| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 1 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 0 | | tagDensity | 1 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 83.30% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 898 | | 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) | |
| 66.59% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 898 | | totalAiIsms | 6 | | found | | | highlights | | 0 | "familiar" | | 1 | "footsteps" | | 2 | "echoing" | | 3 | "flickered" | | 4 | "constructed" | | 5 | "scanned" |
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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 | 61 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 61 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 61 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 50 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 883 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 4 | | unquotedAttributions | 0 | | matches | (empty) | |
| 98.98% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 21 | | wordCount | 882 | | uniqueNames | 12 | | maxNameDensity | 1.02 | | worstName | "Quinn" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Quinn" | | discoveredNames | | Soho | 1 | | Harlow | 1 | | Quinn | 9 | | Thursday-night | 1 | | Raven | 1 | | Nest | 1 | | Morris | 2 | | Tube | 1 | | Stalls | 1 | | Veil | 1 | | Market | 1 | | Met | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Raven" | | 3 | "Nest" | | 4 | "Morris" | | 5 | "Stalls" |
| | places | | | globalScore | 0.99 | | windowScore | 1 | |
| 0.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 39 | | glossingSentenceCount | 6 | | matches | | 0 | "smelled like dead fish" | | 1 | "not quite leaving a gap wide enough to squeeze through" | | 2 | "looked like people" | | 3 | "books that seemed to breathe, turning their own pages in some draft she couldn’t feel" | | 4 | "looked like a stack of bills, though the" | | 5 | "felt like stepping off a cliff" |
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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 | 883 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 61 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 25 | | mean | 35.32 | | std | 24.31 | | cv | 0.688 | | sampleLengths | | 0 | 32 | | 1 | 79 | | 2 | 56 | | 3 | 3 | | 4 | 44 | | 5 | 45 | | 6 | 44 | | 7 | 9 | | 8 | 73 | | 9 | 5 | | 10 | 38 | | 11 | 44 | | 12 | 4 | | 13 | 7 | | 14 | 93 | | 15 | 32 | | 16 | 22 | | 17 | 40 | | 18 | 38 | | 19 | 39 | | 20 | 8 | | 21 | 62 | | 22 | 25 | | 23 | 39 | | 24 | 2 |
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| 88.01% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 61 | | matches | | 0 | "was rusted" | | 1 | "was filled" | | 2 | "was gone" | | 3 | "was left" |
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| 0.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 6 | | totalVerbs | 164 | | matches | | 0 | "was running" | | 1 | "was still falling" | | 2 | "was holding" | | 3 | "was speaking" | | 4 | "was really buying" | | 5 | "was working" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 15 | | semicolonCount | 0 | | flaggedSentences | 11 | | totalSentences | 61 | | ratio | 0.18 | | matches | | 0 | "Not sprinting—she was forty-one, and her knees had opinions—but running with purpose, with that old familiar burn in her calves that meant she was still in this." | | 1 | "Not into an alley—into nothing." | | 2 | "The rain masked sounds, but she caught it—footsteps, rapid, echoing downward, into some kind of tunnel or underground access." | | 3 | "The corridor led to an old service tunnel, then to a gate that was rusted shut—except it wasn’t, not quite, leaving a gap wide enough to squeeze through." | | 4 | "The air was thick with damp and something else—something chemical, sweet and sharp, like incense burning over a chemical fire." | | 5 | "Others moved with wrong proportions—too tall, too many joints, eyes that reflected the scattered lantern light like cats’." | | 6 | "She’d heard whispers for years—every detective in the Met heard them, filed them away with the other urban legends—but she’d never believed, not really, not until now." | | 7 | "Then she saw him—fifty yards away, negotiating with a vendor who had no face, just a smooth oval of skin where features should be." | | 8 | "The suspect—she still didn’t have a name—was speaking in a low voice, trading what looked like a stack of bills, though the paper was black and the denominations made no sense." | | 9 | "She could retreat, call in the kind of forces that might actually understand this place—if any existed, if they wouldn’t just cover it up like they covered up Morris." | | 10 | "Or she could stay, follow him, learn what he was really buying, who he was working with, and maybe—maybe—get some answers about the world that had taken her partner." |
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| 99.35% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 540 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 22 | | adverbRatio | 0.040740740740740744 | | lyAdverbCount | 2 | | lyAdverbRatio | 0.003703703703703704 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 61 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 61 | | mean | 14.48 | | std | 11.78 | | cv | 0.814 | | sampleLengths | | 0 | 15 | | 1 | 17 | | 2 | 27 | | 3 | 24 | | 4 | 3 | | 5 | 1 | | 6 | 24 | | 7 | 31 | | 8 | 4 | | 9 | 21 | | 10 | 3 | | 11 | 5 | | 12 | 39 | | 13 | 22 | | 14 | 2 | | 15 | 2 | | 16 | 19 | | 17 | 4 | | 18 | 19 | | 19 | 21 | | 20 | 5 | | 21 | 2 | | 22 | 2 | | 23 | 7 | | 24 | 5 | | 25 | 11 | | 26 | 50 | | 27 | 5 | | 28 | 28 | | 29 | 10 | | 30 | 1 | | 31 | 4 | | 32 | 14 | | 33 | 20 | | 34 | 5 | | 35 | 4 | | 36 | 7 | | 37 | 16 | | 38 | 6 | | 39 | 8 | | 40 | 18 | | 41 | 45 | | 42 | 5 | | 43 | 27 | | 44 | 9 | | 45 | 13 | | 46 | 24 | | 47 | 16 | | 48 | 20 | | 49 | 18 |
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| 59.02% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 4 | | diversityRatio | 0.39344262295081966 | | totalSentences | 61 | | uniqueOpeners | 24 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 54 | | matches | | 0 | "Then he turned." | | 1 | "Then she saw him—fifty yards" | | 2 | "Then he was gone, melting" |
| | ratio | 0.056 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 14 | | totalSentences | 54 | | matches | | 0 | "He was fast." | | 1 | "She knew this ground." | | 2 | "She’d walked these beats for" | | 3 | "She approached the stairwell." | | 4 | "She glanced back up at" | | 5 | "She could call for backup," | | 6 | "She’d done that for eighteen" | | 7 | "She’d heard whispers for years—every" | | 8 | "Her suspect was here, she" | | 9 | "She scanned the crowd, keeping" | | 10 | "She was close now, close" | | 11 | "She had a choice." | | 12 | "She could retreat, call in" | | 13 | "His hood fell back slightly," |
| | ratio | 0.259 | |
| 80.37% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 41 | | totalSentences | 54 | | matches | | 0 | "The rain came down in" | | 1 | "Detective Harlow Quinn had her" | | 2 | "The suspect was thirty yards" | | 3 | "He was fast." | | 4 | "Quinn kept her head up," | | 5 | "She knew this ground." | | 6 | "She’d walked these beats for" | | 7 | "One second he was there," | | 8 | "Quinn skidded to a stop," | | 9 | "The rain masked sounds, but" | | 10 | "She approached the stairwell." | | 11 | "The concrete steps were slick" | | 12 | "Quinn pulled out her phone." | | 13 | "She glanced back up at" | | 14 | "The rain was still falling." | | 15 | "She could call for backup," | | 16 | "She’d done that for eighteen" | | 17 | "Quinn started down the stairs." | | 18 | "The corridor led to an" | | 19 | "The platform was there, crumbling," |
| | ratio | 0.759 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 54 | | matches | (empty) | | ratio | 0 | |
| 0.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 32 | | technicalSentenceCount | 9 | | matches | | 0 | "Not sprinting—she was forty-one, and her knees had opinions—but running with purpose, with that old familiar burn in her calves that meant she was still in this…" | | 1 | "She’d walked these beats for eighteen years, and she knew every alley that dead-ended, every courtyard that emptied back into traffic." | | 2 | "One second he was there, a blur of black against the wet brick, and the next he’d vanished down a stairwell she hadn’t seen, hidden behind a stack of rotting pa…" | | 3 | "The concrete steps were slick with moss and grease, descending into darkness that smelled of rust and old electricity." | | 4 | "The corridor led to an old service tunnel, then to a gate that was rusted shut—except it wasn’t, not quite, leaving a gap wide enough to squeeze through." | | 5 | "The platform was there, crumbling, with tracks that led into blackness in both directions." | | 6 | "Stalls lined the old tracks, constructed from scrap wood and black iron, displaying goods she couldn’t identify: jars of liquid that glowed with internal colors…" | | 7 | "Quinn moved closer, stepping over something that might have been a pool of water or might have been something alive." | | 8 | "Then he was gone, melting into the crowd, and Quinn was left standing alone in the heart of something she didn’t understand, with nothing but her badge, her gun…" |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 1 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |