| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 6 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 14 | | tagDensity | 0.429 | | leniency | 0.857 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 96.44% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1404 | | 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) | |
| 57.26% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1404 | | totalAiIsms | 12 | | found | | | highlights | | 0 | "weight" | | 1 | "footsteps" | | 2 | "echoed" | | 3 | "standard" | | 4 | "electric" | | 5 | "measured" | | 6 | "flickered" | | 7 | "etched" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "air was thick with" | | count | 1 |
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| | highlights | | 0 | "The air was thick with" |
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| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 160 | | matches | (empty) | |
| 98.21% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 3 | | hedgeCount | 2 | | narrationSentences | 160 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 168 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 37 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 5 | | markdownWords | 24 | | totalWords | 1404 | | ratio | 0.017 | | matches | | 0 | "Not tonight, old friends." | | 1 | "Interesting." | | 2 | "Shit." | | 3 | "Morris went down a hole like this and didn't come back." | | 4 | "I know everything that enters my market." |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 6 | | unquotedAttributions | 0 | | matches | (empty) | |
| 96.93% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 43 | | wordCount | 1319 | | uniqueNames | 20 | | maxNameDensity | 1.06 | | worstName | "Quinn" | | maxWindowNameDensity | 2 | | worstWindowName | "Quinn" | | discoveredNames | | Quinn | 14 | | London | 2 | | Soho | 1 | | Old | 2 | | Compton | 1 | | Street | 1 | | Sig | 2 | | Sauer | 2 | | Camden | 3 | | Tube | 2 | | Mornington | 1 | | Crescent | 1 | | Victorian | 2 | | Underground | 1 | | Kentish | 1 | | Town | 1 | | Morris | 3 | | Veil | 1 | | Market | 1 | | Met | 1 |
| | persons | | 0 | "Quinn" | | 1 | "Sauer" | | 2 | "Tube" | | 3 | "Underground" | | 4 | "Morris" |
| | places | | 0 | "London" | | 1 | "Soho" | | 2 | "Old" | | 3 | "Compton" | | 4 | "Street" | | 5 | "Mornington" | | 6 | "Crescent" | | 7 | "Kentish" | | 8 | "Town" | | 9 | "Met" |
| | globalScore | 0.969 | | windowScore | 1 | |
| 92.53% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 87 | | glossingSentenceCount | 2 | | matches | | 0 | "looked like it led deeper into the tunnel" | | 1 | "symbols that seemed to writhe in the candlelight" |
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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 | 1404 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 168 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 55 | | mean | 25.53 | | std | 17.97 | | cv | 0.704 | | sampleLengths | | 0 | 38 | | 1 | 3 | | 2 | 37 | | 3 | 7 | | 4 | 61 | | 5 | 24 | | 6 | 55 | | 7 | 51 | | 8 | 16 | | 9 | 35 | | 10 | 44 | | 11 | 44 | | 12 | 12 | | 13 | 8 | | 14 | 37 | | 15 | 13 | | 16 | 4 | | 17 | 33 | | 18 | 31 | | 19 | 1 | | 20 | 31 | | 21 | 9 | | 22 | 51 | | 23 | 46 | | 24 | 19 | | 25 | 22 | | 26 | 11 | | 27 | 36 | | 28 | 4 | | 29 | 4 | | 30 | 4 | | 31 | 24 | | 32 | 36 | | 33 | 43 | | 34 | 47 | | 35 | 19 | | 36 | 3 | | 37 | 41 | | 38 | 72 | | 39 | 8 | | 40 | 40 | | 41 | 40 | | 42 | 12 | | 43 | 4 | | 44 | 16 | | 45 | 7 | | 46 | 37 | | 47 | 9 | | 48 | 48 | | 49 | 41 |
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| 92.11% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 6 | | totalSentences | 160 | | matches | | 0 | "been closed" | | 1 | "been ripped" | | 2 | "were rusted" | | 3 | "was lined" | | 4 | "was gone" | | 5 | "was lined" |
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| 0.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 10 | | totalVerbs | 233 | | matches | | 0 | "was hoping" | | 1 | "was already climbing" | | 2 | "were already moving" | | 3 | "was already running" | | 4 | "were going" | | 5 | "was pulling" | | 6 | "were leading" | | 7 | "was walking" | | 8 | "was chasing" | | 9 | "was waiting" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 168 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1322 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 39 | | adverbRatio | 0.029500756429652043 | | lyAdverbCount | 8 | | lyAdverbRatio | 0.006051437216338881 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 168 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 168 | | mean | 8.36 | | std | 6.31 | | cv | 0.755 | | sampleLengths | | 0 | 12 | | 1 | 26 | | 2 | 3 | | 3 | 4 | | 4 | 3 | | 5 | 14 | | 6 | 16 | | 7 | 7 | | 8 | 18 | | 9 | 21 | | 10 | 8 | | 11 | 14 | | 12 | 8 | | 13 | 12 | | 14 | 4 | | 15 | 10 | | 16 | 2 | | 17 | 1 | | 18 | 11 | | 19 | 31 | | 20 | 10 | | 21 | 12 | | 22 | 19 | | 23 | 10 | | 24 | 16 | | 25 | 4 | | 26 | 2 | | 27 | 12 | | 28 | 1 | | 29 | 2 | | 30 | 5 | | 31 | 9 | | 32 | 8 | | 33 | 7 | | 34 | 4 | | 35 | 20 | | 36 | 5 | | 37 | 16 | | 38 | 18 | | 39 | 8 | | 40 | 2 | | 41 | 4 | | 42 | 2 | | 43 | 2 | | 44 | 4 | | 45 | 8 | | 46 | 7 | | 47 | 12 | | 48 | 13 | | 49 | 5 |
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| 55.75% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 13 | | diversityRatio | 0.38095238095238093 | | totalSentences | 168 | | uniqueOpeners | 64 | |
| 49.02% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 136 | | matches | | 0 | "Just hollow points and hope." | | 1 | "Then a dozen." |
| | ratio | 0.015 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 39 | | totalSentences | 136 | | matches | | 0 | "They never did." | | 1 | "They stopped when their legs" | | 2 | "She grabbed the ladder and" | | 3 | "Her knees, older than the" | | 4 | "She followed, the gap between" | | 5 | "she shouted, the wind stealing" | | 6 | "She caught a flash of" | | 7 | "They reached the edge of" | | 8 | "They jumped, landing on a" | | 9 | "She slid off, landing on" | | 10 | "She'd run these streets for" | | 11 | "They were leading her somewhere." | | 12 | "Her gut said trap." | | 13 | "They turned sharply into a" | | 14 | "She crouched, peering down." | | 15 | "She pulled out her phone." | | 16 | "He'd never come back." | | 17 | "They'd found his body two" | | 18 | "His wife said depression." | | 19 | "She knew the supernatural had" |
| | ratio | 0.287 | |
| 59.26% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 109 | | totalSentences | 136 | | matches | | 0 | "Quinn's boots skidded against the" | | 1 | "The suspect was twenty feet" | | 2 | "The figure didn't slow." | | 3 | "They never did." | | 4 | "They stopped when their legs" | | 5 | "Tonight, she was hoping for" | | 6 | "The suspect veered left, disappearing" | | 7 | "Quinn followed, her lungs burning," | | 8 | "The alley dead-ended into a" | | 9 | "The suspect was already climbing," | | 10 | "She grabbed the ladder and" | | 11 | "Her knees, older than the" | | 12 | "The fire escape groaned under" | | 13 | "The suspect threw themselves onto" | | 14 | "She followed, the gap between" | | 15 | "The rain had soaked through" | | 16 | "This was the only time" | | 17 | "she shouted, the wind stealing" | | 18 | "The suspect glanced back." | | 19 | "She caught a flash of" |
| | ratio | 0.801 | |
| 36.76% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 136 | | matches | | 0 | "By the time Quinn crested" |
| | ratio | 0.007 | |
| 38.96% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 55 | | technicalSentenceCount | 8 | | matches | | 0 | "The suspect was twenty feet ahead, a blur of dark clothing and desperation, splashing through puddles that reflected the sickly glow of a thousand neon signs." | | 1 | "Quinn followed, her lungs burning, the worn leather of her watch band digging into her wrist as she pumped her arms." | | 2 | "They'd found his body two days later, wrists slashed, arranged in a pose that screamed ritual." | | 3 | "Water dripped from somewhere, a steady percussion that echoed through the empty space." | | 4 | "The platform was lined with stalls, makeshift tables of wooden crates and rough cloth, each lit by candles that burned with unnaturally steady flames." | | 5 | "A woman with ink-black eyes selling vials of something that glowed faintly blue." | | 6 | "Tall, gaunt, wearing a coat that seemed too heavy for the warm tunnel air." | | 7 | "Follow the suspect into the heart of a supernatural black market she barely understood, surrounded by creatures who could kill her before she got her weapon cle…" |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 6 | | uselessAdditionCount | 2 | | matches | | 0 | "she shouted, the wind stealing her words" | | 1 | "he said, his voice a rasp" |
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| 78.57% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 3 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 14 | | tagDensity | 0.214 | | leniency | 0.429 | | rawRatio | 0.333 | | effectiveRatio | 0.143 | |