| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 24 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 47 | | tagDensity | 0.511 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 97.91% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 2394 | | totalAiIsmAdverbs | 1 | | found | | 0 | | 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) | |
| 68.67% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 2394 | | totalAiIsms | 15 | | found | | | highlights | | 0 | "could feel" | | 1 | "silence" | | 2 | "calculating" | | 3 | "flicked" | | 4 | "pulsed" | | 5 | "echoed" | | 6 | "whisper" | | 7 | "velvet" | | 8 | "tracing" | | 9 | "echo" | | 10 | "trembled" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "hung in the air" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 244 | | matches | (empty) | |
| 90.16% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 3 | | hedgeCount | 6 | | narrationSentences | 244 | | filterMatches | | | hedgeMatches | | 0 | "tried to" | | 1 | "managed to" | | 2 | "seemed to" | | 3 | "started to" |
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| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 262 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 31 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 11 | | markdownWords | 17 | | totalWords | 2381 | | ratio | 0.007 | | matches | | 0 | "The Raven’s Nest" | | 1 | "beggars" | | 2 | "beggars" | | 3 | "Raven’s Nest" | | 4 | "market" | | 5 | "alive" | | 6 | "sang" | | 7 | "can’t" | | 8 | "real enough for that" | | 9 | "body" | | 10 | "Good." |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 23 | | unquotedAttributions | 0 | | matches | (empty) | |
| 66.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 99 | | wordCount | 1950 | | uniqueNames | 25 | | maxNameDensity | 1.44 | | worstName | "Herrera" | | maxWindowNameDensity | 3 | | worstWindowName | "Herrera" | | discoveredNames | | Raven | 3 | | Nest | 3 | | Seville | 1 | | Herrera | 28 | | Defensive | 1 | | London | 1 | | Morris | 4 | | Slurred | 1 | | Quinn | 25 | | Neutral | 1 | | Took | 1 | | Tube | 3 | | Veil | 4 | | Market | 4 | | Camden | 1 | | Victorian | 2 | | Short | 1 | | Burial | 1 | | Herrera-clone | 1 | | Saint | 1 | | Christopher | 1 | | Thames | 1 | | Rain | 3 | | Three | 4 | | One | 3 |
| | persons | | 0 | "Raven" | | 1 | "Herrera" | | 2 | "Morris" | | 3 | "Quinn" | | 4 | "Market" | | 5 | "Herrera-clone" | | 6 | "Saint" | | 7 | "Christopher" | | 8 | "Rain" | | 9 | "One" |
| | places | | 0 | "Nest" | | 1 | "Seville" | | 2 | "London" | | 3 | "Tube" | | 4 | "Veil" | | 5 | "Camden" | | 6 | "Victorian" | | 7 | "Thames" |
| | globalScore | 0.782 | | windowScore | 0.667 | |
| 47.26% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 146 | | glossingSentenceCount | 6 | | matches | | 0 | "felt like a knife twisting in her own r" | | 1 | "looked like a syringe in his palm" | | 2 | "sounded like he was choking on smoke" | | 3 | "tasted like rust" | | 4 | "as if grinding it into muscle memory" | | 5 | "looked like it bled black" |
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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 | 2381 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 262 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 67 | | mean | 35.54 | | std | 19.24 | | cv | 0.541 | | sampleLengths | | 0 | 49 | | 1 | 42 | | 2 | 55 | | 3 | 46 | | 4 | 51 | | 5 | 31 | | 6 | 56 | | 7 | 33 | | 8 | 89 | | 9 | 42 | | 10 | 38 | | 11 | 52 | | 12 | 35 | | 13 | 18 | | 14 | 17 | | 15 | 29 | | 16 | 24 | | 17 | 54 | | 18 | 13 | | 19 | 34 | | 20 | 46 | | 21 | 56 | | 22 | 31 | | 23 | 25 | | 24 | 22 | | 25 | 33 | | 26 | 56 | | 27 | 40 | | 28 | 6 | | 29 | 3 | | 30 | 50 | | 31 | 53 | | 32 | 59 | | 33 | 38 | | 34 | 32 | | 35 | 52 | | 36 | 62 | | 37 | 22 | | 38 | 55 | | 39 | 73 | | 40 | 4 | | 41 | 9 | | 42 | 38 | | 43 | 23 | | 44 | 64 | | 45 | 9 | | 46 | 13 | | 47 | 49 | | 48 | 19 | | 49 | 33 |
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| 96.64% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 6 | | totalSentences | 244 | | matches | | 0 | "been plastered" | | 1 | "been tracked" | | 2 | "was supposed" | | 3 | "was gone" | | 4 | "were made" | | 5 | "was gone" |
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| 45.86% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 8 | | totalVerbs | 346 | | matches | | 0 | "was losing" | | 1 | "was always twitching" | | 2 | "was choking" | | 3 | "was already moving" | | 4 | "were heading" | | 5 | "were bleeding" | | 6 | "was waiting" | | 7 | "was already moving" |
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| 22.90% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 16 | | semicolonCount | 0 | | flaggedSentences | 11 | | totalSentences | 262 | | ratio | 0.042 | | matches | | 0 | "He was right about one thing—her fingers had locked around his bicep with the kind of precision that made even the most uncooperative victims reconsider resistance." | | 1 | "The old wound—her partner, lost to mysteries she still couldn’t name—was a tool, even if it felt like a knife twisting in her own ribs." | | 2 | "One—medium height, olive skin catching the dim light—held what looked like a syringe in his palm." | | 3 | "One of them—Herrera—was always twitching." | | 4 | "Herrera’s hand had been on it—she’d known." | | 5 | "The lock didn’t just pop—it whined like a creature waking." | | 6 | "But no name, no address—so she’d come here." | | 7 | "The walls pulsed—damp, breathy, *alive*—as Quinn stepped through the gate." | | 8 | "Herrera again—or someone who looked exactly like him." | | 9 | "The clone staggered—*real enough for that*—but his right hand flicked upward." | | 10 | "But Herrera’s lips moved under the pressure of his gag—a whisper, an incantation." |
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| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1977 | | adjectiveStacks | 1 | | stackExamples | | 0 | "acrid, metallic beyond rust." |
| | adverbCount | 50 | | adverbRatio | 0.025290844714213456 | | lyAdverbCount | 9 | | lyAdverbRatio | 0.004552352048558422 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 262 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 262 | | mean | 9.09 | | std | 6.1 | | cv | 0.671 | | sampleLengths | | 0 | 11 | | 1 | 11 | | 2 | 14 | | 3 | 12 | | 4 | 1 | | 5 | 11 | | 6 | 3 | | 7 | 1 | | 8 | 1 | | 9 | 26 | | 10 | 18 | | 11 | 12 | | 12 | 17 | | 13 | 8 | | 14 | 14 | | 15 | 4 | | 16 | 10 | | 17 | 18 | | 18 | 20 | | 19 | 15 | | 20 | 16 | | 21 | 4 | | 22 | 2 | | 23 | 5 | | 24 | 2 | | 25 | 18 | | 26 | 21 | | 27 | 25 | | 28 | 10 | | 29 | 7 | | 30 | 17 | | 31 | 3 | | 32 | 4 | | 33 | 2 | | 34 | 21 | | 35 | 8 | | 36 | 2 | | 37 | 2 | | 38 | 6 | | 39 | 23 | | 40 | 4 | | 41 | 23 | | 42 | 5 | | 43 | 5 | | 44 | 11 | | 45 | 16 | | 46 | 3 | | 47 | 2 | | 48 | 7 | | 49 | 11 |
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| 43.13% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 18 | | diversityRatio | 0.26717557251908397 | | totalSentences | 262 | | uniqueOpeners | 70 | |
| 80.91% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 5 | | totalSentences | 206 | | matches | | 0 | "At least, not visibly." | | 1 | "Maybe she’d left it there" | | 2 | "Too fast for a man" | | 3 | "Just the sound of her" | | 4 | "Just the leather and the" |
| | ratio | 0.024 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 48 | | totalSentences | 206 | | matches | | 0 | "His left arm flailed, almost" | | 1 | "He was right about one" | | 2 | "It dangled from the iron" | | 3 | "His knee had taken a" | | 4 | "He tried to wrench free," | | 5 | "He managed to sneer, though" | | 6 | "She stepped into him, her" | | 7 | "His face went ashen." | | 8 | "She shoved him, and he" | | 9 | "He knew the place." | | 10 | "She didn’t let it faze" | | 11 | "He was losing time." | | 12 | "She could feel it in" | | 13 | "His voice was soft, Seville" | | 14 | "She let her hand fall" | | 15 | "She needed a different kind" | | 16 | "He thought he was the" | | 17 | "She kept her stance open," | | 18 | "He smiled, though it didn’t" | | 19 | "Her accent clipped the syllables" |
| | ratio | 0.233 | |
| 47.38% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 170 | | totalSentences | 206 | | matches | | 0 | "Quinn's hand snapped out, intercepting" | | 1 | "The man yelped as his" | | 2 | "Rain slashed sideways, turning the" | | 3 | "His left arm flailed, almost" | | 4 | "The suspect’s teeth chattered" | | 5 | "He was right about one" | | 6 | "Quinn gestured to the mangled" | | 7 | "It dangled from the iron" | | 8 | "His knee had taken a" | | 9 | "Military school taught you how" | | 10 | "He tried to wrench free," | | 11 | "A sharp glance upwards." | | 12 | "The green neon sign of" | | 13 | "He managed to sneer, though" | | 14 | "She stepped into him, her" | | 15 | "The watch on her left" | | 16 | "His face went ashen." | | 17 | "The clinic was a front." | | 18 | "Herrera was a back-alley medic" | | 19 | "Quinn’s words hung in the" |
| | ratio | 0.825 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 206 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 74 | | technicalSentenceCount | 2 | | matches | | 0 | "He was right about one thing—her fingers had locked around his bicep with the kind of precision that made even the most uncooperative victims reconsider resista…" | | 1 | "Quinn’s torch cut the darkness, revealing shelves of teeth, bundles in plastic wrap that moved when her light hit them." |
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| 83.33% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 24 | | uselessAdditionCount | 2 | | matches | | 0 | "He managed, though his voice was half-washed away by the downpour" | | 1 | "she said, voice colder than the key" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 9 | | fancyCount | 2 | | fancyTags | | 0 | "The suspect’s teeth chattered (chatter)" | | 1 | "She spat (spit)" |
| | dialogueSentences | 47 | | tagDensity | 0.191 | | leniency | 0.383 | | rawRatio | 0.222 | | effectiveRatio | 0.085 | |