| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 16 | | adverbTagCount | 1 | | adverbTags | | 0 | "Herrera said softly [softly]" |
| | dialogueSentences | 36 | | tagDensity | 0.444 | | leniency | 0.889 | | rawRatio | 0.063 | | effectiveRatio | 0.056 | |
| 76.42% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1484 | | totalAiIsmAdverbs | 7 | | found | | | highlights | | 0 | "slightly" | | 1 | "sharply" | | 2 | "slowly" | | 3 | "very" | | 4 | "softly" | | 5 | "really" |
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| 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) | |
| 69.68% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1484 | | totalAiIsms | 9 | | found | | | highlights | | 0 | "stomach" | | 1 | "gloom" | | 2 | "spectral" | | 3 | "dancing" | | 4 | "scanned" | | 5 | "echoed" | | 6 | "lilt" | | 7 | "flickered" | | 8 | "chill" |
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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 | 2 | | narrationSentences | 130 | | matches | | 0 | "looked terrified" | | 1 | "felt a chill" |
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| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 2 | | narrationSentences | 130 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 150 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 35 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 3 | | markdownWords | 6 | | totalWords | 1467 | | ratio | 0.004 | | matches | | 0 | "Entry requirement," | | 1 | "clack" | | 2 | "The Veil Market." |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 16 | | unquotedAttributions | 0 | | matches | (empty) | |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 44 | | wordCount | 1177 | | uniqueNames | 11 | | maxNameDensity | 1.27 | | worstName | "Harlow" | | maxWindowNameDensity | 5 | | worstWindowName | "Herrera" | | discoveredNames | | London | 2 | | Harlow | 15 | | Quinn | 1 | | Camden | 1 | | Morris | 4 | | Tube | 2 | | Veil | 1 | | Saint | 1 | | Christopher | 1 | | Herrera | 15 | | Spanish | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Morris" | | 3 | "Tube" | | 4 | "Saint" | | 5 | "Christopher" | | 6 | "Herrera" |
| | places | | | globalScore | 0.863 | | windowScore | 0 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 81 | | glossingSentenceCount | 1 | | matches | | 0 | "knife that seemed to absorb the light" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.682 | | wordCount | 1467 | | matches | | 0 | "not out of respect, but out of confusion" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 150 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 62 | | mean | 23.66 | | std | 14.67 | | cv | 0.62 | | sampleLengths | | 0 | 55 | | 1 | 18 | | 2 | 3 | | 3 | 58 | | 4 | 64 | | 5 | 36 | | 6 | 4 | | 7 | 26 | | 8 | 25 | | 9 | 14 | | 10 | 24 | | 11 | 10 | | 12 | 60 | | 13 | 6 | | 14 | 16 | | 15 | 37 | | 16 | 22 | | 17 | 32 | | 18 | 12 | | 19 | 4 | | 20 | 21 | | 21 | 31 | | 22 | 38 | | 23 | 4 | | 24 | 41 | | 25 | 27 | | 26 | 11 | | 27 | 23 | | 28 | 32 | | 29 | 19 | | 30 | 45 | | 31 | 1 | | 32 | 9 | | 33 | 42 | | 34 | 17 | | 35 | 18 | | 36 | 35 | | 37 | 29 | | 38 | 11 | | 39 | 34 | | 40 | 23 | | 41 | 32 | | 42 | 30 | | 43 | 11 | | 44 | 20 | | 45 | 20 | | 46 | 12 | | 47 | 4 | | 48 | 29 | | 49 | 7 |
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| 97.17% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 130 | | matches | | 0 | "been stalled" | | 1 | "was gone" | | 2 | "been colonized" |
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| 45.68% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 5 | | totalVerbs | 216 | | matches | | 0 | "wasn't running" | | 1 | "was heading" | | 2 | "was flexing" | | 3 | "was rubbing" | | 4 | "was surfacing" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 8 | | semicolonCount | 2 | | flaggedSentences | 10 | | totalSentences | 150 | | ratio | 0.067 | | matches | | 0 | "He—if it was a ‘he’—moved with a fluid, impossible grace that made Harlow’s stomach turn." | | 1 | "The suspect had veered off the main thoroughfare, heading toward the skeletal remains of the huge construction project near Camden—the one that had been stalled in litigation for three years." | | 2 | "The wood didn't move; it rippled like a disturb pool of water, turning translucent, then gaseous." | | 3 | "A smell hit her—ozone, frankincense, and the copper tang of old blood." | | 4 | "Above her was London—rules, paperwork, the slow but logical grind of the justice system." | | 5 | "The crowd parted around her—not out of respect, but out of confusion." | | 6 | "They smelled the law on her; the scent of cheap precinct coffee and rigid morality." | | 7 | "A low, raspy chuckle came from the vendor behind Herrera—a creature whose face was entirely wrapped in bandages." | | 8 | "The memory of Morris hit her again—the emptiness in his eyes." | | 9 | "The paramedic in him was surfacing—triage." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 310 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 10 | | adverbRatio | 0.03225806451612903 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.016129032258064516 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 150 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 150 | | mean | 9.78 | | std | 6.79 | | cv | 0.695 | | sampleLengths | | 0 | 26 | | 1 | 24 | | 2 | 5 | | 3 | 18 | | 4 | 3 | | 5 | 11 | | 6 | 8 | | 7 | 15 | | 8 | 24 | | 9 | 7 | | 10 | 5 | | 11 | 21 | | 12 | 16 | | 13 | 15 | | 14 | 6 | | 15 | 30 | | 16 | 4 | | 17 | 9 | | 18 | 17 | | 19 | 7 | | 20 | 8 | | 21 | 10 | | 22 | 14 | | 23 | 6 | | 24 | 11 | | 25 | 1 | | 26 | 3 | | 27 | 3 | | 28 | 10 | | 29 | 2 | | 30 | 4 | | 31 | 5 | | 32 | 11 | | 33 | 7 | | 34 | 31 | | 35 | 6 | | 36 | 5 | | 37 | 11 | | 38 | 9 | | 39 | 16 | | 40 | 12 | | 41 | 4 | | 42 | 18 | | 43 | 5 | | 44 | 4 | | 45 | 14 | | 46 | 2 | | 47 | 2 | | 48 | 5 | | 49 | 10 |
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| 48.22% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 21 | | diversityRatio | 0.37333333333333335 | | totalSentences | 150 | | uniqueOpeners | 56 | |
| 87.72% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 114 | | matches | | 0 | "Then, the beam caught something" | | 1 | "Instead of commuters, figures in" | | 2 | "Dark curly hair." |
| | ratio | 0.026 | |
| 48.07% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 49 | | totalSentences | 114 | | matches | | 0 | "She didn’t feel the water" | | 1 | "She only felt the hunt." | | 2 | "Her boots slammed against the" | | 3 | "He—if it was a" | | 4 | "He wasn't running so much" | | 5 | "She didn't have his grace." | | 6 | "She scrambled, metal biting into" | | 7 | "She was forty-one, and nights" | | 8 | "She wiped mud from her" | | 9 | "He was heading underground." | | 10 | "She saw him slip through" | | 11 | "she whispered, the steam of" | | 12 | "She clicked on her heavy-duty" | | 13 | "It was a token." | | 14 | "It felt warm to the" | | 15 | "It triggered the same primitive" | | 16 | "She looked at the blockade." | | 17 | "She checked the worn leather" | | 18 | "She drew her baton, flicking" | | 19 | "She stepped onto the stairs." |
| | ratio | 0.43 | |
| 30.18% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 98 | | totalSentences | 114 | | matches | | 0 | "The rain had turned London" | | 1 | "She didn’t feel the water" | | 2 | "She only felt the hunt." | | 3 | "Her boots slammed against the" | | 4 | "The command was a reflex," | | 5 | "The figure ahead of her" | | 6 | "He—if it was a" | | 7 | "He wasn't running so much" | | 8 | "Harlow hit the fence a" | | 9 | "She didn't have his grace." | | 10 | "She scrambled, metal biting into" | | 11 | "She was forty-one, and nights" | | 12 | "She wiped mud from her" | | 13 | "The suspect had veered off" | | 14 | "He was heading underground." | | 15 | "Harlow pushed harder, her breath" | | 16 | "She saw him slip through" | | 17 | "The boards were thick, rotted" | | 18 | "she whispered, the steam of" | | 19 | "She clicked on her heavy-duty" |
| | ratio | 0.86 | |
| 43.86% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 114 | | matches | | 0 | "By the time she reached" |
| | ratio | 0.009 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 49 | | technicalSentenceCount | 2 | | matches | | 0 | "It triggered the same primitive alarm bells that had rung the night she found DS Morris in that warehouse, twisted and broken by things that didn't belong in a …" | | 1 | "Harlow saw a jar on a nearby table containing a human hand that was flexing its fingers." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 16 | | uselessAdditionCount | 5 | | matches | | 0 | "she whispered, the steam of her breath clouding her vision" | | 1 | "he said, his voice carrying a soft Spanish lilt" | | 2 | "Harlow snapped, not taking her eyes off Herrera" | | 3 | "Harlow said, though her knuckles were white around the baton handle" | | 4 | "she said, her voice low and dangerous" |
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| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 15 | | fancyCount | 7 | | fancyTags | | 0 | "she whispered (whisper)" | | 1 | "she muttered (mutter)" | | 2 | "it wheezed (wheeze)" | | 3 | "Harlow snapped (snap)" | | 4 | "Herrera hissed (hiss)" | | 5 | "Herrera whispered (whisper)" | | 6 | "she murmured (murmur)" |
| | dialogueSentences | 36 | | tagDensity | 0.417 | | leniency | 0.833 | | rawRatio | 0.467 | | effectiveRatio | 0.389 | |