| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 9 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 22 | | tagDensity | 0.409 | | leniency | 0.818 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 90.26% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1540 | | totalAiIsmAdverbs | 3 | | 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) | |
| 57.79% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1540 | | totalAiIsms | 13 | | found | | | highlights | | 0 | "could feel" | | 1 | "measured" | | 2 | "weight" | | 3 | "streaming" | | 4 | "potential" | | 5 | "footsteps" | | 6 | "gloom" | | 7 | "symphony" | | 8 | "whisper" | | 9 | "pulsed" | | 10 | "warmth" | | 11 | "crystallized" |
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| 66.67% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 3 | | maxInWindow | 2 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 2 |
| | 1 | | label | "air was thick with" | | count | 1 |
|
| | highlights | | 0 | "eyes narrowed" | | 1 | "eyes widened" | | 2 | "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 | 92 | | matches | (empty) | |
| 49.69% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 4 | | narrationSentences | 92 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 104 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 44 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1525 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 11 | | unquotedAttributions | 0 | | matches | (empty) | |
| 83.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 49 | | wordCount | 1351 | | uniqueNames | 16 | | maxNameDensity | 1.18 | | worstName | "Quinn" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Quinn" | | discoveredNames | | Dean | 1 | | Street | 1 | | Detective | 1 | | Harlow | 1 | | Quinn | 16 | | Herrera | 10 | | Saint | 1 | | Christopher | 1 | | Seville | 1 | | London | 1 | | Raven | 2 | | Nest | 2 | | Morris | 6 | | Soho | 1 | | Veil | 2 | | Market | 2 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Herrera" | | 3 | "Saint" | | 4 | "Christopher" | | 5 | "Raven" | | 6 | "Morris" |
| | places | | 0 | "Dean" | | 1 | "Street" | | 2 | "Seville" | | 3 | "London" | | 4 | "Soho" | | 5 | "Veil" |
| | globalScore | 0.908 | | windowScore | 0.833 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 81 | | glossingSentenceCount | 1 | | matches | | 0 | "fury that seemed to match her rising agitation" |
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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 | 1525 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 104 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 38 | | mean | 40.13 | | std | 23.88 | | cv | 0.595 | | sampleLengths | | 0 | 82 | | 1 | 20 | | 2 | 83 | | 3 | 27 | | 4 | 19 | | 5 | 32 | | 6 | 10 | | 7 | 34 | | 8 | 75 | | 9 | 66 | | 10 | 58 | | 11 | 68 | | 12 | 7 | | 13 | 76 | | 14 | 67 | | 15 | 64 | | 16 | 53 | | 17 | 62 | | 18 | 56 | | 19 | 17 | | 20 | 74 | | 21 | 43 | | 22 | 5 | | 23 | 27 | | 24 | 18 | | 25 | 40 | | 26 | 17 | | 27 | 16 | | 28 | 36 | | 29 | 26 | | 30 | 41 | | 31 | 18 | | 32 | 35 | | 33 | 14 | | 34 | 9 | | 35 | 14 | | 36 | 64 | | 37 | 52 |
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| 90.01% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 4 | | totalSentences | 92 | | matches | | 0 | "been replaced" | | 1 | "were required" | | 2 | "were compromised" | | 3 | "was hushed" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 3 | | totalVerbs | 231 | | matches | | 0 | "was going" | | 1 | "was running" | | 2 | "was saying" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 15 | | semicolonCount | 1 | | flaggedSentences | 13 | | totalSentences | 104 | | ratio | 0.125 | | matches | | 0 | "She could feel her heart hammering against her ribs like a trapped bird, but her breathing remained controlled, measured—the product of eighteen years in uniform and one partner's death that still haunted her dreams." | | 1 | "Tomás Herrera—former paramedic, current underground medical provider for whatever clique Quinn suspected had been murdering her informants." | | 2 | "This wasn't about protocol anymore—it was about DS Morris, about the case that had gone cold, about the whispers in the station that some things were better left buried." | | 3 | "She'd spent three years chasing ghosts; she wasn't about to let this lead go cold." | | 4 | "But beneath it all, she could hear something else—the telltale hum of electricity, the whisper of something artificial and concealed." | | 5 | "But she needed to see where he was going, needed to understand what had claimed three of her witnesses—and possibly Morris himself." | | 6 | "The entrance was cleverly concealed—perhaps behind the bookshelf she'd heard rumors about in the back room of The Raven's Nest." | | 7 | "She pulled her jacket tighter, but the damage was done—her weapons were compromised, her mobility hindered." | | 8 | "Time was running out—Herrera couldn't have gone far, but the market moved with a will of its own, shifting locations with each full moon." | | 9 | "Some wore the distinctive symbols of various supernatural factions—serpents, ravens, pentacles—each more menacing than the last." | | 10 | "Herrera stood at a stall selling medical supplies, the proprietor—a gaunt figure with eyes like chips of obsidian—handing him a small vial." | | 11 | "Before Quinn could respond, the stall owner—who might have been a vampire, a demon, or something else entirely—moved with inhuman speed." | | 12 | "Quinn did what she'd never done before—she touched the bone token in her jacket pocket, whispered the words she'd learned from Morris's final, unfinished case file, and stepped through the exit that opened before her like a door in reality itself." |
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| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1367 | | adjectiveStacks | 1 | | stackExamples | | 0 | "former paramedic, current underground" |
| | adverbCount | 36 | | adverbRatio | 0.026335040234089245 | | lyAdverbCount | 13 | | lyAdverbRatio | 0.009509875640087784 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 104 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 104 | | mean | 14.66 | | std | 8.42 | | cv | 0.574 | | sampleLengths | | 0 | 29 | | 1 | 19 | | 2 | 34 | | 3 | 20 | | 4 | 18 | | 5 | 16 | | 6 | 17 | | 7 | 32 | | 8 | 4 | | 9 | 23 | | 10 | 19 | | 11 | 22 | | 12 | 10 | | 13 | 3 | | 14 | 7 | | 15 | 13 | | 16 | 21 | | 17 | 18 | | 18 | 7 | | 19 | 43 | | 20 | 7 | | 21 | 3 | | 22 | 17 | | 23 | 17 | | 24 | 29 | | 25 | 17 | | 26 | 17 | | 27 | 9 | | 28 | 15 | | 29 | 21 | | 30 | 9 | | 31 | 18 | | 32 | 20 | | 33 | 7 | | 34 | 4 | | 35 | 5 | | 36 | 17 | | 37 | 10 | | 38 | 18 | | 39 | 22 | | 40 | 14 | | 41 | 13 | | 42 | 10 | | 43 | 16 | | 44 | 5 | | 45 | 9 | | 46 | 16 | | 47 | 20 | | 48 | 28 | | 49 | 11 |
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| 66.35% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 1 | | diversityRatio | 0.40384615384615385 | | totalSentences | 104 | | uniqueOpeners | 42 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 4 | | totalSentences | 92 | | matches | | 0 | "Instead, he turned and began" | | 1 | "Then she saw it: a" | | 2 | "Then, with a soft click," | | 3 | "Then Herrera turned and moved" |
| | ratio | 0.043 | |
| 98.26% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 28 | | totalSentences | 92 | | matches | | 0 | "Her leather watch glinted under" | | 1 | "She could feel her heart" | | 2 | "she called into the darkness," | | 3 | "His olive skin was slick" | | 4 | "He paused, turning slightly." | | 5 | "he said, his voice carrying" | | 6 | "She tilted her head toward" | | 7 | "She followed, her boots splashing" | | 8 | "She'd spent three years chasing" | | 9 | "Her training screamed caution." | | 10 | "Her experience counseled against it." | | 11 | "She pulled out her phone," | | 12 | "She'd stumbled upon mentions of" | | 13 | "Her trench coat caught on" | | 14 | "She pulled her jacket tighter," | | 15 | "She stepped through the opening," | | 16 | "Their conversation was hushed, urgent." | | 17 | "She'd never drawn a weapon" | | 18 | "She stepped into the open," | | 19 | "He laughed, but it was" |
| | ratio | 0.304 | |
| 63.26% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 73 | | totalSentences | 92 | | matches | | 0 | "The rain had been falling" | | 1 | "Her leather watch glinted under" | | 2 | "She could feel her heart" | | 3 | "she called into the darkness," | | 4 | "Tomás Herrera—former paramedic, current underground" | | 5 | "His olive skin was slick" | | 6 | "He paused, turning slightly." | | 7 | "The Saint Christopher medallion around" | | 8 | "he said, his voice carrying" | | 9 | "Quinn straightened, water streaming down" | | 10 | "Herrera's expression hardened." | | 11 | "Quinn's brown eyes narrowed as" | | 12 | "The man's hand moved to" | | 13 | "Quinn's trained eye caught the" | | 14 | "She tilted her head toward" | | 15 | "Herrera didn't answer." | | 16 | "Quinn's hand instinctively went to" | | 17 | "This wasn't about protocol anymore—it" | | 18 | "She followed, her boots splashing" | | 19 | "The rain had intensified, hammering" |
| | ratio | 0.793 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 92 | | matches | | 0 | "If she missed him now," | | 1 | "Before Quinn could respond, the" |
| | ratio | 0.022 | |
| 49.18% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 61 | | technicalSentenceCount | 8 | | matches | | 0 | "Her leather watch glinted under the flickering streetlight, its face obscured by water that had seeped through her sleeve." | | 1 | "His olive skin was slick with rain, and she could see the scar that ran along his left forearm, pale against his dark hand as he pulled it into his coat pocket." | | 2 | "The rain had intensified, hammering the city with a fury that seemed to match her rising agitation." | | 3 | "Herrera ducked into an alley that sloped downward, the sound of his footsteps growing fainter as he disappeared into the gloom." | | 4 | "She'd stumbled upon mentions of it in old case files, notes scribbled by Morris before his disappearance, references to a market that didn't exist on any offici…" | | 5 | "Stalls made of salvaged metal and glowing crystals sold curiosities that made her skin crawl: vials of what might have been dragon's breath, necklaces that puls…" | | 6 | "Quinn did what she'd never done before—she touched the bone token in her jacket pocket, whispered the words she'd learned from Morris's final, unfinished case f…" | | 7 | "She didn't look back as she emerged onto the street, the rain washing over her face, carrying with it the weight of what she'd seen and the knowledge that some …" |
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| 13.89% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 9 | | uselessAdditionCount | 2 | | matches | | 0 | "Quinn straightened, water streaming down her sharp jawline" | | 1 | "she called, urgency cutting through her fear" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 6 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 22 | | tagDensity | 0.273 | | leniency | 0.545 | | rawRatio | 0.167 | | effectiveRatio | 0.091 | |