| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 9 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 29 | | tagDensity | 0.31 | | leniency | 0.621 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 84.51% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1614 | | totalAiIsmAdverbs | 5 | | found | | | highlights | | 0 | "cautiously" | | 1 | "really" | | 2 | "slowly" | | 3 | "very" |
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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) | |
| 25.65% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1614 | | totalAiIsms | 24 | | found | | | highlights | | 0 | "glistening" | | 1 | "weight" | | 2 | "pulse" | | 3 | "gleaming" | | 4 | "gloom" | | 5 | "footsteps" | | 6 | "echoed" | | 7 | "flickered" | | 8 | "vibrated" | | 9 | "resonated" | | 10 | "silence" | | 11 | "whisper" | | 12 | "stomach" | | 13 | "could feel" | | 14 | "calculating" | | 15 | "shattered" | | 16 | "tension" |
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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 | 143 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 0 | | narrationSentences | 143 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 162 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 33 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 6 | | markdownWords | 15 | | totalWords | 1597 | | ratio | 0.009 | | matches | | 0 | "The Raven’s Nest" | | 1 | "Tomás Herrera" | | 2 | "This isn’t right." | | 3 | "The Veil Market." | | 4 | "that" | | 5 | "The Raven’s Nest" |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 13 | | unquotedAttributions | 0 | | matches | (empty) | |
| 50.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 53 | | wordCount | 1412 | | uniqueNames | 11 | | maxNameDensity | 1.91 | | worstName | "Quinn" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Quinn" | | discoveredNames | | Soho | 1 | | Harlow | 1 | | Quinn | 27 | | Raven | 1 | | Herrera | 17 | | Camden | 1 | | Tube | 1 | | Silence | 1 | | Veil | 1 | | Saint | 1 | | Christopher | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Raven" | | 3 | "Herrera" | | 4 | "Veil" | | 5 | "Saint" | | 6 | "Christopher" |
| | places | | | globalScore | 0.544 | | windowScore | 0.5 | |
| 75.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 100 | | glossingSentenceCount | 3 | | matches | | 0 | "quite place" | | 1 | "quite music but something deeper, something that resonated in her bones" | | 2 | "quite human" |
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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 | 1597 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 162 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 60 | | mean | 26.62 | | std | 20.9 | | cv | 0.785 | | sampleLengths | | 0 | 75 | | 1 | 74 | | 2 | 55 | | 3 | 64 | | 4 | 11 | | 5 | 63 | | 6 | 9 | | 7 | 30 | | 8 | 47 | | 9 | 48 | | 10 | 46 | | 11 | 33 | | 12 | 22 | | 13 | 1 | | 14 | 51 | | 15 | 6 | | 16 | 67 | | 17 | 6 | | 18 | 31 | | 19 | 2 | | 20 | 63 | | 21 | 5 | | 22 | 3 | | 23 | 8 | | 24 | 32 | | 25 | 16 | | 26 | 6 | | 27 | 22 | | 28 | 18 | | 29 | 50 | | 30 | 43 | | 31 | 6 | | 32 | 6 | | 33 | 11 | | 34 | 26 | | 35 | 13 | | 36 | 20 | | 37 | 5 | | 38 | 63 | | 39 | 8 | | 40 | 7 | | 41 | 41 | | 42 | 3 | | 43 | 28 | | 44 | 36 | | 45 | 30 | | 46 | 4 | | 47 | 34 | | 48 | 52 | | 49 | 13 |
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| 97.90% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 143 | | matches | | 0 | "been flagged" | | 1 | "being hunted" | | 2 | "been abandoned" |
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| 94.18% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 4 | | totalVerbs | 252 | | matches | | 0 | "was heading" | | 1 | "was talking" | | 2 | "wasn’t leaving" | | 3 | "was hunting" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 18 | | semicolonCount | 0 | | flaggedSentences | 11 | | totalSentences | 162 | | ratio | 0.068 | | matches | | 0 | "The suspect—lean, wiry, moving with the desperate agility of a cornered rat—ducked into an alley between a boarded-up record shop and a kebab joint reeking of grease and stale onions." | | 1 | "The suspect—*Tomás Herrera*, according to the file—had been flagged for off-the-books medical work, the kind that didn’t show up in NHS records." | | 2 | "She’d spent years chasing ghosts—literal and figurative—and she wasn’t about to let this one slip through her fingers." | | 3 | "Quinn hesitated for half a second—just long enough to register the cold prickle of unease crawling up her spine—before she followed." | | 4 | "The torchlight flickered over something on the ground—a bone, small and yellowed, lying in the dust." | | 5 | "The air smelled different here—sharp, metallic, with an underlying sweetness that made her stomach clench." | | 6 | "People—if they could be called that—milled about, their forms shifting in the dim light." | | 7 | "But something—instinct, stubbornness, the ghost of her lost partner—kept her rooted in place." | | 8 | "She could feel the weight of the bone token in her pocket—the one she’d found outside the station, the one that had let her pass through the barriers." | | 9 | "Quinn barely had time to react before a hand—too long, too many fingers—grabbed her arm." | | 10 | "Ahead, a faint glow cut through the darkness—the exit." |
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| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1437 | | adjectiveStacks | 1 | | stackExamples | | 0 | "suspect—lean, wiry, moving" |
| | adverbCount | 43 | | adverbRatio | 0.029923451635351428 | | lyAdverbCount | 11 | | lyAdverbRatio | 0.007654836464857342 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 162 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 162 | | mean | 9.86 | | std | 6.37 | | cv | 0.646 | | sampleLengths | | 0 | 14 | | 1 | 26 | | 2 | 30 | | 3 | 3 | | 4 | 2 | | 5 | 21 | | 6 | 23 | | 7 | 22 | | 8 | 6 | | 9 | 2 | | 10 | 14 | | 11 | 13 | | 12 | 2 | | 13 | 8 | | 14 | 18 | | 15 | 25 | | 16 | 14 | | 17 | 1 | | 18 | 1 | | 19 | 23 | | 20 | 11 | | 21 | 3 | | 22 | 13 | | 23 | 15 | | 24 | 11 | | 25 | 21 | | 26 | 6 | | 27 | 3 | | 28 | 18 | | 29 | 5 | | 30 | 7 | | 31 | 5 | | 32 | 21 | | 33 | 21 | | 34 | 13 | | 35 | 15 | | 36 | 16 | | 37 | 4 | | 38 | 8 | | 39 | 10 | | 40 | 16 | | 41 | 7 | | 42 | 3 | | 43 | 2 | | 44 | 22 | | 45 | 11 | | 46 | 9 | | 47 | 13 | | 48 | 1 | | 49 | 5 |
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| 43.21% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 11 | | diversityRatio | 0.2839506172839506 | | totalSentences | 162 | | uniqueOpeners | 46 | |
| 51.28% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 130 | | matches | | 0 | "Then, a whisper of movement." | | 1 | "Then, slowly, he nodded." |
| | ratio | 0.015 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 39 | | totalSentences | 130 | | matches | | 0 | "Her left wrist ached where" | | 1 | "She’d spent years chasing ghosts—literal" | | 2 | "He glanced back, his warm" | | 3 | "He vaulted over a low" | | 4 | "He ripped one of the" | | 5 | "She crouched, her fingers hovering" | | 6 | "It wasn’t human." | | 7 | "she called, her voice swallowed" | | 8 | "She followed, her boots crunching" | | 9 | "She rounded the corner and" | | 10 | "She’d heard the rumors, of" | | 11 | "He was talking to a" | | 12 | "She should turn back." | | 13 | "She should call for backup." | | 14 | "She took a step forward." | | 15 | "She could feel their eyes" | | 16 | "She was an intruder here." | | 17 | "he said, his voice tight" | | 18 | "They spread their hands, gesturing" | | 19 | "She could feel the weight" |
| | ratio | 0.3 | |
| 6.15% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 118 | | totalSentences | 130 | | matches | | 0 | "The rain fell in sheets," | | 1 | "Detective Harlow Quinn’s boots splashed" | | 2 | "The suspect—lean, wiry, moving with" | | 3 | "Quinn didn’t hesitate." | | 4 | "Her left wrist ached where" | | 5 | "The suspect—*Tomás Herrera*, according to" | | 6 | "The kind that got people" | | 7 | "The alley narrowed, the brick" | | 8 | "Quinn’s fingers brushed the baton" | | 9 | "The suspect was fast, but" | | 10 | "She’d spent years chasing ghosts—literal" | | 11 | "Herrera skidded around a dumpster," | | 12 | "He glanced back, his warm" | | 13 | "Quinn barked, her voice cutting" | | 14 | "Herrera didn’t stop." | | 15 | "He vaulted over a low" | | 16 | "Quinn was right behind him," | | 17 | "The fence rattled under her" | | 18 | "The suspect was heading toward" | | 19 | "Quinn’s pulse hammered in her" |
| | ratio | 0.908 | |
| 38.46% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 130 | | matches | | | ratio | 0.008 | |
| 52.15% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 63 | | technicalSentenceCount | 8 | | matches | | 0 | "Detective Harlow Quinn’s boots splashed through puddles as she sprinted past the flickering green neon of *The Raven’s Nest*, her breath coming in sharp, contro…" | | 1 | "The suspect—*Tomás Herrera*, according to the file—had been flagged for off-the-books medical work, the kind that didn’t show up in NHS records." | | 2 | "Or was it the wild, feral look of a man who knew he was being hunted by something far worse than the law?" | | 3 | "A low hum vibrated through the air, a sound that wasn’t quite music but something deeper, something that resonated in her bones." | | 4 | "The air smelled different here—sharp, metallic, with an underlying sweetness that made her stomach clench." | | 5 | "Whispers in the break room, half-drunk confessions from informants who swore they’d seen things that couldn’t be explained." | | 6 | "The figure stepped forward, the shadows peeling away to reveal a face that was all sharp angles and cold, calculating eyes." | | 7 | "Stalls collapsed, their contents spilling across the ground in a cascade of glowing liquids and shattered glass." |
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| 13.89% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 9 | | uselessAdditionCount | 2 | | matches | | 0 | "Quinn barked, her voice cutting through the drumming rain" | | 1 | "he said, his voice tight" |
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| 12.07% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 7 | | fancyCount | 4 | | fancyTags | | 0 | "Quinn barked (bark)" | | 1 | "They snapped (snap)" | | 2 | "he shouted (shout)" | | 3 | "he gasped (gasp)" |
| | dialogueSentences | 29 | | tagDensity | 0.241 | | leniency | 0.483 | | rawRatio | 0.571 | | effectiveRatio | 0.276 | |