| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 34 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 67 | | tagDensity | 0.507 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 94.03% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 2512 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | 0 | "slowly" | | 1 | "suddenly" | | 2 | "quickly" |
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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) | |
| 68.15% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 2512 | | totalAiIsms | 16 | | found | | | highlights | | 0 | "measured" | | 1 | "efficient" | | 2 | "mosaic" | | 3 | "etched" | | 4 | "quivered" | | 5 | "trembled" | | 6 | "beacon" | | 7 | "flicked" | | 8 | "traced" | | 9 | "otherworldly" | | 10 | "tracing" | | 11 | "footsteps" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 164 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 1 | | narrationSentences | 164 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 199 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 61 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 2485 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 32 | | unquotedAttributions | 0 | | matches | (empty) | |
| 66.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 51 | | wordCount | 1658 | | uniqueNames | 9 | | maxNameDensity | 1.57 | | worstName | "Quinn" | | maxWindowNameDensity | 3 | | worstWindowName | "Quinn" | | discoveredNames | | Oyster | 1 | | Eva | 18 | | Quinn | 26 | | Veil | 1 | | Market | 1 | | Tube | 1 | | Camden | 1 | | Tomas | 1 | | Footsteps | 1 |
| | persons | | 0 | "Eva" | | 1 | "Quinn" | | 2 | "Market" | | 3 | "Tomas" | | 4 | "Footsteps" |
| | places | (empty) | | globalScore | 0.716 | | windowScore | 0.667 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 108 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.402 | | wordCount | 2485 | | matches | | 0 | "not the sudden crimson ring of a lethal wound, but the slow smear of someone who bled while being moved" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 199 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 66 | | mean | 37.65 | | std | 23.58 | | cv | 0.626 | | sampleLengths | | 0 | 72 | | 1 | 33 | | 2 | 64 | | 3 | 76 | | 4 | 30 | | 5 | 78 | | 6 | 24 | | 7 | 61 | | 8 | 17 | | 9 | 34 | | 10 | 30 | | 11 | 68 | | 12 | 26 | | 13 | 27 | | 14 | 86 | | 15 | 5 | | 16 | 13 | | 17 | 66 | | 18 | 6 | | 19 | 19 | | 20 | 43 | | 21 | 19 | | 22 | 66 | | 23 | 35 | | 24 | 22 | | 25 | 33 | | 26 | 60 | | 27 | 18 | | 28 | 47 | | 29 | 18 | | 30 | 53 | | 31 | 35 | | 32 | 59 | | 33 | 25 | | 34 | 6 | | 35 | 6 | | 36 | 92 | | 37 | 7 | | 38 | 14 | | 39 | 38 | | 40 | 12 | | 41 | 59 | | 42 | 15 | | 43 | 26 | | 44 | 38 | | 45 | 46 | | 46 | 78 | | 47 | 49 | | 48 | 5 | | 49 | 30 |
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| 88.15% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 8 | | totalSentences | 164 | | matches | | 0 | "been pushed" | | 1 | "was undisturbed" | | 2 | "been lifted" | | 3 | "been clipped" | | 4 | "been taught" | | 5 | "been brushed" | | 6 | "being moved" | | 7 | "been seen" | | 8 | "been tampered" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 298 | | matches | (empty) | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 12 | | semicolonCount | 8 | | flaggedSentences | 19 | | totalSentences | 199 | | ratio | 0.095 | | matches | | 0 | "Quinn kept her steps light and measured, heels finding the worn grooves in the landing tiles the way a drill sergeant expected you to move—purposeful, efficient." | | 1 | "The body lay half-curled at the base of a mosaic of a swimmer—an old Oyster card mosaic, tiles missing like loose teeth." | | 2 | "Books and bottles had spilled from crates; a brass compass sat on the concrete with its face scratched and full of dust, its needle trembling toward the dark recess where the service tunnel narrowed." | | 3 | "The charge in the air that hummed along the station walls felt natural to her—her shoulders softened the way they did when she smelled old paper." | | 4 | "The dust around where the man's boots had rested was undisturbed in arcs—like someone had been lifted vertically and then set down." | | 5 | "She lifted the compass with fingers she kept steady and tested it; the needle swung before it settled back toward the tunnel." | | 6 | "Evidence might speak in small languages; she didn't want to ruin a sentence." | | 7 | "But the scrawl elsewhere—on a scrap of paper jammed into a box of bottle caps—was quick, panicked." | | 8 | "The mention of tokens made the station fall quieter; all eyes scraped toward the vendors' stalls." | | 9 | "The knuckles bore rings of grime; the nails had been clipped neat." | | 10 | "Maintenance for the old Tube service tunnels that ran like veins under Camden—dark, damp, easy to forget." | | 11 | "She walked the platform edge slowly, eyes the way she had been taught to hold a room—top to bottom, corner to corner." | | 12 | "She knelt and scraped a thumbnail along the edge of a groove; it came away with a sliver of black gum." | | 13 | "There had been an odd payment two days ago—large for a stall that only sold trinkets." | | 14 | "An officer handed Quinn a bundle of photographs taken earlier—wide shots, close-ups, angles that tried to trap the truth like a net." | | 15 | "The blood spread in a way that suggested an extended tidal drift—not the sudden crimson ring of a lethal wound, but the slow smear of someone who bled while being moved." | | 16 | "She found a man in business attire at the edge of the crowd—a nervous little man rubbing his palms." | | 17 | "Quinn studied the man's shoes; the soles had new mud caked with the same black gum she had scraped from the seam." | | 18 | "He protested; his voice sounded small against the vault." |
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| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1356 | | adjectiveStacks | 1 | | stackExamples | | 0 | "thin, ribbon-marked volumes." |
| | adverbCount | 18 | | adverbRatio | 0.01327433628318584 | | lyAdverbCount | 3 | | lyAdverbRatio | 0.0022123893805309734 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 199 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 199 | | mean | 12.49 | | std | 9.03 | | cv | 0.723 | | sampleLengths | | 0 | 9 | | 1 | 26 | | 2 | 16 | | 3 | 11 | | 4 | 10 | | 5 | 11 | | 6 | 13 | | 7 | 9 | | 8 | 22 | | 9 | 8 | | 10 | 34 | | 11 | 36 | | 12 | 14 | | 13 | 26 | | 14 | 12 | | 15 | 12 | | 16 | 6 | | 17 | 6 | | 18 | 9 | | 19 | 16 | | 20 | 17 | | 21 | 4 | | 22 | 5 | | 23 | 8 | | 24 | 13 | | 25 | 6 | | 26 | 18 | | 27 | 5 | | 28 | 3 | | 29 | 18 | | 30 | 16 | | 31 | 19 | | 32 | 6 | | 33 | 3 | | 34 | 8 | | 35 | 5 | | 36 | 8 | | 37 | 7 | | 38 | 14 | | 39 | 16 | | 40 | 14 | | 41 | 9 | | 42 | 24 | | 43 | 35 | | 44 | 3 | | 45 | 23 | | 46 | 7 | | 47 | 4 | | 48 | 7 | | 49 | 9 |
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| 43.55% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 20 | | diversityRatio | 0.32160804020100503 | | totalSentences | 199 | | uniqueOpeners | 64 | |
| 24.88% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 134 | | matches | | 0 | "Somewhere down the platform a" |
| | ratio | 0.007 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 39 | | totalSentences | 134 | | matches | | 0 | "She stopped at the line" | | 1 | "Her watch, old leather worn" | | 2 | "She glanced at it the" | | 3 | "She kept her satchel close," | | 4 | "She tapped a chalk ring" | | 5 | "Her fingers hovered above the" | | 6 | "His left hand had a" | | 7 | "She nudged it." | | 8 | "Her voice dropped." | | 9 | "Her jaw tightened, old gears" | | 10 | "She gestured to the man's" | | 11 | "Her voice didn't rise." | | 12 | "It clipped the air, small" | | 13 | "She ran her thumb along" | | 14 | "She drew the fossil-like edge" | | 15 | "She pointed to the scuffing" | | 16 | "She tuned them out." | | 17 | "She lifted the compass with" | | 18 | "She didn't like leaving items" | | 19 | "She had been a detective" |
| | ratio | 0.291 | |
| 4.78% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 122 | | totalSentences | 134 | | matches | | 0 | "The stairwell smelled of damp" | | 1 | "Quinn kept her steps light" | | 2 | "The taped-off mouth of the" | | 3 | "Flashbulbs flared like cheap fireworks," | | 4 | "She stopped at the line" | | 5 | "Her watch, old leather worn" | | 6 | "She glanced at it the" | | 7 | "The body lay half-curled at" | | 8 | "A battered market stall had" | | 9 | "Books and bottles had spilled" | | 10 | "Eva crouched at the edge" | | 11 | "She kept her satchel close," | | 12 | "The charge in the air" | | 13 | "Eva asked, voice tight as" | | 14 | "She tapped a chalk ring" | | 15 | "The chalk gleamed pale and" | | 16 | "Quinn crouched with knees square," | | 17 | "Her fingers hovered above the" | | 18 | "The man was mid-thirties, market" | | 19 | "His left hand had a" |
| | ratio | 0.91 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 134 | | matches | (empty) | | ratio | 0 | |
| 72.43% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 71 | | technicalSentenceCount | 7 | | matches | | 0 | "The man was mid-thirties, market stall apron smeared with something that read red from a distance." | | 1 | "The face had sigils etched shallow and precise around the edge, tiny crescents that curled at the points." | | 2 | "The motion betrayed a magnetism that wasn't normal for compass needles in a chain of underground pipes." | | 3 | "An officer handed Quinn a bundle of photographs taken earlier—wide shots, close-ups, angles that tried to trap the truth like a net." | | 4 | "The blood spread in a way that suggested an extended tidal drift—not the sudden crimson ring of a lethal wound, but the slow smear of someone who bled while bei…" | | 5 | "The man's palms were damp, the mud on his soles drying into cracked webbing." | | 6 | "She had put together a shape the others had missed, but shapes invited questions that could rupture easy judgments." |
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| 95.59% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 34 | | uselessAdditionCount | 2 | | matches | | 0 | "Eva asked, voice tight as a wire" | | 1 | "the constable asked, confused" |
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| 75.37% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 28 | | fancyCount | 5 | | fancyTags | | 0 | "Eva breathed (breathe)" | | 1 | "Quinn interrupted (interrupt)" | | 2 | "Eva murmured (murmur)" | | 3 | "she whispered (whisper)" | | 4 | "she ordered (order)" |
| | dialogueSentences | 67 | | tagDensity | 0.418 | | leniency | 0.836 | | rawRatio | 0.179 | | effectiveRatio | 0.149 | |