| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 3 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 15 | | tagDensity | 0.2 | | leniency | 0.4 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 93.31% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 747 | | 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) | |
| 12.99% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 747 | | totalAiIsms | 13 | | found | | | highlights | | 0 | "familiar" | | 1 | "weight" | | 2 | "oppressive" | | 3 | "flicker" | | 4 | "scanning" | | 5 | "etched" | | 6 | "intricate" | | 7 | "standard" | | 8 | "echoed" | | 9 | "whisper" | | 10 | "flickered" | | 11 | "stomach" | | 12 | "pulsed" |
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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 | 79 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 79 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 91 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 24 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 743 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 9 | | unquotedAttributions | 0 | | matches | (empty) | |
| 95.74% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 20 | | wordCount | 645 | | uniqueNames | 8 | | maxNameDensity | 1.09 | | worstName | "Harris" | | maxWindowNameDensity | 2 | | worstWindowName | "Harris" | | discoveredNames | | Tube | 1 | | Camden | 1 | | Harlow | 6 | | Quinn | 1 | | Harris | 7 | | Morris | 2 | | Veil | 1 | | Market | 1 |
| | persons | | 0 | "Camden" | | 1 | "Harlow" | | 2 | "Quinn" | | 3 | "Harris" | | 4 | "Morris" |
| | places | (empty) | | globalScore | 0.957 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 48 | | 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 | 743 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 91 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 30 | | mean | 24.77 | | std | 17.97 | | cv | 0.725 | | sampleLengths | | 0 | 61 | | 1 | 45 | | 2 | 5 | | 3 | 66 | | 4 | 51 | | 5 | 14 | | 6 | 46 | | 7 | 15 | | 8 | 38 | | 9 | 52 | | 10 | 5 | | 11 | 17 | | 12 | 32 | | 13 | 5 | | 14 | 38 | | 15 | 22 | | 16 | 16 | | 17 | 46 | | 18 | 20 | | 19 | 18 | | 20 | 1 | | 21 | 22 | | 22 | 9 | | 23 | 15 | | 24 | 13 | | 25 | 25 | | 26 | 12 | | 27 | 6 | | 28 | 22 | | 29 | 6 |
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| 91.94% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 79 | | matches | | 0 | "been sucked" | | 1 | "were curled" | | 2 | "been abandoned" |
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| 85.06% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 116 | | matches | | 0 | "were draining" | | 1 | "was spinning" |
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| 48.67% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 4 | | semicolonCount | 0 | | flaggedSentences | 3 | | totalSentences | 91 | | ratio | 0.033 | | matches | | 0 | "The victim—a man in a long, tattered coat—lay sprawled across the tracks, his limbs twisted at unnatural angles." | | 1 | "The station had been abandoned for years, but the walls were fresh with symbols—carved into the brick, daubed in something dark and sticky." | | 2 | "A noise echoed from the tunnel—a scuffle, a whisper." |
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| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 651 | | adjectiveStacks | 1 | | stackExamples | | 0 | "dry, ashen grey creeping" |
| | adverbCount | 20 | | adverbRatio | 0.030721966205837174 | | lyAdverbCount | 6 | | lyAdverbRatio | 0.009216589861751152 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 91 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 91 | | mean | 8.16 | | std | 5.38 | | cv | 0.659 | | sampleLengths | | 0 | 11 | | 1 | 17 | | 2 | 14 | | 3 | 19 | | 4 | 12 | | 5 | 20 | | 6 | 13 | | 7 | 5 | | 8 | 3 | | 9 | 6 | | 10 | 18 | | 11 | 10 | | 12 | 6 | | 13 | 4 | | 14 | 19 | | 15 | 6 | | 16 | 10 | | 17 | 7 | | 18 | 10 | | 19 | 7 | | 20 | 11 | | 21 | 6 | | 22 | 8 | | 23 | 5 | | 24 | 23 | | 25 | 2 | | 26 | 3 | | 27 | 5 | | 28 | 8 | | 29 | 9 | | 30 | 6 | | 31 | 16 | | 32 | 11 | | 33 | 2 | | 34 | 9 | | 35 | 16 | | 36 | 23 | | 37 | 5 | | 38 | 8 | | 39 | 3 | | 40 | 2 | | 41 | 3 | | 42 | 5 | | 43 | 9 | | 44 | 9 | | 45 | 9 | | 46 | 3 | | 47 | 9 | | 48 | 2 | | 49 | 2 |
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| 58.61% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 5 | | diversityRatio | 0.38461538461538464 | | totalSentences | 91 | | uniqueOpeners | 35 | |
| 93.90% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 71 | | matches | | 0 | "Just a dry, ashen grey" | | 1 | "Then she saw it." |
| | ratio | 0.028 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 21 | | totalSentences | 71 | | matches | | 0 | "She adjusted the worn leather" | | 1 | "He nodded as she approached," | | 2 | "She didn’t answer." | | 3 | "It was the lack of" | | 4 | "She reached for his wrist," | | 5 | "It was the cold of" | | 6 | "She stood, scanning the platform." | | 7 | "It smelled metallic, but wrong." | | 8 | "She pulled a pair of" | | 9 | "It twitched, restless, then settled" | | 10 | "She knew what it was." | | 11 | "She turned, her hand instinctively" | | 12 | "she said, her voice steady" | | 13 | "She followed its pull, stepping" | | 14 | "Her stomach twisted." | | 15 | "She’d seen one of these" | | 16 | "She didn’t turn." | | 17 | "It was a gateway." | | 18 | "She met his gaze." | | 19 | "It was a message." |
| | ratio | 0.296 | |
| 72.68% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 55 | | totalSentences | 71 | | matches | | 0 | "The abandoned Tube station beneath" | | 1 | "Detective Harlow Quinn stepped over" | | 2 | "The air hung thick, the" | | 3 | "She adjusted the worn leather" | | 4 | "PC Harris stood by a" | | 5 | "He nodded as she approached," | | 6 | "She didn’t answer." | | 7 | "Nothing about this scene was" | | 8 | "The victim—a man in a" | | 9 | "It was the lack of" | | 10 | "Harlow crouched, her sharp jaw" | | 11 | "The man’s fingers were curled" | | 12 | "She reached for his wrist," | | 13 | "The skin was cold, but" | | 14 | "It was the cold of" | | 15 | "Something that made the hairs" | | 16 | "She stood, scanning the platform." | | 17 | "The station had been abandoned" | | 18 | "It smelled metallic, but wrong." | | 19 | "Harris said, following her gaze" |
| | ratio | 0.775 | |
| 70.42% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 71 | | matches | | 0 | "Because if she was right," |
| | ratio | 0.014 | |
| 87.91% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 26 | | technicalSentenceCount | 2 | | matches | | 0 | "Something that made the hairs on her arms stand on end." | | 1 | "The torchlight flickered, as if something were draining the batteries." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 3 | | uselessAdditionCount | 1 | | matches | | 0 | "she said, her voice steady despite the unease coiling in her gut" |
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| 83.33% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 3 | | fancyCount | 1 | | fancyTags | | 0 | "Harris muttered (mutter)" |
| | dialogueSentences | 15 | | tagDensity | 0.2 | | leniency | 0.4 | | rawRatio | 0.333 | | effectiveRatio | 0.133 | |