| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 7 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 11 | | tagDensity | 0.636 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 95.87% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1211 | | totalAiIsmAdverbs | 1 | | 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) | |
| 62.84% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1211 | | totalAiIsms | 9 | | found | | | highlights | | 0 | "fractured" | | 1 | "throbbed" | | 2 | "pumping" | | 3 | "footsteps" | | 4 | "echoing" | | 5 | "echo" | | 6 | "resolve" |
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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 | 76 | | matches | (empty) | |
| 86.47% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 1 | | narrationSentences | 76 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 80 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 43 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 4 | | markdownWords | 36 | | totalWords | 1205 | | ratio | 0.03 | | matches | | 0 | "misadventure" | | 1 | "In pursuit, suspect fled into a station that isn't supposed to exist, requesting units to a location I can't fully explain." | | 2 | "something" | | 3 | "Harlow, I think I found where they go. There's a market. The Veil—" |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 10 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 34 | | wordCount | 1114 | | uniqueNames | 14 | | maxNameDensity | 0.9 | | worstName | "Quinn" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Quinn" | | discoveredNames | | Camden | 1 | | High | 1 | | Street | 1 | | Harlow | 2 | | Quinn | 10 | | Herrera | 6 | | Raven | 1 | | Nest | 1 | | Tube | 2 | | London | 1 | | Morris | 3 | | Veil | 2 | | Market | 1 | | Tomás | 2 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Herrera" | | 3 | "Raven" | | 4 | "Morris" | | 5 | "Tomás" |
| | places | | 0 | "Camden" | | 1 | "High" | | 2 | "Street" | | 3 | "London" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 57 | | glossingSentenceCount | 1 | | matches | | |
| 0.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 4 | | per1kWords | 3.32 | | wordCount | 1205 | | matches | | 0 | "Not damp and rot, which she'd expected, but something stranger" | | 1 | "neither male nor" | | 2 | "not in a briefing, not in any case file, but in the last voicemail Morris ever left her, his voice tight" | | 3 | "not in any case file, but in the last voicemail Morris ever left her, his voice tight" |
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| 83.33% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 2 | | totalSentences | 80 | | matches | | 0 | "carved that truth" | | 1 | "hate that word" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 30 | | mean | 40.17 | | std | 26.93 | | cv | 0.67 | | sampleLengths | | 0 | 53 | | 1 | 75 | | 2 | 17 | | 3 | 5 | | 4 | 78 | | 5 | 56 | | 6 | 66 | | 7 | 11 | | 8 | 58 | | 9 | 12 | | 10 | 59 | | 11 | 79 | | 12 | 79 | | 13 | 9 | | 14 | 83 | | 15 | 13 | | 16 | 15 | | 17 | 3 | | 18 | 80 | | 19 | 28 | | 20 | 48 | | 21 | 46 | | 22 | 24 | | 23 | 62 | | 24 | 14 | | 25 | 32 | | 26 | 7 | | 27 | 45 | | 28 | 38 | | 29 | 10 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 76 | | matches | | |
| 97.96% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 3 | | totalVerbs | 196 | | matches | | 0 | "was telling" | | 1 | "was ringing" | | 2 | "was disappearing" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 7 | | semicolonCount | 0 | | flaggedSentences | 6 | | totalSentences | 80 | | ratio | 0.075 | | matches | | 0 | "She lunged, fingertips brushing the wet canvas of his duffel—and then he twisted free and dropped through a gap in the hoarding that bordered an old construction site." | | 1 | "Not damp and rot, which she'd expected, but something stranger—incense and copper and a sweetness like burnt sugar." | | 2 | "If she called this in and it turned out to be nothing—or worse, if it turned out to be *something*—she'd hand them everything they needed to take her badge." | | 3 | "Through a gap in the curtain she could see light—warm amber and sickly green, the glow of dozens of stalls, and figures moving between them that her mind refused to fully render." | | 4 | "She had heard it once before—not in a briefing, not in any case file, but in the last voicemail Morris ever left her, his voice tight with something she'd taken for fear." | | 5 | "The Veil—*" |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1123 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 28 | | adverbRatio | 0.024933214603739984 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.004452359750667854 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 80 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 80 | | mean | 15.06 | | std | 10.99 | | cv | 0.729 | | sampleLengths | | 0 | 26 | | 1 | 27 | | 2 | 4 | | 3 | 2 | | 4 | 16 | | 5 | 43 | | 6 | 10 | | 7 | 4 | | 8 | 13 | | 9 | 3 | | 10 | 2 | | 11 | 3 | | 12 | 31 | | 13 | 6 | | 14 | 8 | | 15 | 30 | | 16 | 3 | | 17 | 19 | | 18 | 16 | | 19 | 8 | | 20 | 10 | | 21 | 31 | | 22 | 7 | | 23 | 28 | | 24 | 11 | | 25 | 9 | | 26 | 19 | | 27 | 18 | | 28 | 12 | | 29 | 12 | | 30 | 5 | | 31 | 17 | | 32 | 37 | | 33 | 8 | | 34 | 18 | | 35 | 16 | | 36 | 37 | | 37 | 16 | | 38 | 26 | | 39 | 4 | | 40 | 4 | | 41 | 29 | | 42 | 9 | | 43 | 8 | | 44 | 4 | | 45 | 42 | | 46 | 29 | | 47 | 13 | | 48 | 15 | | 49 | 3 |
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| 67.92% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 9 | | diversityRatio | 0.475 | | totalSentences | 80 | | uniqueOpeners | 38 | |
| 95.24% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 70 | | matches | | 0 | "Somewhere a bell was ringing," | | 1 | "Somewhere beyond the curtain, Tomás" |
| | ratio | 0.029 | |
| 88.57% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 23 | | totalSentences | 70 | | matches | | 0 | "She knew his name." | | 1 | "She'd been watching the green" | | 2 | "He didn't stop." | | 3 | "He vaulted a low railing," | | 4 | "Her left wrist throbbed where" | | 5 | "He was fast." | | 6 | "She had run down men" | | 7 | "She had never once let" | | 8 | "She lunged, fingertips brushing the" | | 9 | "She stopped at the lip" | | 10 | "She had the kind of" | | 11 | "He'd gone down a stairwell" | | 12 | "They'd found his torch." | | 13 | "They'd found one shoe." | | 14 | "They'd never found a single" | | 15 | "She thought about that now," | | 16 | "Her hand went to her" | | 17 | "She went down." | | 18 | "she said, and reached for" | | 19 | "She had heard it once" |
| | ratio | 0.329 | |
| 95.71% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 51 | | totalSentences | 70 | | matches | | 0 | "The rain came down in" | | 1 | "Detective Harlow Quinn ran through" | | 2 | "She knew his name." | | 3 | "She'd been watching the green" | | 4 | "The moment their eyes met" | | 5 | "Innocent men didn't run." | | 6 | "He didn't stop." | | 7 | "He vaulted a low railing," | | 8 | "Quinn followed, her shoulder scraping" | | 9 | "Water sluiced down the back" | | 10 | "Her left wrist throbbed where" | | 11 | "He was fast." | | 12 | "She had run down men" | | 13 | "She had never once let" | | 14 | "The alley dumped them into" | | 15 | "She lunged, fingertips brushing the" | | 16 | "Quinn slammed into the plywood," | | 17 | "A stairwell, she realized, half-collapsed" | | 18 | "The kind of place London" | | 19 | "Herrera was already halfway down," |
| | ratio | 0.729 | |
| 71.43% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 70 | | matches | | | ratio | 0.014 | |
| 0.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 40 | | technicalSentenceCount | 10 | | matches | | 0 | "The rain came down in sheets across Camden High Street, turning the pavement into a black mirror that swallowed the streetlights and spat them back fractured." | | 1 | "Detective Harlow Quinn ran through it, her boots hammering the slick stone, her breath sawing in time with the rhythm of the man fleeing thirty feet ahead." | | 2 | "Twenty-nine, former paramedic, struck off the NHS register for reasons that hadn't made sense until tonight." | | 3 | "She'd been watching the green neon glow of the Raven's Nest from across the street for two hours when he'd slipped out the side door with a duffel bag slung acr…" | | 4 | "Younger than her by twelve years and built like someone who'd spent his life carrying stretchers up tenement stairs." | | 5 | "She had the kind of instincts that had kept her alive through two stabbings and a building fire, and every one of them was telling her that the dark below her w…" | | 6 | "A murmur of many people, the low rolling sound of a crowd, drifting up from a place that according to every map she'd ever studied should hold nothing but flood…" | | 7 | "*In pursuit, suspect fled into a station that isn't supposed to exist, requesting units to a location I can't fully explain.* They'd already started whispering …" | | 8 | "Quinn looked at the curtain, at the impossible amber glow leaking through its edges, and felt the old grief and the older anger braid together into something th…" | | 9 | "Somewhere beyond the curtain, Tomás Herrera was disappearing into a crowd that didn't exist, carrying a bag full of answers she had been chasing for three years…" |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 7 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 66.67% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 6 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 11 | | tagDensity | 0.545 | | leniency | 1 | | rawRatio | 0.167 | | effectiveRatio | 0.167 | |