| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 2 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 7 | | tagDensity | 0.286 | | leniency | 0.571 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 82.89% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1169 | | totalAiIsmAdverbs | 4 | | found | | | highlights | | 0 | "sharply" | | 1 | "quickly" | | 2 | "slightly" | | 3 | "cautiously" |
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| 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) | |
| 57.23% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1169 | | totalAiIsms | 10 | | found | | | highlights | | 0 | "fractured" | | 1 | "scanned" | | 2 | "flickered" | | 3 | "warmth" | | 4 | "treacherous" | | 5 | "flicker" | | 6 | "echoing" | | 7 | "echoed" | | 8 | "pulse" | | 9 | "raced" |
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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 | 86 | | matches | (empty) | |
| 93.02% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 2 | | narrationSentences | 86 | | filterMatches | | | hedgeMatches | | |
| 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 | | maxSentenceWordsSeen | 37 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 5 | | markdownWords | 9 | | totalWords | 1155 | | ratio | 0.008 | | matches | | 0 | "The Raven’s Nest" | | 1 | "The Raven’s Nest" | | 2 | "off" | | 3 | "other" | | 4 | "impossible" |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 5 | | unquotedAttributions | 0 | | matches | (empty) | |
| 96.19% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 31 | | wordCount | 1115 | | uniqueNames | 11 | | maxNameDensity | 1.08 | | worstName | "Quinn" | | maxWindowNameDensity | 2 | | worstWindowName | "Quinn" | | discoveredNames | | Harlow | 1 | | Quinn | 12 | | London | 1 | | Greek | 1 | | Street | 1 | | Raven | 2 | | Tomás | 1 | | Herrera | 6 | | Saint | 2 | | Christopher | 2 | | Morris | 2 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Raven" | | 3 | "Tomás" | | 4 | "Herrera" | | 5 | "Saint" | | 6 | "Christopher" | | 7 | "Morris" |
| | places | | 0 | "London" | | 1 | "Greek" | | 2 | "Street" |
| | globalScore | 0.962 | | windowScore | 1 | |
| 0.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 63 | | glossingSentenceCount | 4 | | matches | | 0 | "looked like they’d never been opened" | | 1 | "something like panic, before he ducked left" | | 2 | "looked like an abandoned building" | | 3 | "artifacts that seemed to hum with energy" |
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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 | 1155 | | 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 | 38.5 | | std | 30.84 | | cv | 0.801 | | sampleLengths | | 0 | 90 | | 1 | 95 | | 2 | 66 | | 3 | 89 | | 4 | 5 | | 5 | 71 | | 6 | 46 | | 7 | 83 | | 8 | 71 | | 9 | 4 | | 10 | 62 | | 11 | 8 | | 12 | 63 | | 13 | 13 | | 14 | 60 | | 15 | 15 | | 16 | 5 | | 17 | 81 | | 18 | 16 | | 19 | 7 | | 20 | 35 | | 21 | 7 | | 22 | 7 | | 23 | 16 | | 24 | 9 | | 25 | 22 | | 26 | 45 | | 27 | 17 | | 28 | 32 | | 29 | 15 |
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| 84.86% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 5 | | totalSentences | 86 | | matches | | 0 | "was gone" | | 1 | "been opened" | | 2 | "was gone" | | 3 | "was carved" | | 4 | "been found" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 185 | | matches | | 0 | "was running" | | 1 | "wasn’t leaving" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 14 | | semicolonCount | 0 | | flaggedSentences | 11 | | totalSentences | 91 | | ratio | 0.121 | | matches | | 0 | "Detective Harlow Quinn moved with the precision of a woman who had spent too many nights like this—chasing shadows through the underbelly of London." | | 1 | "The bar was a known haunt for the kind of people who didn’t like cops—especially not ones asking questions about missing persons and unsolved cases with too many loose ends." | | 2 | "She was here for the man who had just ducked inside—Tomás Herrera, the former paramedic with the scarred forearm and the Saint Christopher medallion." | | 3 | "Her eyes adjusted quickly, sweeping over the patrons—most of them too absorbed in their drinks to notice her, but a few glancing up with the wary eyes of people who knew trouble when they saw it." | | 4 | "The bookshelf was just as she’d heard—lined with leather-bound volumes that looked like they’d never been opened." | | 5 | "The alley opened into a wider street, the kind that tourists never saw—boarded-up shops, graffiti-scrawled walls, the occasional flicker of a security light." | | 6 | "The walls were damp, the scent of mildew and something older—something metallic—filling her nose." | | 7 | "She thought of DS Morris, her partner, the way his body had been found three years ago—no signs of struggle, no cause of death, just a look of frozen terror on his face." | | 8 | "Stalls lined the cavernous room, their wares displayed under glass or hanging from hooks—vials of glowing liquid, bundles of dried herbs, strange artifacts that seemed to hum with energy." | | 9 | "She’d heard rumors—whispers of a market that moved with the moon, where the things sold weren’t just illegal, they were *impossible*." | | 10 | "And if this place held the answers she needed—answers about Morris, about the cases that had haunted her for years—then she wasn’t leaving without them." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1133 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 28 | | adverbRatio | 0.02471315092674316 | | lyAdverbCount | 8 | | lyAdverbRatio | 0.00706090026478376 | |
| 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 | 12.69 | | std | 8.22 | | cv | 0.647 | | sampleLengths | | 0 | 23 | | 1 | 24 | | 2 | 23 | | 3 | 20 | | 4 | 25 | | 5 | 16 | | 6 | 19 | | 7 | 5 | | 8 | 30 | | 9 | 10 | | 10 | 6 | | 11 | 24 | | 12 | 21 | | 13 | 5 | | 14 | 19 | | 15 | 22 | | 16 | 36 | | 17 | 5 | | 18 | 7 | | 19 | 3 | | 20 | 2 | | 21 | 19 | | 22 | 17 | | 23 | 17 | | 24 | 18 | | 25 | 14 | | 26 | 15 | | 27 | 3 | | 28 | 14 | | 29 | 22 | | 30 | 18 | | 31 | 23 | | 32 | 20 | | 33 | 5 | | 34 | 18 | | 35 | 23 | | 36 | 7 | | 37 | 18 | | 38 | 4 | | 39 | 8 | | 40 | 20 | | 41 | 10 | | 42 | 13 | | 43 | 11 | | 44 | 8 | | 45 | 10 | | 46 | 14 | | 47 | 12 | | 48 | 15 | | 49 | 12 |
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| 39.01% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 10 | | diversityRatio | 0.24175824175824176 | | totalSentences | 91 | | uniqueOpeners | 22 | |
| 41.67% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 80 | | matches | | | ratio | 0.013 | |
| 75.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 29 | | totalSentences | 80 | | matches | | 0 | "Her breath came in controlled" | | 1 | "She adjusted the worn leather" | | 2 | "She slowed, her instincts prickling." | | 3 | "She wasn’t here for the" | | 4 | "She was here for the" | | 5 | "He’d been at the scene" | | 6 | "She pushed through the door" | | 7 | "Her eyes adjusted quickly, sweeping" | | 8 | "He wasn’t at any of" | | 9 | "She moved toward the back" | | 10 | "She ran her fingers along" | | 11 | "She stepped inside, pulling the" | | 12 | "He glanced back once, his" | | 13 | "She wasn’t as young as" | | 14 | "She closed the distance, her" | | 15 | "She approached cautiously, her hand" | | 16 | "She pushed the door open" | | 17 | "She didn’t recognize it, but" | | 18 | "She thought of DS Morris," | | 19 | "She thought of the cases" |
| | ratio | 0.363 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 75 | | totalSentences | 80 | | matches | | 0 | "The rain came down in" | | 1 | "Detective Harlow Quinn moved with" | | 2 | "Her breath came in controlled" | | 3 | "The suspect had vanished near" | | 4 | "She adjusted the worn leather" | | 5 | "The soles of her boots" | | 6 | "She slowed, her instincts prickling." | | 7 | "The bar was a known" | | 8 | "Quinn exhaled sharply, her breath" | | 9 | "She wasn’t here for the" | | 10 | "She was here for the" | | 11 | "He’d been at the scene" | | 12 | "She pushed through the door" | | 13 | "The air was thick with" | | 14 | "Her eyes adjusted quickly, sweeping" | | 15 | "Herrera wasn’t at the bar." | | 16 | "He wasn’t at any of" | | 17 | "Quinn’s jaw tightened." | | 18 | "She moved toward the back" | | 19 | "The bookshelf was just as" |
| | ratio | 0.938 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 80 | | matches | (empty) | | ratio | 0 | |
| 2.80% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 51 | | technicalSentenceCount | 10 | | matches | | 0 | "The rain came down in sheets, turning the pavement into a slick mirror that reflected the fractured glow of neon signs and streetlamps." | | 1 | "Detective Harlow Quinn moved with the precision of a woman who had spent too many nights like this—chasing shadows through the underbelly of London." | | 2 | "The bar was a known haunt for the kind of people who didn’t like cops—especially not ones asking questions about missing persons and unsolved cases with too man…" | | 3 | "She was here for the man who had just ducked inside—Tomás Herrera, the former paramedic with the scarred forearm and the Saint Christopher medallion." | | 4 | "Her eyes adjusted quickly, sweeping over the patrons—most of them too absorbed in their drinks to notice her, but a few glancing up with the wary eyes of people…" | | 5 | "The bookshelf was just as she’d heard—lined with leather-bound volumes that looked like they’d never been opened." | | 6 | "A symbol was carved into the center of it, something that made her skin prickle." | | 7 | "The space beyond was vast, lit by flickering lanterns that cast long, shifting shadows across the walls." | | 8 | "Stalls lined the cavernous room, their wares displayed under glass or hanging from hooks—vials of glowing liquid, bundles of dried herbs, strange artifacts that…" | | 9 | "The people here moved like ghosts, their faces obscured by hoods or masks, their voices a low murmur that echoed unnaturally." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 2 | | uselessAdditionCount | 1 | | matches | | 0 | "he said, as if that explained everything" |
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| 7.14% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 2 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 7 | | tagDensity | 0.286 | | leniency | 0.571 | | rawRatio | 0.5 | | effectiveRatio | 0.286 | |