| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 18 | | adverbTagCount | 2 | | adverbTags | | 0 | "she said quietly [quietly]" | | 1 | "She glanced once [once]" |
| | dialogueSentences | 53 | | tagDensity | 0.34 | | leniency | 0.679 | | rawRatio | 0.111 | | effectiveRatio | 0.075 | |
| 93.85% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1625 | | 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) | |
| 50.77% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1625 | | totalAiIsms | 16 | | found | | | highlights | | 0 | "footsteps" | | 1 | "echoing" | | 2 | "flickered" | | 3 | "gloom" | | 4 | "scanned" | | 5 | "traced" | | 6 | "weight" | | 7 | "framework" | | 8 | "etched" | | 9 | "intricate" | | 10 | "spectral" | | 11 | "quivered" | | 12 | "glistening" | | 13 | "unwavering" | | 14 | "racing" |
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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 | 3 | | narrationSentences | 140 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 172 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 54 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 2 | | markdownWords | 2 | | totalWords | 1611 | | ratio | 0.001 | | matches | | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 18 | | unquotedAttributions | 0 | | matches | (empty) | |
| 66.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 41 | | wordCount | 1138 | | uniqueNames | 11 | | maxNameDensity | 1.23 | | worstName | "Quinn" | | maxWindowNameDensity | 3 | | worstWindowName | "Quinn" | | discoveredNames | | Tube | 1 | | Harlow | 1 | | Quinn | 14 | | Sergeant | 1 | | Greaves | 11 | | Camden | 1 | | Bovril | 1 | | Veil | 2 | | Market | 5 | | Compass | 1 | | Morris | 3 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Sergeant" | | 3 | "Greaves" | | 4 | "Bovril" | | 5 | "Market" | | 6 | "Morris" |
| | places | | | globalScore | 0.885 | | windowScore | 0.667 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 88 | | glossingSentenceCount | 1 | | matches | | 0 | "liquids that seemed to move on their own" |
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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 | 1611 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 2 | | totalSentences | 172 | | matches | | 0 | "understood that she looking, that she’d" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 66 | | mean | 24.41 | | std | 16.25 | | cv | 0.666 | | sampleLengths | | 0 | 50 | | 1 | 33 | | 2 | 40 | | 3 | 66 | | 4 | 31 | | 5 | 45 | | 6 | 38 | | 7 | 39 | | 8 | 21 | | 9 | 22 | | 10 | 28 | | 11 | 6 | | 12 | 61 | | 13 | 23 | | 14 | 5 | | 15 | 32 | | 16 | 4 | | 17 | 8 | | 18 | 54 | | 19 | 10 | | 20 | 27 | | 21 | 12 | | 22 | 8 | | 23 | 10 | | 24 | 8 | | 25 | 20 | | 26 | 33 | | 27 | 35 | | 28 | 2 | | 29 | 33 | | 30 | 3 | | 31 | 7 | | 32 | 15 | | 33 | 24 | | 34 | 37 | | 35 | 26 | | 36 | 4 | | 37 | 26 | | 38 | 30 | | 39 | 19 | | 40 | 5 | | 41 | 16 | | 42 | 36 | | 43 | 17 | | 44 | 5 | | 45 | 47 | | 46 | 26 | | 47 | 10 | | 48 | 7 | | 49 | 33 |
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| 80.20% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 10 | | totalSentences | 140 | | matches | | 0 | "was cordoned" | | 1 | "was unbuttoned" | | 2 | "was curled" | | 3 | "was etched" | | 4 | "were gone" | | 5 | "were washed" | | 6 | "been found" | | 7 | "been killed" | | 8 | "been killed" | | 9 | "was buried" |
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| 97.96% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 3 | | totalVerbs | 196 | | matches | | 0 | "wasn’t pointing" | | 1 | "was pointing" | | 2 | "was looking" |
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| 43.19% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 7 | | semicolonCount | 0 | | flaggedSentences | 6 | | totalSentences | 172 | | ratio | 0.035 | | matches | | 0 | "The air in the abandoned Tube station was cold and thick with the scent of damp concrete and something else—ozone, maybe, or rust." | | 1 | "Graffiti covered the vintage advertising tiles—faded exhortations to drink Bovril faded between modern tags." | | 2 | "“Place was empty when uniforms arrived. Looks like it was cleared out in a hurry. Left some stuff behind.” He gestured to a stall further down the platform—a collapsed wooden framework, a scatter of strange items: brass scales, bundles of dried herbs, small vials containing liquids that seemed to move on their own." | | 3 | "The forensic tech had bagged the item from the victim’s hand—a small brass compass." | | 4 | "The tunnel floor was a mess of debris—brick fragments, old newspapers, pooled water." | | 5 | "And someone—the tipster—wanted the police to find the body, to find the compass, to maybe even find the door." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1149 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 26 | | adverbRatio | 0.022628372497824196 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.004351610095735422 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 172 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 172 | | mean | 9.37 | | std | 7.01 | | cv | 0.748 | | sampleLengths | | 0 | 23 | | 1 | 15 | | 2 | 12 | | 3 | 11 | | 4 | 5 | | 5 | 17 | | 6 | 11 | | 7 | 21 | | 8 | 8 | | 9 | 10 | | 10 | 4 | | 11 | 9 | | 12 | 14 | | 13 | 6 | | 14 | 7 | | 15 | 5 | | 16 | 11 | | 17 | 19 | | 18 | 2 | | 19 | 10 | | 20 | 10 | | 21 | 10 | | 22 | 3 | | 23 | 12 | | 24 | 6 | | 25 | 3 | | 26 | 1 | | 27 | 6 | | 28 | 32 | | 29 | 5 | | 30 | 5 | | 31 | 8 | | 32 | 5 | | 33 | 5 | | 34 | 6 | | 35 | 5 | | 36 | 10 | | 37 | 11 | | 38 | 9 | | 39 | 10 | | 40 | 3 | | 41 | 28 | | 42 | 6 | | 43 | 8 | | 44 | 53 | | 45 | 3 | | 46 | 11 | | 47 | 2 | | 48 | 7 | | 49 | 5 |
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| 45.16% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 14 | | diversityRatio | 0.31976744186046513 | | totalSentences | 172 | | uniqueOpeners | 55 | |
| 26.67% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 125 | | matches | | 0 | "Too black, with a faint" |
| | ratio | 0.008 | |
| 82.40% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 43 | | totalSentences | 125 | | matches | | 0 | "She scanned the platform." | | 1 | "It was the Camden branch," | | 2 | "She’d tracked rumors of it" | | 3 | "She didn’t have one, but" | | 4 | "His face was slack, eyes" | | 5 | "It was blank." | | 6 | "She didn’t touch the body." | | 7 | "Her eyes traced the lines" | | 8 | "His left hand was curled" | | 9 | "she said to a forensic" | | 10 | "He gestured to a stall" | | 11 | "It was pointing straight into" | | 12 | "She knew what it was." | | 13 | "She’d read descriptions in the" | | 14 | "It pointed to supernatural rifts." | | 15 | "She looked from the compass" | | 16 | "It carried a faint, metallic" | | 17 | "She walked to the platform" | | 18 | "She switched on her torch," | | 19 | "It had the same iridescent" |
| | ratio | 0.344 | |
| 24.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 109 | | totalSentences | 125 | | matches | | 0 | "The air in the abandoned" | | 1 | "Detective Harlow Quinn descended the" | | 2 | "The emergency lights strung along" | | 3 | "The scene was cordoned off" | | 4 | "A forensics team in white" | | 5 | "A figure separated from the" | | 6 | "Detective Sergeant Greaves, a man" | | 7 | "Quinn’s voice was flat" | | 8 | "She scanned the platform." | | 9 | "It was the Camden branch," | | 10 | "Graffiti covered the vintage advertising" | | 11 | "The Veil Market used this" | | 12 | "She’d tracked rumors of it" | | 13 | "Entry required a bone token." | | 14 | "She didn’t have one, but" | | 15 | "Greaves led her past a" | | 16 | "The body lay near the" | | 17 | "His face was slack, eyes" | | 18 | "The expression wasn’t fear or" | | 19 | "It was blank." |
| | ratio | 0.872 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 3 | | totalSentences | 125 | | matches | | 0 | "To expose the Market?" | | 1 | "To lure someone in?" | | 2 | "To lure *her* in?" |
| | ratio | 0.024 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 40 | | technicalSentenceCount | 2 | | matches | | 0 | "Detective Sergeant Greaves, a man with a perpetually concerned expression and a bad knee that made him list to one side." | | 1 | "Someone who understood that she was looking, that she’d been piecing together the supernatural truths behind the city’s unexplained crimes." |
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| 69.44% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 18 | | uselessAdditionCount | 2 | | matches | | 0 | "she heard, the words leaving her lips before she could filter them" | | 1 | "she ordered, her voice leaving no room for argument" |
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| 93.40% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 12 | | fancyCount | 3 | | fancyTags | | 0 | "she heard (hear)" | | 1 | "Quinn muttered (mutter)" | | 2 | "she ordered (order)" |
| | dialogueSentences | 53 | | tagDensity | 0.226 | | leniency | 0.453 | | rawRatio | 0.25 | | effectiveRatio | 0.113 | |