| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1384 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 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) | |
| 63.87% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1384 | | totalAiIsms | 10 | | found | | | highlights | | 0 | "fractured" | | 1 | "weight" | | 2 | "familiar" | | 3 | "vibrated" | | 4 | "warmth" | | 5 | "resolved" | | 6 | "whisper" | | 7 | "velvet" |
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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 | 115 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 1 | | narrationSentences | 115 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 115 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 38 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1366 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 7 | | unquotedAttributions | 0 | | matches | (empty) | |
| 83.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 34 | | wordCount | 1366 | | uniqueNames | 18 | | maxNameDensity | 0.51 | | worstName | "Quinn" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Morris" | | discoveredNames | | Soho | 1 | | Quinn | 7 | | Old | 1 | | Compton | 1 | | Street | 2 | | Raven | 1 | | Nest | 1 | | Silas | 2 | | London | 3 | | Berwick | 1 | | Pod | 1 | | Tube | 1 | | Morris | 7 | | Camden | 1 | | Arabic | 1 | | Welsh | 1 | | Veil | 1 | | Market | 1 |
| | persons | | 0 | "Quinn" | | 1 | "Raven" | | 2 | "Silas" | | 3 | "Morris" | | 4 | "Market" |
| | places | | 0 | "Soho" | | 1 | "Old" | | 2 | "Compton" | | 3 | "Street" | | 4 | "London" | | 5 | "Berwick" |
| | globalScore | 1 | | windowScore | 0.833 | |
| 76.47% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 68 | | glossingSentenceCount | 2 | | matches | | 0 | "smelled like copper and burnt sage and som" | | 1 | "something that seemed to swallow the faint light from the stairwell behind her" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.732 | | wordCount | 1366 | | matches | | 0 | "Not the ordinary darkness of an unlit basement, but something thicker, something" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 115 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 34 | | mean | 40.18 | | std | 30.64 | | cv | 0.763 | | sampleLengths | | 0 | 64 | | 1 | 16 | | 2 | 65 | | 3 | 9 | | 4 | 61 | | 5 | 85 | | 6 | 14 | | 7 | 33 | | 8 | 93 | | 9 | 39 | | 10 | 2 | | 11 | 66 | | 12 | 4 | | 13 | 95 | | 14 | 42 | | 15 | 43 | | 16 | 19 | | 17 | 5 | | 18 | 96 | | 19 | 48 | | 20 | 42 | | 21 | 15 | | 22 | 5 | | 23 | 83 | | 24 | 6 | | 25 | 91 | | 26 | 41 | | 27 | 49 | | 28 | 51 | | 29 | 4 | | 30 | 49 | | 31 | 4 | | 32 | 21 | | 33 | 6 |
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| 99.16% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 115 | | matches | | 0 | "being dragged" | | 1 | "being greeted" |
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| 0.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 8 | | totalVerbs | 228 | | matches | | 0 | "was tracking" | | 1 | "was descending" | | 2 | "was listening" | | 3 | "were walking" | | 4 | "were walking" | | 5 | "was selling" | | 6 | "was examining" | | 7 | "was already being" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 18 | | semicolonCount | 0 | | flaggedSentences | 11 | | totalSentences | 115 | | ratio | 0.096 | | matches | | 0 | "Three blocks ahead, the suspect—a lean figure in a dark jacket—ducked left around the corner of Old Compton Street." | | 1 | "Quinn turned the corner and caught a glimpse of movement—fabric whipping, a flash of heel—and she pushed harder, her lungs working, the worn leather watch on her left wrist catching the light from a passing taxi." | | 2 | "Could have been something else entirely—something that would explain the way her gut had clenched the moment she spotted it." | | 3 | "She was descending into something—an alley, a service tunnel, she couldn't tell yet—and the air changed." | | 4 | "The beam cut into the dark, revealing worn tile, old advertising posters peeling from the walls—something about Pod shoes, faded to ghostly illegibility—and then a platform." | | 5 | "And there were voices—too many voices, layered over each other in a dozen languages she couldn't parse, punctuated by sounds that didn't belong in any underground space she'd ever investigated." | | 6 | "And whatever this place was—this hidden market humming with illegal activity beneath the streets of Camden—it would keep operating." | | 7 | "The candlelight grew brighter, and with it the sounds—more distinct now, more layered." | | 8 | "The space was crowded—far more crowded than she'd expected—with figures browsing, trading, leaning in to whisper." | | 9 | "On her right, a man in a tailored suit was examining a row of teeth—human teeth, she was almost certain—laid out on black velvet." | | 10 | "The heavyset man looked up—and his eyes swept the cavern, slow and deliberate, and then stopped." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1387 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 32 | | adverbRatio | 0.023071377072819033 | | lyAdverbCount | 6 | | lyAdverbRatio | 0.004325883201153569 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 115 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 115 | | mean | 11.88 | | std | 9.2 | | cv | 0.774 | | sampleLengths | | 0 | 15 | | 1 | 30 | | 2 | 19 | | 3 | 5 | | 4 | 7 | | 5 | 4 | | 6 | 24 | | 7 | 2 | | 8 | 25 | | 9 | 14 | | 10 | 4 | | 11 | 5 | | 12 | 36 | | 13 | 4 | | 14 | 21 | | 15 | 4 | | 16 | 25 | | 17 | 29 | | 18 | 3 | | 19 | 4 | | 20 | 20 | | 21 | 5 | | 22 | 9 | | 23 | 33 | | 24 | 13 | | 25 | 20 | | 26 | 3 | | 27 | 11 | | 28 | 16 | | 29 | 3 | | 30 | 1 | | 31 | 26 | | 32 | 12 | | 33 | 3 | | 34 | 24 | | 35 | 2 | | 36 | 6 | | 37 | 4 | | 38 | 25 | | 39 | 4 | | 40 | 26 | | 41 | 1 | | 42 | 4 | | 43 | 3 | | 44 | 17 | | 45 | 5 | | 46 | 14 | | 47 | 30 | | 48 | 8 | | 49 | 8 |
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| 49.86% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 16 | | diversityRatio | 0.3826086956521739 | | totalSentences | 115 | | uniqueOpeners | 44 | |
| 32.05% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 104 | | matches | | 0 | "More pouches passed under tables." |
| | ratio | 0.01 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 25 | | totalSentences | 104 | | matches | | 0 | "She didn't call it in." | | 1 | "She'd had her eye on" | | 2 | "She'd seen him three hours" | | 3 | "She'd followed him on instinct." | | 4 | "She was descending into something—an" | | 5 | "It got heavier." | | 6 | "It smelled like copper and" | | 7 | "Her breathing was the only" | | 8 | "She pressed her back against" | | 9 | "She thumbed it on." | | 10 | "She knew them." | | 11 | "Her suspect was down there." | | 12 | "She'd seen the door move." | | 13 | "He was down there, and" | | 14 | "She stood in the dark," | | 15 | "She'd been circling it for" | | 16 | "She looked at her watch." | | 17 | "She stepped through the door." | | 18 | "She moved along the platform" | | 19 | "She could hear haggling." |
| | ratio | 0.24 | |
| 80.19% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 79 | | totalSentences | 104 | | matches | | 0 | "The rain came down in" | | 1 | "Harlow Quinn moved through it" | | 2 | "She didn't call it in." | | 3 | "Dispatch would ask questions she" | | 4 | "The green glow of the" | | 5 | "She'd had her eye on" | | 6 | "Everyone who walked through those" | | 7 | "Tonight wasn't about Silas." | | 8 | "Tonight was about the runner." | | 9 | "Quinn turned the corner and" | | 10 | "The driver didn't slow." | | 11 | "Nobody slowed in this part" | | 12 | "The suspect was fast." | | 13 | "She'd seen him three hours" | | 14 | "A small pouch." | | 15 | "She'd followed him on instinct." | | 16 | "Morris had always told her" | | 17 | "The thought scraped against something" | | 18 | "The suspect vaulted a low" | | 19 | "Quinn hit the gate a" |
| | ratio | 0.76 | |
| 96.15% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 104 | | matches | | 0 | "If she went in and" | | 1 | "If she didn't go in," |
| | ratio | 0.019 | |
| 12.99% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 55 | | technicalSentenceCount | 10 | | matches | | 0 | "Harlow Quinn moved through it like a blade, her boots striking wet pavement with the kind of deliberate rhythm that had kept her alive for eighteen years on the…" | | 1 | "Everyone who walked through those doors clammed up the moment they saw her badge." | | 2 | "Younger than her by at least a decade, with that loose-limbed stride of someone who'd spent their life slipping through spaces other people couldn't fit." | | 3 | "She'd seen him three hours ago at a café on Berwick Street, sitting across from a woman with too many rings on her fingers, passing something under the table." | | 4 | "It smelled like copper and burnt sage and something underneath that she couldn't name, something that made the hair on the back of her neck rise." | | 5 | "Not the ordinary darkness of an unlit basement, but something thicker, something that seemed to swallow the faint light from the stairwell behind her." | | 6 | "And there were voices—too many voices, layered over each other in a dozen languages she couldn't parse, punctuated by sounds that didn't belong in any undergrou…" | | 7 | "She'd been circling it for months, picking at the edges of cases that didn't make sense, evidence that dissolved under scrutiny, witnesses who vanished before s…" | | 8 | "A pattern that pointed to something beneath the ordinary criminal underworld of London, something organized and vast and wrong." | | 9 | "She had eighteen years of training holding her upright, and behind that, she had three years of grief that had hardened into something colder and more durable t…" |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 0 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |