| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | |
| 94.32% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1760 | | totalAiIsmAdverbs | 2 | | found | | 0 | | | 1 | | adverb | "deliberately" | | count | 1 |
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| | 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) | |
| 60.23% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1760 | | totalAiIsms | 14 | | found | | | highlights | | 0 | "familiar" | | 1 | "scanning" | | 2 | "weight" | | 3 | "pulse" | | 4 | "stomach" | | 5 | "footsteps" | | 6 | "echoing" | | 7 | "echoed" | | 8 | "intensity" | | 9 | "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 | 130 | | matches | (empty) | |
| 98.90% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 3 | | narrationSentences | 130 | | filterMatches | | | hedgeMatches | | 0 | "appeared to" | | 1 | "seemed to" |
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| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 130 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 45 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1779 | | ratio | 0 | | matches | (empty) | |
| 75.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 5 | | unquotedAttributions | 1 | | matches | | 0 | "Paramedic training, she guessed." |
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| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 59 | | wordCount | 1779 | | uniqueNames | 23 | | maxNameDensity | 0.84 | | worstName | "Quinn" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Quinn" | | discoveredNames | | Soho | 2 | | Quinn | 15 | | Raven | 2 | | Nest | 2 | | Herrera | 11 | | Saint | 3 | | Christopher | 3 | | Vauxhall | 1 | | Greek | 1 | | Street | 1 | | Morris | 3 | | Shaftesbury | 1 | | Avenue | 1 | | Tottenham | 1 | | Court | 1 | | Road | 1 | | Camden | 2 | | Lock | 1 | | Tube | 1 | | Met | 1 | | Veil | 1 | | Market | 1 | | One | 3 |
| | persons | | 0 | "Quinn" | | 1 | "Raven" | | 2 | "Nest" | | 3 | "Herrera" | | 4 | "Saint" | | 5 | "Christopher" | | 6 | "Morris" | | 7 | "Lock" | | 8 | "Met" |
| | places | | 0 | "Soho" | | 1 | "Vauxhall" | | 2 | "Greek" | | 3 | "Street" | | 4 | "Shaftesbury" | | 5 | "Avenue" | | 6 | "Tottenham" | | 7 | "Court" | | 8 | "Road" | | 9 | "Camden" | | 10 | "Market" | | 11 | "One" |
| | globalScore | 1 | | windowScore | 1 | |
| 41.30% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 92 | | glossingSentenceCount | 4 | | matches | | 0 | "looked like an abandoned Tube station" | | 1 | "looked like it belonged in a museum, or a" | | 2 | "violet that seemed to move on its own, a silver that glinted like mercury, a green so dark it was almost black" | | 3 | "looked like herbs and looked like somethi" | | 4 | "looked like something else entirely" |
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| 87.58% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 2 | | per1kWords | 1.124 | | wordCount | 1779 | | matches | | 0 | "not knives, not guns, but things with edges" | | 1 | "not guns, but things with edges" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 130 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 38 | | mean | 46.82 | | std | 36.39 | | cv | 0.777 | | sampleLengths | | 0 | 7 | | 1 | 70 | | 2 | 21 | | 3 | 10 | | 4 | 101 | | 5 | 68 | | 6 | 29 | | 7 | 6 | | 8 | 77 | | 9 | 105 | | 10 | 16 | | 11 | 9 | | 12 | 46 | | 13 | 76 | | 14 | 60 | | 15 | 72 | | 16 | 100 | | 17 | 44 | | 18 | 109 | | 19 | 12 | | 20 | 86 | | 21 | 6 | | 22 | 3 | | 23 | 108 | | 24 | 14 | | 25 | 5 | | 26 | 79 | | 27 | 111 | | 28 | 62 | | 29 | 40 | | 30 | 15 | | 31 | 1 | | 32 | 70 | | 33 | 25 | | 34 | 9 | | 35 | 49 | | 36 | 54 | | 37 | 4 |
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| 99.87% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 130 | | matches | | 0 | "being hunted" | | 1 | "was gone" |
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| 63.95% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 6 | | totalVerbs | 294 | | matches | | 0 | "was lengthening" | | 1 | "was going" | | 2 | "was leading" | | 3 | "wasn't heading" | | 4 | "was weighing" | | 5 | "was standing" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 19 | | semicolonCount | 0 | | flaggedSentences | 15 | | totalSentences | 130 | | ratio | 0.115 | | matches | | 0 | "The bar's door had swung open twice in the last hour — once for a couple too drunk to notice her, once for a man in a trench coat who walked like he owed someone money." | | 1 | "He was shorter than she'd expected — five ten, maybe — but he moved with the quick, compact energy of someone used to thinking on his feet." | | 2 | "He moved fast but not suspiciously fast — the pace of a man with somewhere to be, not somewhere to hide." | | 3 | "She could see the faint ridge of the scar along his forearm from here — the knife wound that had landed him in A&E three years ago, which was how she'd first found his name threaded through the clique's messy web." | | 4 | "Herrera had a half-block lead and was lengthening it, his stride opening up like a man who'd been waiting for this moment — who'd walked out of The Raven's Nest knowing she'd be there, knowing the rain would cover his exit, leading her somewhere specific." | | 5 | "She knew the area — every detective in the borough knew the area." | | 6 | "Somewhere below, she could hear footsteps — Herrera's footsteps — echoing off tile, growing fainter." | | 7 | "Morris had been the same — gone in an instant, into a dark she couldn't follow, and the case file had sat on her desk for three years like a stone she couldn't set down." | | 8 | "She thought about the bone token they'd found on the last suspect she'd caught — a small, carved thing that looked like it belonged in a museum, or a pyre." | | 9 | "The sound of the city above faded — the traffic, the rain, the distant pulse of a bass line from some club — replaced by a damp, close quiet that smelled of old tile and standing water." | | 10 | "Emergency lighting — old bulbs with a reddish tint she didn't recognize — gave the passage a bruised, feverish quality." | | 11 | "The air was thick with incense and something else — something metallic, something that tasted the way a battery smells on the tongue." | | 12 | "Glass bottles lined the nearest stall, filled with liquids in colors that didn't correspond to anything in Quinn's experience — a deep violet that seemed to move on its own, a silver that glinted like mercury, a green so dark it was almost black." | | 13 | "Farther back, a stall sold weapons — not knives, not guns, but things with edges and curves that seemed to shift when Quinn looked at them directly." | | 14 | "And Quinn made her choice the way she'd made every choice since the night she lost Morris — by refusing to make the safe one." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1763 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 59 | | adverbRatio | 0.033465683494044246 | | lyAdverbCount | 11 | | lyAdverbRatio | 0.006239364719228588 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 130 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 130 | | mean | 13.68 | | std | 11.32 | | cv | 0.827 | | sampleLengths | | 0 | 7 | | 1 | 26 | | 2 | 36 | | 3 | 8 | | 4 | 4 | | 5 | 12 | | 6 | 2 | | 7 | 3 | | 8 | 10 | | 9 | 15 | | 10 | 27 | | 11 | 4 | | 12 | 13 | | 13 | 42 | | 14 | 3 | | 15 | 2 | | 16 | 19 | | 17 | 4 | | 18 | 2 | | 19 | 8 | | 20 | 30 | | 21 | 5 | | 22 | 3 | | 23 | 8 | | 24 | 13 | | 25 | 6 | | 26 | 21 | | 27 | 13 | | 28 | 29 | | 29 | 9 | | 30 | 1 | | 31 | 4 | | 32 | 23 | | 33 | 20 | | 34 | 8 | | 35 | 41 | | 36 | 2 | | 37 | 2 | | 38 | 9 | | 39 | 11 | | 40 | 5 | | 41 | 9 | | 42 | 9 | | 43 | 6 | | 44 | 3 | | 45 | 20 | | 46 | 3 | | 47 | 5 | | 48 | 3 | | 49 | 16 |
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| 47.95% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 16 | | diversityRatio | 0.36153846153846153 | | totalSentences | 130 | | uniqueOpeners | 47 | |
| 56.02% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 119 | | matches | | 0 | "Somewhere below, she could hear" | | 1 | "Somewhere ahead, past the stall" |
| | ratio | 0.017 | |
| 88.91% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 39 | | totalSentences | 119 | | matches | | 0 | "She checked her watch." | | 1 | "He was shorter than she'd" | | 2 | "You don't haul bodies for" | | 3 | "She'd watched a suspect walk" | | 4 | "He tugged his jacket collar" | | 5 | "He moved fast but not" | | 6 | "She kept thirty yards between" | | 7 | "She needed the noise." | | 8 | "His left arm swung freely" | | 9 | "She could see the faint" | | 10 | "She shut that thought down" | | 11 | "He didn't flinch." | | 12 | "He cut through the gap" | | 13 | "He'd made her." | | 14 | "She was sure of it." | | 15 | "She bolted across the avenue," | | 16 | "She ignored him." | | 17 | "They pushed north through the" | | 18 | "He didn't look back." | | 19 | "He was leading her, all" |
| | ratio | 0.328 | |
| 69.24% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 93 | | totalSentences | 119 | | matches | | 0 | "The rain hit Soho like" | | 1 | "Harlow Quinn pressed her shoulder" | | 2 | "The bar's door had swung" | | 3 | "Neither of them was the" | | 4 | "She checked her watch." | | 5 | "The worn leather band pulled" | | 6 | "Herrera was late." | | 7 | "The door opened a third" | | 8 | "Tomás Herrera stepped out under" | | 9 | "He was shorter than she'd" | | 10 | "You don't haul bodies for" | | 11 | "The Saint Christopher medallion around" | | 12 | "Quinn didn't move." | | 13 | "A shift of weight." | | 14 | "The wet scrape of a" | | 15 | "She'd watched a suspect walk" | | 16 | "Herrera's gaze swept past her." | | 17 | "He tugged his jacket collar" | | 18 | "Quinn counted to five, then" | | 19 | "He moved fast but not" |
| | ratio | 0.782 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 119 | | matches | (empty) | | ratio | 0 | |
| 18.14% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 63 | | technicalSentenceCount | 11 | | matches | | 0 | "She bolted across the avenue, her shoes slapping the wet asphalt, the rain needling her face." | | 1 | "Herrera had a half-block lead and was lengthening it, his stride opening up like a man who'd been waiting for this moment — who'd walked out of The Raven's Nest…" | | 2 | "But she'd seen one before, hanging from a chain around the neck of a woman outside a Camden flat two months ago, and that woman had looked at Quinn with the kin…" | | 3 | "It occupied the full width of the abandoned station platform and stretched back into the dark beyond the reach of the hanging lanterns that swung gently on thei…" | | 4 | "The air was thick with incense and something else — something metallic, something that tasted the way a battery smells on the tongue." | | 5 | "Glass bottles lined the nearest stall, filled with liquids in colors that didn't correspond to anything in Quinn's experience — a deep violet that seemed to mov…" | | 6 | "Beside them, jars of powders and dried substances that looked like herbs and looked like something else entirely." | | 7 | "A woman with no eyebrows was weighing out a handful of what might have been seeds on a brass scale, her lips moving in a soundless count." | | 8 | "The man behind the table had eyes the color of molten copper, and when her gaze passed over him, he looked away with the studied disinterest of someone who didn…" | | 9 | "A dozen figures, maybe fifteen, browsing the stalls with the quiet intensity of people shopping for things that mattered." | | 10 | "She was standing in a place she didn't understand, surrounded by people who might be human and might not, looking for a man who had led her here deliberately." |
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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 | |