| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 9 | | adverbTagCount | 1 | | adverbTags | | 0 | "he said quietly [quietly]" |
| | dialogueSentences | 22 | | tagDensity | 0.409 | | leniency | 0.818 | | rawRatio | 0.111 | | effectiveRatio | 0.091 | |
| 90.66% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 2141 | | totalAiIsmAdverbs | 4 | | 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) | |
| 74.31% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 2141 | | totalAiIsms | 11 | | found | | | highlights | | 0 | "eyebrow" | | 1 | "weight" | | 2 | "echo" | | 3 | "velvet" | | 4 | "scanned" | | 5 | "database" | | 6 | "shimmered" | | 7 | "pulse" | | 8 | "flickered" |
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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 | 114 | | matches | (empty) | |
| 55.14% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 3 | | hedgeCount | 4 | | narrationSentences | 114 | | filterMatches | | | hedgeMatches | | 0 | "seemed to" | | 1 | "appeared to" |
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| 97.97% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 126 | | gibberishSentences | 1 | | adjustedGibberishSentences | 1 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 77 | | ratio | 0.008 | | matches | | 0 | "Eighteen years on the force had taught her that the worst things happened on nights like this — when the rain drowned out the sounds that might have warned you, when the streetligh…" |
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| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 2168 | | 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 | 53 | | wordCount | 1844 | | uniqueNames | 25 | | maxNameDensity | 0.98 | | worstName | "Quinn" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Quinn" | | discoveredNames | | London | 2 | | Harlow | 2 | | Quinn | 18 | | Camden | 2 | | Road | 1 | | Mercedes | 3 | | Celina | 1 | | Voss | 1 | | Brockley | 1 | | Marsh | 1 | | Street | 1 | | Glock | 1 | | Metropolitan | 1 | | Police | 1 | | Royal | 1 | | Marines | 1 | | Met | 1 | | Town | 1 | | East | 1 | | End | 1 | | Veil | 2 | | Market | 2 | | Morris | 4 | | Poplar | 1 | | Tomás | 2 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Mercedes" | | 3 | "Celina" | | 4 | "Voss" | | 5 | "Market" | | 6 | "Morris" | | 7 | "Tomás" |
| | places | | 0 | "London" | | 1 | "Camden" | | 2 | "Road" | | 3 | "Brockley" | | 4 | "Marsh" | | 5 | "Street" | | 6 | "Metropolitan" | | 7 | "Royal" | | 8 | "Met" | | 9 | "Town" | | 10 | "East" | | 11 | "End" | | 12 | "Poplar" |
| | globalScore | 1 | | windowScore | 0.833 | |
| 28.05% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 82 | | glossingSentenceCount | 4 | | matches | | 0 | "looked like an abandoned lot — old railwa" | | 1 | "angle that seemed to defy geometry — swung open" | | 2 | "looked like it had been made by something" | | 3 | "quite make out in the low light" |
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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 | 2168 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 126 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 48 | | mean | 45.17 | | std | 35.9 | | cv | 0.795 | | sampleLengths | | 0 | 98 | | 1 | 139 | | 2 | 81 | | 3 | 50 | | 4 | 59 | | 5 | 110 | | 6 | 70 | | 7 | 54 | | 8 | 3 | | 9 | 110 | | 10 | 3 | | 11 | 90 | | 12 | 71 | | 13 | 70 | | 14 | 69 | | 15 | 25 | | 16 | 8 | | 17 | 54 | | 18 | 91 | | 19 | 50 | | 20 | 45 | | 21 | 15 | | 22 | 4 | | 23 | 78 | | 24 | 39 | | 25 | 90 | | 26 | 19 | | 27 | 9 | | 28 | 24 | | 29 | 13 | | 30 | 5 | | 31 | 34 | | 32 | 6 | | 33 | 101 | | 34 | 6 | | 35 | 8 | | 36 | 24 | | 37 | 23 | | 38 | 81 | | 39 | 2 | | 40 | 12 | | 41 | 61 | | 42 | 6 | | 43 | 36 | | 44 | 64 | | 45 | 20 | | 46 | 32 | | 47 | 6 |
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| 96.03% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 114 | | matches | | 0 | "been expanded" | | 1 | "was gone" | | 2 | "been made" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 4 | | totalVerbs | 288 | | matches | | 0 | "was bleeding" | | 1 | "was doing" | | 2 | "was holding" | | 3 | "was screaming" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 29 | | semicolonCount | 0 | | flaggedSentences | 22 | | totalSentences | 126 | | ratio | 0.175 | | matches | | 0 | "Eighteen years on the force had taught her that the worst things happened on nights like this — when the rain drowned out the sounds that might have warned you, when the streetlights turned to smears of gold through a windshield and the city became a place of shadows and wet pavement and the hard, bright syntax of a blue light barrelling through a红灯." | | 1 | "The suspect's car — a black Mercedes, registration logged six hours ago when a woman named Celina Voss had walked into a betting shop in Brockley and left without placing a single bet — had turned north off the main road and into the warren of narrow streets behind the market." | | 2 | "She matched the description from the Marsh Street incident, the one the informant had called \"the Viper\" — though Quinn had learned long ago that the people she pursued didn't use names like that for themselves." | | 3 | "The road ended at a chain-link fence surrounding what looked like an abandoned lot — old railway arches, a rusted gate, the kind of place that appeared on no map and attracted no attention from the council." | | 4 | "Quinn reached for the glove compartment and retrieved her service weapon — a Glock 19, the grip worn smooth by years of her own grip — and checked the magazine by touch, the way she'd done ten thousand times since her first year in the Metropolitan Police." | | 5 | "She moved forward in a low crouch, weapon raised, crossing the wet gravel with steps she'd learned in the Royal Marines before she'd transferred to the Met — weight on the balls of the feet, breath steady, eyes sweeping the dark." | | 6 | "But she'd never believed — not fully — not until three years ago, not until Morris." | | 7 | "The darkness beyond was total, the kind of dark that didn't exist in a city — a dark with weight and texture, the sort that pressed against your eyes." | | 8 | "The beam cut into the dark and found brick — old London stock, crumbling, the walls slick with moisture." | | 9 | "The tunnel opened into a cavern — there was no other word for it." | | 10 | "Stalls lined the perimeter, their canopies draped in dark velvet, their surfaces covered with objects Quinn couldn't immediately identify — glass vials, books with no titles, bone combs, silver mirrors that seemed to fog and clear on their own." | | 11 | "Torches burned with flames that were the wrong color — blue, green, pale violet — and the air smelled of something sharp and herbal, like burning rosemary and copper pennies." | | 12 | "The passage was dark and the woman was fast, but Quinn was faster — she ran track in the academy and she ran now, her shoes slapping against the wet stone, her breath sharp in her chest." | | 13 | "She was holding something — a small white object, oblong, smooth." | | 14 | "Beyond it, she could see only darkness — and the faintest sound of music, something old and stringed and played at a tempo that didn't exist in any modern composition." | | 15 | "She didn't know what laws governed this place, what powers moved through its tunnels, what had killed Morris three years ago in a warehouse in Poplar when she'd heard him scream her name over the radio and arrived to find nothing but a scorch mark on the concrete and his watch — her watch, the worn leather one she'd given him as a joke years ago — lying in a puddle of water that hadn't come from any pipe." | | 16 | "And she had spent three years since then reaching for the same thing — the truth, the explanation, the thing behind the curtain that everyone else had learned to stop looking at." | | 17 | "The green light of the market behind her seemed to pulse, and she became aware — suddenly, viscerally — that she was alone in a chamber with a door that would not open for her, surrounded by things she did not understand, in a place that did not exist on any map, with no way in and no guarantee of a way out." | | 18 | "Then the door to her left — a different door, one she hadn't noticed, set into the wall at an angle that seemed to defy geometry — swung open." | | 19 | "He laughed — a short, dry sound, no humor in it." | | 20 | "Something flickered behind his eyes — surprise, maybe, or the recognition of a bigger problem than the one he'd expected." | | 21 | "Then he reached into his coat and produced a bone token — small, white, smooth, identical to the one the blond woman had pressed to the dark wood." |
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| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1820 | | adjectiveStacks | 1 | | stackExamples | | 0 | "blue, green, pale violet —" |
| | adverbCount | 39 | | adverbRatio | 0.02142857142857143 | | lyAdverbCount | 7 | | lyAdverbRatio | 0.0038461538461538464 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 126 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 126 | | mean | 17.21 | | std | 16.21 | | cv | 0.942 | | sampleLengths | | 0 | 27 | | 1 | 7 | | 2 | 64 | | 3 | 21 | | 4 | 51 | | 5 | 9 | | 6 | 2 | | 7 | 2 | | 8 | 6 | | 9 | 36 | | 10 | 12 | | 11 | 19 | | 12 | 37 | | 13 | 25 | | 14 | 12 | | 15 | 13 | | 16 | 20 | | 17 | 5 | | 18 | 47 | | 19 | 2 | | 20 | 10 | | 21 | 9 | | 22 | 3 | | 23 | 41 | | 24 | 10 | | 25 | 4 | | 26 | 27 | | 27 | 16 | | 28 | 9 | | 29 | 29 | | 30 | 7 | | 31 | 25 | | 32 | 13 | | 33 | 19 | | 34 | 8 | | 35 | 14 | | 36 | 3 | | 37 | 14 | | 38 | 17 | | 39 | 10 | | 40 | 39 | | 41 | 30 | | 42 | 3 | | 43 | 17 | | 44 | 5 | | 45 | 53 | | 46 | 3 | | 47 | 6 | | 48 | 6 | | 49 | 17 |
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| 39.68% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 15 | | diversityRatio | 0.30952380952380953 | | totalSentences | 126 | | uniqueOpeners | 39 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 5 | | totalSentences | 105 | | matches | | 0 | "Somewhere inside, she could hear" | | 1 | "Then the door opened and" | | 2 | "Then the door to her" | | 3 | "Then he reached into his" | | 4 | "Somewhere beyond the dark wood," |
| | ratio | 0.048 | |
| 82.86% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 36 | | totalSentences | 105 | | matches | | 0 | "She was doing ninety down" | | 1 | "She matched the description from" | | 2 | "She pulled up twenty metres" | | 3 | "She slid out of the" | | 4 | "She didn't care." | | 5 | "She moved forward in a" | | 6 | "She'd read the files." | | 7 | "She stopped at the entrance" | | 8 | "She moved forward." | | 9 | "She could see it in" | | 10 | "She'd seen things like this" | | 11 | "She knew how to survive" | | 12 | "She scanned the crowd for" | | 13 | "She was holding something —" | | 14 | "She pressed it to the" | | 15 | "It was something worse." | | 16 | "It was pity." | | 17 | "She didn't know what was" | | 18 | "She didn't know what laws" | | 19 | "She didn't know, and every" |
| | ratio | 0.343 | |
| 45.71% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 87 | | totalSentences | 105 | | matches | | 0 | "The rain had a way" | | 1 | "Detective Harlow Quinn didn't mind" | | 2 | "She was doing ninety down" | | 3 | "The suspect's car — a" | | 4 | "Quinn had seen her face" | | 5 | "A scar through her left" | | 6 | "She matched the description from" | | 7 | "Those were names the world" | | 8 | "The Mercedes took a hard" | | 9 | "The road ended at a" | | 10 | "She pulled up twenty metres" | | 11 | "The rain hammered the roof" | | 12 | "Quinn reached for the glove" | | 13 | "She slid out of the" | | 14 | "The water soaked through her" | | 15 | "She didn't care." | | 16 | "She moved forward in a" | | 17 | "The arches led into the" | | 18 | "She'd read the files." | | 19 | "Everyone who'd worked the East" |
| | ratio | 0.829 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 105 | | matches | (empty) | | ratio | 0 | |
| 0.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 58 | | technicalSentenceCount | 13 | | matches | | 0 | "Eighteen years on the force had taught her that the worst things happened on nights like this — when the rain drowned out the sounds that might have warned you,…" | | 1 | "The road ended at a chain-link fence surrounding what looked like an abandoned lot — old railway arches, a rusted gate, the kind of place that appeared on no ma…" | | 2 | "Everyone who'd worked the East End long enough had heard whispers about it, the Veil Market, the underground bazaar that appeared and disappeared like a fever d…" | | 3 | "The echo was wrong, too vast, as though the tunnel opened into a space far larger than any underground station had a right to be." | | 4 | "Torches burned with flames that were the wrong color — blue, green, pale violet — and the air smelled of something sharp and herbal, like burning rosemary and c…" | | 5 | "The woman was moving fast, heading for a narrow passage between two stalls, her face tight with the look of someone who knew these tunnels, who had used them be…" | | 6 | "Beyond it, she could see only darkness — and the faintest sound of music, something old and stringed and played at a tempo that didn't exist in any modern compo…" | | 7 | "She didn't know what laws governed this place, what powers moved through its tunnels, what had killed Morris three years ago in a warehouse in Poplar when she'd…" | | 8 | "She didn't know, and every instinct she'd honed over eighteen years was screaming at her to turn around, to climb back up to the surface, to file the report and…" | | 9 | "The green light of the market behind her seemed to pulse, and she became aware — suddenly, viscerally — that she was alone in a chamber with a door that would n…" | | 10 | "He was olive-skinned, dark-haired, with warm brown eyes and a scar running along his left forearm that looked like it had been made by something more shaped lik…" | | 11 | "He looked at her with an expression of weary recognition, as though she were a problem he'd been expecting." | | 12 | "Quinn felt them in her chest, in the place where she'd kept Morris's absence for three years, a wound that hadn't healed because she wouldn't let it, because he…" |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 9 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 4 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 22 | | tagDensity | 0.182 | | leniency | 0.364 | | rawRatio | 0 | | effectiveRatio | 0 | |