| 0.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 2 | | adverbTagCount | 1 | | adverbTags | | 0 | "she said aloud [aloud]" |
| | dialogueSentences | 3 | | tagDensity | 0.667 | | leniency | 1 | | rawRatio | 0.5 | | effectiveRatio | 0.5 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1141 | | 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) | |
| 60.56% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1141 | | totalAiIsms | 9 | | found | | | highlights | | 0 | "pulse" | | 1 | "electric" | | 2 | "flicker" | | 3 | "structure" | | 4 | "weight" | | 5 | "footsteps" | | 6 | "lurch" |
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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 | 58 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 58 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 59 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 71 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1130 | | ratio | 0 | | matches | (empty) | |
| 97.22% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 9 | | unquotedAttributions | 1 | | matches | | 0 | "The chain rattled shut behind her on its own, or the wind moved it, she told herself, the wind, nothing more, and she we…" |
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| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 24 | | wordCount | 1120 | | uniqueNames | 12 | | maxNameDensity | 0.63 | | worstName | "Herrera" | | maxWindowNameDensity | 1 | | worstWindowName | "Quinn" | | discoveredNames | | Detective | 1 | | Harlow | 1 | | Quinn | 5 | | Herrera | 7 | | Brewer | 1 | | Street | 1 | | St | 1 | | London | 1 | | Morris | 3 | | Victorian | 1 | | God | 1 | | Underground | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Herrera" | | 3 | "Morris" | | 4 | "God" |
| | places | | 0 | "Brewer" | | 1 | "Street" | | 2 | "St" | | 3 | "London" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 42 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1130 | | matches | (empty) | |
| 0.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 3 | | totalSentences | 59 | | matches | | 0 | "being that dark" | | 1 | "was that light" | | 2 | "suspect that a" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 24 | | mean | 47.08 | | std | 31.42 | | cv | 0.667 | | sampleLengths | | 0 | 69 | | 1 | 48 | | 2 | 4 | | 3 | 73 | | 4 | 49 | | 5 | 64 | | 6 | 12 | | 7 | 84 | | 8 | 70 | | 9 | 78 | | 10 | 13 | | 11 | 5 | | 12 | 82 | | 13 | 85 | | 14 | 31 | | 15 | 44 | | 16 | 51 | | 17 | 21 | | 18 | 5 | | 19 | 67 | | 20 | 116 | | 21 | 39 | | 22 | 6 | | 23 | 14 |
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| 93.16% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 58 | | matches | | 0 | "was gone" | | 1 | "been opened" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 177 | | matches | | 0 | "wasn't faltering" | | 1 | "was tilting" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 13 | | semicolonCount | 0 | | flaggedSentences | 10 | | totalSentences | 59 | | ratio | 0.169 | | matches | | 0 | "She'd clocked him at the scene on Brewer Street twenty minutes ago, kneeling over a body that had no pulse and shouldn't have had a pulse—not with what she'd seen done to it—and then he'd looked up, met her eyes across the crime tape, and run." | | 1 | "Eighteen years on the force had taught Quinn to read a chase the way other people read a book—the tells, the tempo, the moment a suspect's confidence would falter." | | 2 | "She caught a glimpse of his face as he cut under a streetlamp—young, olive-skinned, a St." | | 3 | "Beyond it, darkness—and a smell, cold and mineral, like a cellar that had never once seen sun." | | 4 | "TUBE STATION – CLOSED, read a sign bolted to the brick, the paint peeling in long white curls." | | 5 | "Not wrong like a bad address or a dead end—wrong like the air itself had a texture to it, faintly electric, the kind of wrong she'd felt exactly twice before in her life: once in the alley where they'd found Morris's body, and once, months later, in an empty warehouse where she was quite sure something had been watching her from a dark that had no business being that dark." | | 6 | "Stairs, she could see, old tiled stairs curving downward, Victorian ironwork peeling with rust, and somewhere below—was that light?" | | 7 | "Then she thought of Herrera's face in the streetlight, the flat certainty of a man running toward something rather than away from it, and she thought—God help her—that if she turned back now she would never know." | | 8 | "The murmur of voices grew as she descended, layered now with something else—a low chime, like coins dropped on stone, a smell of woodsmoke and something bitter and herbal she couldn't place, ash and rosemary and old blood." | | 9 | "Ahead, past a final turn in the tunnel, gold light bloomed against old brick, and a voice—not Herrera's, older, dry as paper—said, quite clearly, close enough that it might have been at her shoulder though she saw no one:" |
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| 89.61% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1133 | | adjectiveStacks | 1 | | stackExamples | | 0 | "deeper black beyond it." |
| | adverbCount | 51 | | adverbRatio | 0.04501323918799647 | | lyAdverbCount | 8 | | lyAdverbRatio | 0.00706090026478376 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 59 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 59 | | mean | 19.15 | | std | 16.42 | | cv | 0.857 | | sampleLengths | | 0 | 33 | | 1 | 36 | | 2 | 2 | | 3 | 46 | | 4 | 4 | | 5 | 20 | | 6 | 3 | | 7 | 5 | | 8 | 45 | | 9 | 29 | | 10 | 3 | | 11 | 17 | | 12 | 16 | | 13 | 17 | | 14 | 31 | | 15 | 6 | | 16 | 3 | | 17 | 3 | | 18 | 35 | | 19 | 33 | | 20 | 11 | | 21 | 5 | | 22 | 40 | | 23 | 30 | | 24 | 6 | | 25 | 29 | | 26 | 17 | | 27 | 18 | | 28 | 1 | | 29 | 7 | | 30 | 13 | | 31 | 5 | | 32 | 12 | | 33 | 70 | | 34 | 4 | | 35 | 20 | | 36 | 19 | | 37 | 22 | | 38 | 7 | | 39 | 13 | | 40 | 5 | | 41 | 22 | | 42 | 1 | | 43 | 3 | | 44 | 4 | | 45 | 18 | | 46 | 22 | | 47 | 37 | | 48 | 7 | | 49 | 7 |
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| 81.92% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 5 | | diversityRatio | 0.5423728813559322 | | totalSentences | 59 | | uniqueOpeners | 32 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 5 | | totalSentences | 55 | | matches | | 0 | "Then he was gone again," | | 1 | "Too many voices for an" | | 2 | "Too many for a place" | | 3 | "Of course nothing." | | 4 | "Then she thought of Herrera's" |
| | ratio | 0.091 | |
| 60.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 22 | | totalSentences | 55 | | matches | | 0 | "She'd clocked him at the" | | 1 | "Her voice cracked against the" | | 2 | "He didn't stop." | | 3 | "He never even looked back." | | 4 | "She followed him left, past" | | 5 | "He moved like a man" | | 6 | "She caught a glimpse of" | | 7 | "Her radio crackled at her" | | 8 | "She ignored it." | | 9 | "She'd learned, since then, to" | | 10 | "It was tilting wrong now." | | 11 | "Her boot skidded on the" | | 12 | "She hadn't realized they'd come" | | 13 | "She drew her torch." | | 14 | "Her phone had no signal." | | 15 | "She checked, out of habit," | | 16 | "She thought of protocol." | | 17 | "She thought of the eleven" | | 18 | "She had spent three years" | | 19 | "She was so tired of" |
| | ratio | 0.4 | |
| 87.27% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 41 | | totalSentences | 55 | | matches | | 0 | "Rain came down in sheets" | | 1 | "She'd clocked him at the" | | 2 | "Innocent men didn't run." | | 3 | "Her voice cracked against the" | | 4 | "He didn't stop." | | 5 | "He never even looked back." | | 6 | "She followed him left, past" | | 7 | "Herrera wasn't faltering." | | 8 | "He moved like a man" | | 9 | "She caught a glimpse of" | | 10 | "Christopher medallion swinging loose from" | | 11 | "Her radio crackled at her" | | 12 | "She ignored it." | | 13 | "This was hers." | | 14 | "She'd learned, since then, to" | | 15 | "It was tilting wrong now." | | 16 | "Herrera ducked down a set" | | 17 | "Her boot skidded on the" | | 18 | "The steps ended at a" | | 19 | "TUBE STATION – CLOSED, read" |
| | ratio | 0.745 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 55 | | matches | (empty) | | ratio | 0 | |
| 0.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 34 | | technicalSentenceCount | 9 | | matches | | 0 | "Rain came down in sheets that turned the sodium streetlights into smears of orange, and Detective Harlow Quinn ran through it with her lungs burning and her coa…" | | 1 | "Ahead of her, thirty feet and losing ground, a man in a dark jacket vaulted a low wall with the fluid economy of someone who'd done it before, who'd trained his…" | | 2 | "She'd clocked him at the scene on Brewer Street twenty minutes ago, kneeling over a body that had no pulse and shouldn't have had a pulse—not with what she'd se…" | | 3 | "She followed him left, past a shuttered kebab shop, its metal grille rattling in the wind, past a doorway where a rough sleeper had wedged himself against the c…" | | 4 | "Christopher medallion swinging loose from his collar, catching the light in one bright, useless flash of silver." | | 5 | "Rusted iron, half-collapsed, wound with a chain that looked ancient but had clearly been opened and closed a thousand times, the links worn smooth and bright at…" | | 6 | "Not wrong like a bad address or a dead end—wrong like the air itself had a texture to it, faintly electric, the kind of wrong she'd felt exactly twice before in…" | | 7 | "The chain rattled shut behind her on its own, or the wind moved it, she told herself, the wind, nothing more, and she went down the stairs with her torch low an…" | | 8 | "The tiles underfoot were old Underground green, cracked, furred with a moss that shouldn't grow in a place with no light." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 2 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 1 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 3 | | tagDensity | 0.333 | | leniency | 0.667 | | rawRatio | 0 | | effectiveRatio | 0 | |