| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 3 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 8 | | tagDensity | 0.375 | | leniency | 0.75 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 88.04% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1254 | | totalAiIsmAdverbs | 3 | | 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) | |
| 48.17% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1254 | | totalAiIsms | 13 | | found | | | highlights | | 0 | "flickered" | | 1 | "glint" | | 2 | "footsteps" | | 3 | "echoed" | | 4 | "silence" | | 5 | "pulse" | | 6 | "traced" | | 7 | "unreadable" | | 8 | "flicked" | | 9 | "lurched" | | 10 | "cacophony" |
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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 | 1 | | narrationSentences | 105 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 105 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 110 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 32 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 3 | | markdownWords | 4 | | totalWords | 1232 | | ratio | 0.003 | | matches | | 0 | "Tomás Herrera." | | 1 | "wanted" | | 2 | "safe" |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 4 | | unquotedAttributions | 0 | | matches | (empty) | |
| 66.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 44 | | wordCount | 1181 | | uniqueNames | 10 | | maxNameDensity | 1.52 | | worstName | "Quinn" | | maxWindowNameDensity | 3 | | worstWindowName | "Quinn" | | discoveredNames | | Harlow | 1 | | Quinn | 18 | | Saint | 1 | | Christopher | 1 | | Raven | 1 | | Nest | 1 | | Morris | 1 | | Herrera | 18 | | Veil | 1 | | Market | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Saint" | | 3 | "Christopher" | | 4 | "Morris" | | 5 | "Herrera" |
| | places | | | globalScore | 0.738 | | windowScore | 0.667 | |
| 14.86% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 74 | | glossingSentenceCount | 4 | | matches | | 0 | "smelled like ozone and decay, weapons that" | | 1 | "looked like animal bones" | | 2 | "looked like human teeth" | | 3 | "something like resignation" |
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| 37.66% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 2 | | per1kWords | 1.623 | | wordCount | 1232 | | matches | | 0 | "Not her usual beat, but the name on the report had been enough to drag her out into" | | 1 | "not with fear, but with something like resignation" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 110 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 44 | | mean | 28 | | std | 23.07 | | cv | 0.824 | | sampleLengths | | 0 | 65 | | 1 | 2 | | 2 | 69 | | 3 | 65 | | 4 | 8 | | 5 | 62 | | 6 | 54 | | 7 | 42 | | 8 | 48 | | 9 | 3 | | 10 | 39 | | 11 | 69 | | 12 | 48 | | 13 | 41 | | 14 | 5 | | 15 | 32 | | 16 | 57 | | 17 | 13 | | 18 | 11 | | 19 | 31 | | 20 | 3 | | 21 | 66 | | 22 | 40 | | 23 | 21 | | 24 | 25 | | 25 | 10 | | 26 | 2 | | 27 | 34 | | 28 | 17 | | 29 | 11 | | 30 | 5 | | 31 | 48 | | 32 | 3 | | 33 | 39 | | 34 | 4 | | 35 | 6 | | 36 | 4 | | 37 | 50 | | 38 | 9 | | 39 | 12 | | 40 | 2 | | 41 | 51 | | 42 | 2 | | 43 | 4 |
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| 95.24% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 105 | | matches | | 0 | "was connected" | | 1 | "were lined" | | 2 | "was piled" |
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| 70.55% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 4 | | totalVerbs | 206 | | matches | | 0 | "was willing" | | 1 | "wasn’t running" | | 2 | "was leading" | | 3 | "was saying" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 18 | | semicolonCount | 0 | | flaggedSentences | 14 | | totalSentences | 110 | | ratio | 0.127 | | matches | | 0 | "The suspect—lean, fast, and already halfway down the next side street—glanced back just long enough for her to catch the glint of a Saint Christopher medallion bouncing against his chest." | | 1 | "Herrera wasn’t just some two-bit criminal—he was connected." | | 2 | "Then she saw it—the manhole cover, slightly ajar." | | 3 | "The walls were lined with graffiti—some fresh, some so old the paint had flaked away to nothing." | | 4 | "Quinn had heard whispers of it, of course—every cop in the city had." | | 5 | "The crowd was a mix of the desperate and the dangerous—faces half-hidden in hoods, eyes darting in the dim light." | | 6 | "A woman—pale, with eyes like polished river stones—hissed at her, baring teeth that were just a little too sharp." | | 7 | "She reached into her pocket, fingers closing around the only thing she had—a crumpled twenty-pound note." | | 8 | "Herrera’s expression was unreadable—fear, defiance, something else entirely." | | 9 | "Herrera stood in the center of the room, his chest heaving, his hands raised slightly—a gesture of surrender, or maybe just exhaustion." | | 10 | "Quinn spun, her finger tightening on the trigger—but the figure was already gone, melted back into the darkness." | | 11 | "The shot echoed through the chamber, the muzzle flash illuminating Herrera’s face—wide-eyed, not with fear, but with something like resignation." | | 12 | "The walls of the chamber rippled, the stalls beyond twisting into something else—something that wasn’t there before." | | 13 | "Its face—if it could be called a face—was a shifting mass of angles and hollows, like a reflection in broken glass." |
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| 95.72% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1203 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 54 | | adverbRatio | 0.04488778054862843 | | lyAdverbCount | 6 | | lyAdverbRatio | 0.004987531172069825 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 110 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 110 | | mean | 11.2 | | std | 6.76 | | cv | 0.604 | | sampleLengths | | 0 | 15 | | 1 | 20 | | 2 | 30 | | 3 | 2 | | 4 | 19 | | 5 | 20 | | 6 | 8 | | 7 | 22 | | 8 | 15 | | 9 | 12 | | 10 | 18 | | 11 | 20 | | 12 | 8 | | 13 | 8 | | 14 | 15 | | 15 | 2 | | 16 | 18 | | 17 | 7 | | 18 | 12 | | 19 | 15 | | 20 | 11 | | 21 | 28 | | 22 | 18 | | 23 | 17 | | 24 | 7 | | 25 | 13 | | 26 | 18 | | 27 | 7 | | 28 | 10 | | 29 | 3 | | 30 | 13 | | 31 | 8 | | 32 | 4 | | 33 | 9 | | 34 | 5 | | 35 | 15 | | 36 | 22 | | 37 | 20 | | 38 | 5 | | 39 | 7 | | 40 | 16 | | 41 | 8 | | 42 | 17 | | 43 | 4 | | 44 | 3 | | 45 | 11 | | 46 | 11 | | 47 | 19 | | 48 | 5 | | 49 | 6 |
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| 42.42% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 10 | | diversityRatio | 0.3090909090909091 | | totalSentences | 110 | | uniqueOpeners | 34 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 7 | | totalSentences | 98 | | matches | | 0 | "Then she saw it—the manhole" | | 1 | "Then, suddenly, the tunnel opened" | | 2 | "Then Herrera turned, his gaze" | | 3 | "Then he bolted." | | 4 | "Then he reached into his" | | 5 | "Instead, his fingers closed around" | | 6 | "Then the screaming started." |
| | ratio | 0.071 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 15 | | totalSentences | 98 | | matches | | 0 | "She’d been tailing him for" | | 1 | "She lifted the cover just" | | 2 | "She kept her head down," | | 3 | "She reached into her pocket," | | 4 | "She shoved it into the" | | 5 | "She was close enough to" | | 6 | "She lost sight of him" | | 7 | "She followed, bursting into a" | | 8 | "he said, his voice steady" | | 9 | "He staggered back, his hand" | | 10 | "She reached for her torch," | | 11 | "He wasn’t moving." | | 12 | "His eyes were wide, fixed" | | 13 | "Its limbs were too long," | | 14 | "Its face—if it could be" |
| | ratio | 0.153 | |
| 67.14% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 77 | | totalSentences | 98 | | matches | | 0 | "The neon sign flickered above" | | 1 | "Detective Harlow Quinn’s boots splashed" | | 2 | "The suspect—lean, fast, and already" | | 3 | "She’d been tailing him for" | | 4 | "Herrera wasn’t just some two-bit" | | 5 | "Herrera ducked left, vanishing into" | | 6 | "Quinn followed, her shoulder scraping" | | 7 | "The alley opened into a" | | 8 | "A single flickering streetlamp threw" | | 9 | "Quinn crouched, fingers curling around" | | 10 | "The rain had washed away" | | 11 | "Underground meant no backup, no" | | 12 | "She lifted the cover just" | | 13 | "The ladder descended into darkness," | | 14 | "The air below was thick" | | 15 | "The walls were lined with" | | 16 | "Herrera’s footsteps echoed ahead, quick" | | 17 | "Quinn moved forward, her hand" | | 18 | "The tunnel branched, then branched" | | 19 | "The air grew colder, the" |
| | ratio | 0.786 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 98 | | matches | (empty) | | ratio | 0 | |
| 91.84% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 56 | | technicalSentenceCount | 4 | | matches | | 0 | "The air below was thick with the scent of damp earth and something older, something that made the hairs on the back of her neck stand on end." | | 1 | "A woman—pale, with eyes like polished river stones—hissed at her, baring teeth that were just a little too sharp." | | 2 | "Herrera was fast, weaving through the crowd with the ease of someone who knew these tunnels like the back of his hand." | | 3 | "She lost sight of him for a second, then spotted him again, ducking behind a curtain of beads that clattered as he passed through." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 3 | | uselessAdditionCount | 1 | | matches | | 0 | "Quinn said, her voice low" |
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| 25.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 3 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 8 | | tagDensity | 0.375 | | leniency | 0.75 | | rawRatio | 0.333 | | effectiveRatio | 0.25 | |