| 50.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 10 | | adverbTagCount | 3 | | adverbTags | | 0 | "Eva said carefully [carefully]" | | 1 | "She looked around [around]" | | 2 | "Quinn said flatly [flatly]" |
| | dialogueSentences | 40 | | tagDensity | 0.25 | | leniency | 0.5 | | rawRatio | 0.3 | | effectiveRatio | 0.15 | |
| 93.23% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1478 | | totalAiIsmAdverbs | 2 | | found | | | highlights | | |
| 80.00% | AI-ism character names | Target: 0 AI-default names (17 tracked, −20% each) | | codexExemptions | (empty) | | found | | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 52.64% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1478 | | totalAiIsms | 14 | | found | | | highlights | | 0 | "silence" | | 1 | "scanning" | | 2 | "pulse" | | 3 | "etched" | | 4 | "pristine" | | 5 | "grave" | | 6 | "tension" | | 7 | "flicker" | | 8 | "quivered" | | 9 | "trembled" | | 10 | "familiar" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "air was thick with" | | count | 1 |
|
| | highlights | | 0 | "The air was thick with" |
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| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 1 | | narrationSentences | 157 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 157 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 186 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 33 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 1 | | markdownWords | 6 | | totalWords | 1449 | | ratio | 0.004 | | matches | | 0 | "For J—my light in the dark." |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 18 | | unquotedAttributions | 0 | | matches | (empty) | |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 82 | | wordCount | 1119 | | uniqueNames | 22 | | maxNameDensity | 2.06 | | worstName | "Quinn" | | maxWindowNameDensity | 5.5 | | worstWindowName | "Quinn" | | discoveredNames | | Camden | 1 | | High | 1 | | Street | 1 | | Transport | 1 | | London | 2 | | Harlow | 1 | | Quinn | 23 | | Jason | 2 | | Reardon | 7 | | Tube | 1 | | Patel | 7 | | Morris | 5 | | Three | 1 | | Covent | 1 | | Garden | 1 | | Kowalski | 1 | | Aurora | 6 | | Eva | 13 | | Veil | 3 | | Compass | 1 | | Whitechapel | 1 | | Market | 2 |
| | persons | | 0 | "Camden" | | 1 | "Harlow" | | 2 | "Quinn" | | 3 | "Jason" | | 4 | "Reardon" | | 5 | "Patel" | | 6 | "Morris" | | 7 | "Kowalski" | | 8 | "Aurora" | | 9 | "Eva" | | 10 | "Compass" | | 11 | "Market" |
| | places | | 0 | "High" | | 1 | "Street" | | 2 | "London" | | 3 | "Covent" | | 4 | "Garden" | | 5 | "Whitechapel" |
| | globalScore | 0.472 | | windowScore | 0 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 72 | | glossingSentenceCount | 1 | | matches | | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1449 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 186 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 81 | | mean | 17.89 | | std | 18.85 | | cv | 1.054 | | sampleLengths | | 0 | 93 | | 1 | 49 | | 2 | 80 | | 3 | 42 | | 4 | 30 | | 5 | 30 | | 6 | 34 | | 7 | 31 | | 8 | 7 | | 9 | 8 | | 10 | 26 | | 11 | 36 | | 12 | 3 | | 13 | 17 | | 14 | 11 | | 15 | 12 | | 16 | 57 | | 17 | 45 | | 18 | 6 | | 19 | 2 | | 20 | 2 | | 21 | 53 | | 22 | 9 | | 23 | 48 | | 24 | 2 | | 25 | 10 | | 26 | 8 | | 27 | 9 | | 28 | 26 | | 29 | 6 | | 30 | 35 | | 31 | 13 | | 32 | 20 | | 33 | 28 | | 34 | 8 | | 35 | 4 | | 36 | 3 | | 37 | 9 | | 38 | 10 | | 39 | 7 | | 40 | 26 | | 41 | 8 | | 42 | 5 | | 43 | 22 | | 44 | 32 | | 45 | 3 | | 46 | 3 | | 47 | 16 | | 48 | 72 | | 49 | 6 |
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| 96.32% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 4 | | totalSentences | 157 | | matches | | 0 | "was sprawled" | | 1 | "being left" | | 2 | "been placed" | | 3 | "been convinced" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 210 | | matches | (empty) | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 28 | | semicolonCount | 0 | | flaggedSentences | 23 | | totalSentences | 186 | | ratio | 0.124 | | matches | | 0 | "The air was thick with damp and iron, laced with something else—something metallic, but not quite blood." | | 1 | "At the center of it all lay Jason Reardon—mid-thirties, private security contractor, reported missing for five days." | | 2 | "His clothes were intact—designer shirt, tailored trousers—expensive, dry, and strangely free of dust despite being left in a disused Tube station." | | 3 | "In a place where everything else—walls, benches, rails—was slick with mildew." | | 4 | "There, on the ring finger, a faint circular indentation—recent." | | 5 | "And yet, the area around the body was untouched—no tags, no footprints other than the uniforms who arrived first." | | 6 | "The rails ended abruptly in a rusted tangle, but beyond—beyond—there was something wrong with the air." | | 7 | "Quinn’s hand brushed the worn leather watch on her wrist—the one Morris had given her before he vanished." | | 8 | "She’d argued then—hysterical, they’d said." | | 9 | "She flexed her fingers, the ache in her left shoulder flaring—residual damage from the blast that took Morris." | | 10 | "The way Morris had screamed—not in pain." | | 11 | "“I know the victim,” Eva said, tucking a curl behind her left ear—a nervous habit Quinn recognized from Aurora’s old letters." | | 12 | "Quinn studied her—the intelligence in those green eyes, the tension in her freckled face." | | 13 | "Felt it—cold, porous, unnaturally still." | | 14 | "And then, from behind the collapsed service door—a flicker." | | 15 | "Inside, beneath her service pistol and spare ammo, lay a small brass compass—casing green with verdigris, face etched with sigils." | | 16 | "It quivered, then swung sharply—toward the shimmer." | | 17 | "She watched as the rift widened—a doorway of darkness edged in silver filament, pulsing like a heartbeat." | | 18 | "The scent of burnt sage and something older—dust and ink and blood." | | 19 | "The smell made her gag—bitter, fermented, like grave soil." | | 20 | "The Veil Market unfolded around them—a cavernous hall beneath London’s forgotten underbelly, lit by floating orbs of amber light." | | 21 | "Engraved inside: *For J—my light in the dark.*" | | 22 | "But the vendor—tall, hooded, skin like ash—wasn’t human." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1150 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 32 | | adverbRatio | 0.02782608695652174 | | lyAdverbCount | 8 | | lyAdverbRatio | 0.006956521739130435 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 186 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 186 | | mean | 7.79 | | std | 6.2 | | cv | 0.795 | | sampleLengths | | 0 | 24 | | 1 | 17 | | 2 | 25 | | 3 | 13 | | 4 | 14 | | 5 | 17 | | 6 | 15 | | 7 | 8 | | 8 | 9 | | 9 | 10 | | 10 | 4 | | 11 | 2 | | 12 | 10 | | 13 | 9 | | 14 | 3 | | 15 | 5 | | 16 | 3 | | 17 | 21 | | 18 | 2 | | 19 | 11 | | 20 | 17 | | 21 | 10 | | 22 | 15 | | 23 | 4 | | 24 | 7 | | 25 | 9 | | 26 | 4 | | 27 | 2 | | 28 | 4 | | 29 | 12 | | 30 | 18 | | 31 | 5 | | 32 | 1 | | 33 | 1 | | 34 | 19 | | 35 | 8 | | 36 | 8 | | 37 | 16 | | 38 | 2 | | 39 | 5 | | 40 | 7 | | 41 | 6 | | 42 | 2 | | 43 | 18 | | 44 | 8 | | 45 | 6 | | 46 | 15 | | 47 | 2 | | 48 | 2 | | 49 | 6 |
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| 68.46% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 6 | | diversityRatio | 0.43010752688172044 | | totalSentences | 186 | | uniqueOpeners | 80 | |
| 52.08% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 128 | | matches | | 0 | "Then she noticed it: beneath" | | 1 | "Just like Morris." |
| | ratio | 0.016 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 24 | | totalSentences | 128 | | matches | | 0 | "His body was sprawled against" | | 1 | "Her sharp jaw tightened as" | | 2 | "His clothes were intact—designer shirt," | | 3 | "He held a penlight, flicking" | | 4 | "Her eyes lingered on Reardon’s" | | 5 | "He’d worn a ring." | | 6 | "Her gaze drifted to the" | | 7 | "she asked, voice low" | | 8 | "She turned back to the" | | 9 | "Her breath caught." | | 10 | "Her voice was steel" | | 11 | "She’d argued then—hysterical, they’d said." | | 12 | "She’d spent the next two" | | 13 | "She flexed her fingers, the" | | 14 | "She wore a heavy coat," | | 15 | "Her green eyes were wide," | | 16 | "She looked around" | | 17 | "They waited until the uniforms" | | 18 | "She’d thought it junk." | | 19 | "She set it on the" |
| | ratio | 0.188 | |
| 100.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 86 | | totalSentences | 128 | | matches | | 0 | "Rain drummed a steady rhythm" | | 1 | "The air was thick with" | | 2 | "Detective Harlow Quinn adjusted the" | | 3 | "The glow of portable floodlights" | | 4 | "Uniforms stood back, murmuring among" | | 5 | "His body was sprawled against" | | 6 | "Quinn knelt, one gloved hand" | | 7 | "Time of death estimated between" | | 8 | "Her sharp jaw tightened as" | | 9 | "Fingernails were clean." | | 10 | "His clothes were intact—designer shirt," | | 11 | "He held a penlight, flicking" | | 12 | "Quinn didn’t answer immediately." | | 13 | "Her eyes lingered on Reardon’s" | | 14 | "There, on the ring finger," | | 15 | "He’d worn a ring." | | 16 | "Patel continued, reading from a" | | 17 | "Quinn stood, scanning the station." | | 18 | "Her gaze drifted to the" | | 19 | "The rails ended abruptly in" |
| | ratio | 0.672 | |
| 78.13% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 128 | | matches | | 0 | "As if Reardon had been" | | 1 | "Before Aurora vanished without a" |
| | ratio | 0.016 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 39 | | technicalSentenceCount | 2 | | matches | | 0 | "And yet, the area around the body was untouched—no tags, no footprints other than the uniforms who arrived first." | | 1 | "She flexed her fingers, the ache in her left shoulder flaring—residual damage from the blast that took Morris." |
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| 75.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 10 | | uselessAdditionCount | 1 | | matches | | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 7 | | fancyCount | 1 | | fancyTags | | 0 | "Patel continued (continue)" |
| | dialogueSentences | 40 | | tagDensity | 0.175 | | leniency | 0.35 | | rawRatio | 0.143 | | effectiveRatio | 0.05 | |