| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 13 | | adverbTagCount | 1 | | adverbTags | | 0 | "he said softly [softly]" |
| | dialogueSentences | 31 | | tagDensity | 0.419 | | leniency | 0.839 | | rawRatio | 0.077 | | effectiveRatio | 0.065 | |
| 86.13% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1442 | | totalAiIsmAdverbs | 4 | | found | | | highlights | | 0 | "sharply" | | 1 | "slightly" | | 2 | "completely" | | 3 | "softly" |
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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) | |
| 51.46% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1442 | | totalAiIsms | 14 | | found | | | highlights | | 0 | "standard" | | 1 | "pulsed" | | 2 | "pulse" | | 3 | "scanning" | | 4 | "flicked" | | 5 | "silence" | | 6 | "shimmered" | | 7 | "electric" | | 8 | "maw" | | 9 | "perfect" | | 10 | "footsteps" | | 11 | "echoed" |
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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 |
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| | 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 | 0 | | narrationSentences | 133 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 1 | | narrationSentences | 133 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 151 | | 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 | 23 | | totalWords | 1416 | | ratio | 0.016 | | matches | | 0 | "Tomás Herrera." | | 1 | "Three years ago, Morris went underground too. Into places the report never mentioned." | | 2 | "There’s something down here. Not human. Not anymore." |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 16 | | unquotedAttributions | 0 | | matches | (empty) | |
| 83.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 41 | | wordCount | 1160 | | uniqueNames | 17 | | maxNameDensity | 1.12 | | worstName | "Quinn" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Herrera" | | discoveredNames | | Soho | 1 | | Harlow | 2 | | Quinn | 13 | | Dean | 1 | | Street | 2 | | Berwick | 1 | | Saint | 1 | | Christopher | 1 | | Glock | 1 | | Herrera | 9 | | Morris | 2 | | Veil | 1 | | Market | 2 | | Tube | 1 | | Christmas | 1 | | Spanish | 1 | | Whitechapel | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Saint" | | 3 | "Christopher" | | 4 | "Herrera" | | 5 | "Morris" | | 6 | "Market" | | 7 | "Christmas" |
| | places | | 0 | "Soho" | | 1 | "Dean" | | 2 | "Street" | | 3 | "Berwick" |
| | globalScore | 0.94 | | windowScore | 0.833 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 72 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.706 | | wordCount | 1416 | | matches | | 0 | "not with machinery, but with presence" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 151 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 77 | | mean | 18.39 | | std | 16 | | cv | 0.87 | | sampleLengths | | 0 | 84 | | 1 | 2 | | 2 | 50 | | 3 | 24 | | 4 | 5 | | 5 | 70 | | 6 | 45 | | 7 | 11 | | 8 | 15 | | 9 | 27 | | 10 | 23 | | 11 | 59 | | 12 | 13 | | 13 | 3 | | 14 | 45 | | 15 | 22 | | 16 | 24 | | 17 | 12 | | 18 | 11 | | 19 | 7 | | 20 | 11 | | 21 | 24 | | 22 | 29 | | 23 | 15 | | 24 | 14 | | 25 | 5 | | 26 | 3 | | 27 | 55 | | 28 | 10 | | 29 | 13 | | 30 | 19 | | 31 | 28 | | 32 | 28 | | 33 | 31 | | 34 | 4 | | 35 | 6 | | 36 | 30 | | 37 | 11 | | 38 | 20 | | 39 | 4 | | 40 | 1 | | 41 | 22 | | 42 | 9 | | 43 | 5 | | 44 | 35 | | 45 | 31 | | 46 | 4 | | 47 | 17 | | 48 | 17 | | 49 | 7 |
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| 97.35% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 133 | | matches | | 0 | "was—caught" | | 1 | "been pried" | | 2 | "been named" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 3 | | totalVerbs | 208 | | matches | | 0 | "was running" | | 1 | "was playing" | | 2 | "was speaking" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 25 | | semicolonCount | 0 | | flaggedSentences | 18 | | totalSentences | 151 | | ratio | 0.119 | | matches | | 0 | "Her leather watch—old, scarred, the strap frayed at the clasp—slid down her wrist as she pushed off a metal trash bin to cut the corner onto Dean Street." | | 1 | "But there he was—caught mid-frame, face half in shadow, scar visible along his forearm—lifting a lead-lined case from the back of a stolen van." | | 2 | "Her jacket—navy, unmarked, standard issue minus the badge clipped inside her pocket—clung to her shoulders, heavy with water." | | 3 | "Quinn followed, drawing her sidearm—standard-issue Glock 17—but holding it low against her thigh." | | 4 | "The frame had been pried open—recently." | | 5 | "The air that rose from below was warm, stale, and carried a scent she couldn’t place—burnt sage, perhaps, or something older, earthier." | | 6 | "Footprints—fresh, boot-shaped—dug into the grime." | | 7 | "The space stretched far beyond what geography allowed—a cavernous chamber built in the bones of a decommissioned Tube station, arched ceilings dripping with moisture, platforms long since buried repurposed into stalls." | | 8 | "A stall selling bottled storms—glass orbs swirling with miniature lightning." | | 9 | "The air thrummed—low, electric—not with machinery, but with presence." | | 10 | "And people—humans and things that wore human shapes—drifted through the aisles like ghosts." | | 11 | "They found him two days later—alive, but hollow." | | 12 | "And now, standing in this impossible place, she felt it again—the pull of something just beyond understanding." | | 13 | "Then he picked up the case and began to walk—away from the stall, toward a narrow archway beneath a flickering lantern marked with a raven symbol." | | 14 | "She’d heard stories—rumors of doctors vanishing, hospitals with missing patients, wards that didn’t appear on floor plans." | | 15 | "And she’d seen the bruises on Morris’s arms—perfect circles, like suction marks." | | 16 | "Another beside him—taller, face obscured by a hood." | | 17 | "Outside the archway, the Market hummed—a living thing, ancient, indifferent." |
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| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 322 | | adjectiveStacks | 1 | | stackExamples | | 0 | "ex-paramedic turned underground healer." |
| | adverbCount | 4 | | adverbRatio | 0.012422360248447204 | | lyAdverbCount | 1 | | lyAdverbRatio | 0.003105590062111801 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 151 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 151 | | mean | 9.38 | | std | 6.87 | | cv | 0.733 | | sampleLengths | | 0 | 14 | | 1 | 20 | | 2 | 28 | | 3 | 22 | | 4 | 2 | | 5 | 14 | | 6 | 6 | | 7 | 6 | | 8 | 24 | | 9 | 24 | | 10 | 5 | | 11 | 13 | | 12 | 18 | | 13 | 20 | | 14 | 19 | | 15 | 16 | | 16 | 13 | | 17 | 3 | | 18 | 2 | | 19 | 11 | | 20 | 11 | | 21 | 3 | | 22 | 2 | | 23 | 2 | | 24 | 8 | | 25 | 16 | | 26 | 6 | | 27 | 5 | | 28 | 12 | | 29 | 11 | | 30 | 6 | | 31 | 22 | | 32 | 5 | | 33 | 24 | | 34 | 2 | | 35 | 7 | | 36 | 6 | | 37 | 3 | | 38 | 18 | | 39 | 9 | | 40 | 5 | | 41 | 13 | | 42 | 9 | | 43 | 13 | | 44 | 24 | | 45 | 7 | | 46 | 5 | | 47 | 7 | | 48 | 4 | | 49 | 4 |
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| 51.43% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 9 | | diversityRatio | 0.3443708609271523 | | totalSentences | 151 | | uniqueOpeners | 52 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 4 | | totalSentences | 112 | | matches | | 0 | "Then she saw it: a" | | 1 | "Then a soft click." | | 2 | "Then he picked up the" | | 3 | "Then, almost inaudibly:" |
| | ratio | 0.036 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 27 | | totalSentences | 112 | | matches | | 0 | "Her leather watch—old, scarred, the" | | 1 | "She hadn’t expected to see" | | 2 | "Her jacket—navy, unmarked, standard issue" | | 3 | "She holstered her weapon and" | | 4 | "She flicked on the light." | | 5 | "She stepped down." | | 6 | "She moved fast but cautious," | | 7 | "She didn’t like the rules." | | 8 | "It wasn’t a market." | | 9 | "She spotted Herrera near a" | | 10 | "He was speaking in low," | | 11 | "She spun, elbow cocked, but" | | 12 | "he said, voice like gravel" | | 13 | "She met his gaze." | | 14 | "He’d radioed in: *There’s something" | | 15 | "They found him two days" | | 16 | "His eyes didn’t track." | | 17 | "His mouth moved, whispering numbers" | | 18 | "He died three weeks later." | | 19 | "She’d seen the claw marks" |
| | ratio | 0.241 | |
| 100.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 74 | | totalSentences | 112 | | matches | | 0 | "Rain fell in thick, silver" | | 1 | "Detective Harlow Quinn moved fast," | | 2 | "Her leather watch—old, scarred, the" | | 3 | "The suspect was ahead, just" | | 4 | "She hadn’t expected to see" | | 5 | "Quinn ducked under a sagging" | | 6 | "Her jacket—navy, unmarked, standard issue" | | 7 | "The city pulsed around her:" | | 8 | "Herrera turned sharply into a" | | 9 | "Quinn followed, drawing her sidearm—standard—issue" | | 10 | "The alley dead-ended at a" | | 11 | "Quinn slowed, scanning." | | 12 | "Graffiti of a raven with" | | 13 | "The frame had been pried" | | 14 | "She holstered her weapon and" | | 15 | "The air that rose from" | | 16 | "She flicked on the light." | | 17 | "The beam cut through damp" | | 18 | "She stepped down." | | 19 | "The passage opened into a" |
| | ratio | 0.661 | |
| 89.29% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 112 | | matches | | 0 | "To her right, a woman" | | 1 | "Because three years ago, her" |
| | ratio | 0.018 | |
| 61.69% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 44 | | technicalSentenceCount | 5 | | matches | | 0 | "Detective Harlow Quinn moved fast, boots splashing through puddles, her breath coming in hard bursts that fogged the cold air." | | 1 | "Strings of fairy lights crisscrossed overhead, casting swaying halos over wares that defied logic." | | 2 | "A thousand whispered incantations, the click of talons on stone, the hiss of creatures that hadn’t yet been named." | | 3 | "And people—humans and things that wore human shapes—drifted through the aisles like ghosts." | | 4 | "She’d heard stories—rumors of doctors vanishing, hospitals with missing patients, wards that didn’t appear on floor plans." |
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| 9.62% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 13 | | uselessAdditionCount | 3 | | matches | | 0 | "Quinn said, trying to keep her voice level" | | 1 | "he said, his voice quiet" | | 2 | "she said, voice low," |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 11 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 31 | | tagDensity | 0.355 | | leniency | 0.71 | | rawRatio | 0 | | effectiveRatio | 0 | |