | | 1 | "Harlow" | | 2 | "Quinn" | | 3 | "Sergeant" | | 4 | "Jamie" | | 5 | "Cole" | | 6 | "Morris" | | 7 | "Since" | | 8 | "Market" | | 9 | "Eva" | | 10 | "Kowalski" |
| | places | | | globalScore | 0.929 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 97 | | glossingSentenceCount | 1 | | matches | | 0 | "as if searching for something just out of reach" |
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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 | 1777 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 209 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 50 | | mean | 35.54 | | std | 24.11 | | cv | 0.679 | | sampleLengths | | 0 | 84 | | 1 | 100 | | 2 | 1 | | 3 | 25 | | 4 | 45 | | 5 | 48 | | 6 | 24 | | 7 | 7 | | 8 | 26 | | 9 | 71 | | 10 | 94 | | 11 | 6 | | 12 | 58 | | 13 | 19 | | 14 | 7 | | 15 | 54 | | 16 | 47 | | 17 | 46 | | 18 | 4 | | 19 | 40 | | 20 | 9 | | 21 | 37 | | 22 | 47 | | 23 | 21 | | 24 | 51 | | 25 | 34 | | 26 | 76 | | 27 | 50 | | 28 | 33 | | 29 | 16 | | 30 | 64 | | 31 | 13 | | 32 | 44 | | 33 | 42 | | 34 | 30 | | 35 | 49 | | 36 | 7 | | 37 | 7 | | 38 | 59 | | 39 | 34 | | 40 | 41 | | 41 | 42 | | 42 | 25 | | 43 | 25 | | 44 | 5 | | 45 | 11 | | 46 | 59 | | 47 | 9 | | 48 | 13 | | 49 | 18 |
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| 92.13% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 7 | | totalSentences | 187 | | matches | | 0 | "been torn" | | 1 | "was frozen" | | 2 | "been found" | | 3 | "was etched" | | 4 | "been murdered" | | 5 | "been *found" | | 6 | "been filled" |
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| 38.06% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 6 | | totalVerbs | 247 | | matches | | 0 | "was pointing" | | 1 | "was biting" | | 2 | "was staring" | | 3 | "was racing" | | 4 | "was still talking" | | 5 | "was still frowning" |
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| 19.82% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 14 | | semicolonCount | 0 | | flaggedSentences | 9 | | totalSentences | 209 | | ratio | 0.043 | | matches | | 0 | "Not just the location—though a murder in a disused Underground station was odd enough—but the details." | | 1 | "Detective Sergeant Jamie Cole—her new partner, though she still thought of him as Morris’s replacement—stepped up beside her, his torch flickering over the body." | | 2 | "She’d seen the things that didn’t make sense—the way the shadows had moved on their own, the way his body had been found with no injuries, just like this one." | | 3 | "The beam caught something near the edge—a small, brass object half-hidden beneath a crumpled newspaper." | | 4 | "She’d seen similar markings in Morris’s notes—the ones the department had dismissed as the ramblings of a man losing his grip." | | 5 | "And then—" | | 6 | "She gritted her teeth and forced her arm further, her fingers searching for something—anything—on the other side." | | 7 | "And this—this token—was the key." | | 8 | "And if Harlow was going to step into the world Morris had been investigating—the world that had gotten him killed—she needed all the information she could get." |
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| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1506 | | adjectiveStacks | 1 | | stackExamples | | 0 | "single, business-sized card," |
| | adverbCount | 51 | | adverbRatio | 0.03386454183266932 | | lyAdverbCount | 8 | | lyAdverbRatio | 0.005312084993359893 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 209 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 209 | | mean | 8.5 | | std | 6.74 | | cv | 0.793 | | sampleLengths | | 0 | 25 | | 1 | 16 | | 2 | 23 | | 3 | 20 | | 4 | 5 | | 5 | 16 | | 6 | 29 | | 7 | 18 | | 8 | 5 | | 9 | 3 | | 10 | 6 | | 11 | 18 | | 12 | 1 | | 13 | 3 | | 14 | 4 | | 15 | 12 | | 16 | 6 | | 17 | 24 | | 18 | 7 | | 19 | 14 | | 20 | 12 | | 21 | 3 | | 22 | 5 | | 23 | 5 | | 24 | 14 | | 25 | 9 | | 26 | 3 | | 27 | 21 | | 28 | 5 | | 29 | 2 | | 30 | 2 | | 31 | 21 | | 32 | 3 | | 33 | 4 | | 34 | 7 | | 35 | 4 | | 36 | 8 | | 37 | 8 | | 38 | 30 | | 39 | 10 | | 40 | 11 | | 41 | 15 | | 42 | 19 | | 43 | 11 | | 44 | 21 | | 45 | 5 | | 46 | 12 | | 47 | 6 | | 48 | 5 | | 49 | 12 |
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| 40.91% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 19 | | diversityRatio | 0.24401913875598086 | | totalSentences | 209 | | uniqueOpeners | 51 | |
| 81.30% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 4 | | totalSentences | 164 | | matches | | 0 | "Just the man, his skin" | | 1 | "Just clean, almost manicured fingers." | | 2 | "Just a single, business-sized card," | | 3 | "Then she turned on her" |
| | ratio | 0.024 | |
| 88.29% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 54 | | totalSentences | 164 | | matches | | 0 | "She adjusted the worn leather" | | 1 | "His face was frozen in" | | 2 | "She didn’t turn." | | 3 | "She knew that voice." | | 4 | "she said, her own voice" | | 5 | "he said, not unkindly" | | 6 | "She stood, rolling her shoulders" | | 7 | "He cut himself off, but" | | 8 | "She knew what they said" | | 9 | "She’d seen the things that" | | 10 | "She turned away from the" | | 11 | "She crossed the platform in" | | 12 | "It twitched, restless, as if" | | 13 | "She turned the compass over" | | 14 | "They were protective." | | 15 | "She’d seen similar markings in" | | 16 | "He’d been onto something." | | 17 | "she said finally, her voice" | | 18 | "She was too busy staring" | | 19 | "She took a step forward," |
| | ratio | 0.329 | |
| 72.80% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 127 | | totalSentences | 164 | | matches | | 0 | "The abandoned Tube station beneath" | | 1 | "Detective Harlow Quinn stepped over" | | 2 | "The beam of her torch" | | 3 | "She adjusted the worn leather" | | 4 | "The crime scene was wrong." | | 5 | "The body lay sprawled near" | | 6 | "His face was frozen in" | | 7 | "She didn’t turn." | | 8 | "She knew that voice." | | 9 | "she said, her own voice" | | 10 | "Detective Sergeant Jamie Cole—her new" | | 11 | "he said, not unkindly" | | 12 | "Harlow crouched, her sharp jaw" | | 13 | "She stood, rolling her shoulders" | | 14 | "Harlow exhaled through her nose." | | 15 | "He cut himself off, but" | | 16 | "Harlow ignored the jab." | | 17 | "She knew what they said" | | 18 | "That she’d become obsessed." | | 19 | "That she saw conspiracies where" |
| | ratio | 0.774 | |
| 60.98% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 164 | | matches | | 0 | "If Harlow Quinn was hesitant," | | 1 | "If anyone would know about" |
| | ratio | 0.012 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 54 | | technicalSentenceCount | 1 | | matches | | 0 | "It twitched, restless, as if searching for something just out of reach." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 13 | | uselessAdditionCount | 7 | | matches | | 0 | "she said, her own voice steady, precise" | | 1 | "he said, not unkindly" | | 2 | "He cut, but the words hung there anyway" | | 3 | "she said finally, her voice tight" | | 4 | "Cole said, his voice uneasy" | | 5 | "she said, her voice firm" | | 6 | "She pocketed, her mind already working through the angles" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 8 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 35 | | tagDensity | 0.229 | | leniency | 0.457 | | rawRatio | 0 | | effectiveRatio | 0 | |