| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 13 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 45 | | tagDensity | 0.289 | | leniency | 0.578 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 94.94% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1978 | | totalAiIsmAdverbs | 2 | | found | | | highlights | | |
| 80.00% | AI-ism character names | Target: 0 AI-default names (17 tracked, −20% each) | | codexExemptions | (empty) | | found | | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 57.03% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1978 | | totalAiIsms | 17 | | found | | | highlights | | 0 | "marble" | | 1 | "gleaming" | | 2 | "silk" | | 3 | "tension" | | 4 | "scanning" | | 5 | "pristine" | | 6 | "pumping" | | 7 | "resolve" | | 8 | "traced" | | 9 | "etched" | | 10 | "echoed" | | 11 | "processed" | | 12 | "quivered" | | 13 | "echoes" | | 14 | "chill" | | 15 | "database" |
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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 | 128 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 128 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 160 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 49 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 2 | | markdownWords | 23 | | totalWords | 1995 | | ratio | 0.012 | | matches | | 0 | "You were right about Deptford. Come to the Veil Market tonight and I'll prove it. Bring the compass." | | 1 | "You were right about Deptford." |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 13 | | unquotedAttributions | 0 | | matches | (empty) | |
| 83.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 50 | | wordCount | 1440 | | uniqueNames | 17 | | maxNameDensity | 0.9 | | worstName | "Harlow" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Langley" | | discoveredNames | | Harlow | 13 | | Quinn | 2 | | Persian | 1 | | Langley | 10 | | Windsor | 1 | | Deptford | 3 | | Morris | 3 | | Dr | 2 | | Tube | 1 | | Veil | 2 | | Market | 2 | | Camden | 2 | | Marcus | 1 | | Webb | 1 | | Strand | 1 | | London | 2 | | Box | 3 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Langley" | | 3 | "Deptford" | | 4 | "Morris" | | 5 | "Dr" | | 6 | "Marcus" | | 7 | "Webb" |
| | places | | 0 | "Windsor" | | 1 | "Veil" | | 2 | "Camden" | | 3 | "London" |
| | globalScore | 1 | | windowScore | 0.833 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 97 | | glossingSentenceCount | 1 | | matches | | 0 | "quite resolve into letters" |
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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 | 1995 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 2 | | totalSentences | 160 | | matches | | 0 | "died — that someone" | | 1 | "sent that text " |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 66 | | mean | 30.23 | | std | 21.42 | | cv | 0.709 | | sampleLengths | | 0 | 9 | | 1 | 52 | | 2 | 46 | | 3 | 75 | | 4 | 5 | | 5 | 9 | | 6 | 11 | | 7 | 63 | | 8 | 2 | | 9 | 68 | | 10 | 32 | | 11 | 6 | | 12 | 48 | | 13 | 3 | | 14 | 15 | | 15 | 12 | | 16 | 45 | | 17 | 7 | | 18 | 18 | | 19 | 47 | | 20 | 73 | | 21 | 5 | | 22 | 2 | | 23 | 44 | | 24 | 5 | | 25 | 55 | | 26 | 8 | | 27 | 49 | | 28 | 43 | | 29 | 1 | | 30 | 15 | | 31 | 26 | | 32 | 26 | | 33 | 41 | | 34 | 21 | | 35 | 56 | | 36 | 3 | | 37 | 53 | | 38 | 8 | | 39 | 17 | | 40 | 35 | | 41 | 8 | | 42 | 30 | | 43 | 56 | | 44 | 4 | | 45 | 41 | | 46 | 4 | | 47 | 61 | | 48 | 40 | | 49 | 44 |
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| 91.56% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 5 | | totalSentences | 128 | | matches | | 0 | "was dressed" | | 1 | "were folded" | | 2 | "was scored" | | 3 | "been closed" | | 4 | "was etched" |
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| 0.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 8 | | totalVerbs | 235 | | matches | | 0 | "was looking" | | 1 | "wasn't getting" | | 2 | "wasn't pointing" | | 3 | "was pointing" | | 4 | "was waking" | | 5 | "was watching" | | 6 | "were building" | | 7 | "was being" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 12 | | semicolonCount | 0 | | flaggedSentences | 11 | | totalSentences | 160 | | ratio | 0.069 | | matches | | 0 | "The air hit her first — cold and still, with something cloying underneath." | | 1 | "But this — a decommissioned bank vault beneath the old financial district — this was new." | | 2 | "The man's face was peaceful — too peaceful." | | 3 | "And placed with precision — exactly centered, exactly level." | | 4 | "The fabric of the suit jacket had been cut cleanly — no ragged edges, no sign of a struggle." | | 5 | "The brass was scored with deep scratches — deliberate marks, not random vandalism." | | 6 | "The glass face was etched with designs that echoed the scratches on the wall — protective sigils, she realized, though she couldn't have said how she knew." | | 7 | "London was waking up outside — she could hear traffic, the distant rumble of the Tube, a tourist's laugh cutting through the morning chill." | | 8 | "Harlow Quinn had spent eighteen years building a career on evidence that made sense — fingerprints and fibres, motives and means, the clean arithmetic of cause and effect." | | 9 | "Right about the warehouse, right about the symbols, right about the feeling he'd had in the days before he died — that someone was watching them, that the case they were building wasn't just a case but a door, and that doors, once opened, could not always be closed again." | | 10 | "And she would have some very pointed questions for whoever had sent that text — starting with how they'd gotten her number, and ending with what they knew about a compass that pointed at dead men." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1431 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 49 | | adverbRatio | 0.03424178895877009 | | lyAdverbCount | 7 | | lyAdverbRatio | 0.004891684136967156 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 160 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 160 | | mean | 12.47 | | std | 9.75 | | cv | 0.782 | | sampleLengths | | 0 | 9 | | 1 | 28 | | 2 | 13 | | 3 | 11 | | 4 | 7 | | 5 | 5 | | 6 | 5 | | 7 | 13 | | 8 | 16 | | 9 | 28 | | 10 | 18 | | 11 | 29 | | 12 | 5 | | 13 | 9 | | 14 | 6 | | 15 | 5 | | 16 | 15 | | 17 | 19 | | 18 | 18 | | 19 | 11 | | 20 | 2 | | 21 | 5 | | 22 | 13 | | 23 | 14 | | 24 | 8 | | 25 | 7 | | 26 | 21 | | 27 | 5 | | 28 | 8 | | 29 | 7 | | 30 | 8 | | 31 | 4 | | 32 | 6 | | 33 | 18 | | 34 | 30 | | 35 | 3 | | 36 | 15 | | 37 | 9 | | 38 | 3 | | 39 | 45 | | 40 | 7 | | 41 | 2 | | 42 | 16 | | 43 | 3 | | 44 | 6 | | 45 | 11 | | 46 | 13 | | 47 | 9 | | 48 | 5 | | 49 | 14 |
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| 63.54% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 10 | | diversityRatio | 0.41875 | | totalSentences | 160 | | uniqueOpeners | 67 | |
| 84.75% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 118 | | matches | | 0 | "Once, a meatpacking plant where" | | 1 | "Almost as though the man" | | 2 | "Then she deleted the message" |
| | ratio | 0.025 | |
| 87.80% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 39 | | totalSentences | 118 | | matches | | 0 | "She'd worked cases in strange" | | 1 | "She didn't turn at the" | | 2 | "He was a man built" | | 3 | "His face carried the particular" | | 4 | "They approached the desk together." | | 5 | "He was dressed in a" | | 6 | "His hands were folded over" | | 7 | "His fingernails were clean." | | 8 | "She was looking at the" | | 9 | "She reached into her own" | | 10 | "She leaned closer to the" | | 11 | "She pointed at the wound." | | 12 | "She frowned, crouching down to" | | 13 | "She was forty-one years old," | | 14 | "She walked to the nearest" | | 15 | "She made a mental note" | | 16 | "She crossed the vault, her" | | 17 | "She recognized them." | | 18 | "She didn't answer." | | 19 | "Her attention had shifted to" |
| | ratio | 0.331 | |
| 70.17% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 92 | | totalSentences | 118 | | matches | | 0 | "The vault door stood open" | | 1 | "Detective Harlow Quinn ducked under" | | 2 | "The air hit her first" | | 3 | "She'd worked cases in strange" | | 4 | "Warehouses converted to fighting pits." | | 5 | "Rooftop gardens hiding shallow graves." | | 6 | "The vault itself was circular," | | 7 | "The boxes stretched from floor" | | 8 | "She didn't turn at the" | | 9 | "He was a man built" | | 10 | "His face carried the particular" | | 11 | "They approached the desk together." | | 12 | "The dead man lay on" | | 13 | "He was dressed in a" | | 14 | "Italian leather shoes without a" | | 15 | "A silk tie in a" | | 16 | "His hands were folded over" | | 17 | "Harlow circled the body slowly." | | 18 | "The man's face was peaceful" | | 19 | "His fingernails were clean." |
| | ratio | 0.78 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 118 | | matches | (empty) | | ratio | 0 | |
| 19.23% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 52 | | technicalSentenceCount | 9 | | matches | | 0 | "Detective Harlow Quinn ducked under the crime scene tape and stepped through, her heels clicking once on the marble threshold before falling silent on the Persi…" | | 1 | "At the vault's center sat a massive oak desk, incongruous in its domesticity, as though someone had dragged a banker's office into this subterranean chamber and…" | | 2 | "His face carried the particular weariness of someone who'd been standing in a cold room for three hours." | | 3 | "London was waking up outside — she could hear traffic, the distant rumble of the Tube, a tourist's laugh cutting through the morning chill." | | 4 | "Harlow Quinn had spent eighteen years building a career on evidence that made sense — fingerprints and fibres, motives and means, the clean arithmetic of cause …" | | 5 | "But the dead man in the vault had clean fingernails and a wound that shouldn't have been fatal." | | 6 | "And somewhere in the dark beneath Camden, a market was moving with the moon, selling things that didn't exist in any police database." | | 7 | "And she would have some very pointed questions for whoever had sent that text — starting with how they'd gotten her number, and ending with what they knew about…" | | 8 | "The cab turned onto the Strand, and London closed around her like a fist around a secret: tight, unyielding, full of things that did not want to be found." |
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| 86.54% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 13 | | uselessAdditionCount | 1 | | matches | | 0 | "Harlow traced, her gloved finger hovering just above the metal" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 5 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 45 | | tagDensity | 0.111 | | leniency | 0.222 | | rawRatio | 0.2 | | effectiveRatio | 0.044 | |