| 82.35% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 7 | | adverbTagCount | 1 | | adverbTags | | 0 | "he said simply [simply]" |
| | dialogueSentences | 17 | | tagDensity | 0.412 | | leniency | 0.824 | | rawRatio | 0.143 | | effectiveRatio | 0.118 | |
| 93.28% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 2231 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | 0 | "angrily" | | 1 | "slowly" | | 2 | "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) | |
| 43.97% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 2231 | | totalAiIsms | 25 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | | | 13 | | | 14 | | | 15 | | | 16 | | | 17 | | | 18 | | | 19 | | | 20 | |
| | highlights | | 0 | "pumping" | | 1 | "glistening" | | 2 | "pulsed" | | 3 | "velvet" | | 4 | "fractured" | | 5 | "scanned" | | 6 | "pulse" | | 7 | "charged" | | 8 | "crystal" | | 9 | "shimmered" | | 10 | "hulking" | | 11 | "measured" | | 12 | "echoed" | | 13 | "flickered" | | 14 | "weight" | | 15 | "could feel" | | 16 | "jaw clenched" | | 17 | "wavered" | | 18 | "depths" | | 19 | "quickened" | | 20 | "reminder" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "jaw/fists clenched" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 1 | | narrationSentences | 208 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 5 | | hedgeCount | 1 | | narrationSentences | 208 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 218 | | gibberishSentences | 1 | | adjustedGibberishSentences | 1 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 39 | | ratio | 0.005 | | matches | | 0 | "Here the真正 dangerous deals happened." |
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| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 2218 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 10 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 74 | | wordCount | 2030 | | uniqueNames | 22 | | maxNameDensity | 0.89 | | worstName | "Quinn" | | maxWindowNameDensity | 2 | | worstWindowName | "Herrera" | | discoveredNames | | Harlow | 1 | | Quinn | 18 | | Soho | 1 | | Herrera | 17 | | Raven | 2 | | Nest | 2 | | Saint | 2 | | Christopher | 2 | | Morris | 7 | | Charing | 1 | | Cross | 1 | | Road | 1 | | Camden | 1 | | Tube | 3 | | Veil | 2 | | Market | 3 | | Greek | 1 | | Tomás | 2 | | Seville | 1 | | London | 1 | | Spanish | 1 | | Rain | 4 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Herrera" | | 3 | "Raven" | | 4 | "Saint" | | 5 | "Christopher" | | 6 | "Morris" | | 7 | "Tube" | | 8 | "Market" | | 9 | "Tomás" | | 10 | "Rain" |
| | places | | 0 | "Soho" | | 1 | "Charing" | | 2 | "Cross" | | 3 | "Road" | | 4 | "Camden" | | 5 | "Seville" | | 6 | "London" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 143 | | glossingSentenceCount | 2 | | matches | | 0 | "looked like a forgotten maintenance entra" | | 1 | "looked like a human femur carved with run" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 2218 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 218 | | matches | (empty) | |
| 98.95% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 53 | | mean | 41.85 | | std | 20.77 | | cv | 0.496 | | sampleLengths | | 0 | 85 | | 1 | 58 | | 2 | 61 | | 3 | 78 | | 4 | 61 | | 5 | 60 | | 6 | 10 | | 7 | 51 | | 8 | 47 | | 9 | 96 | | 10 | 41 | | 11 | 64 | | 12 | 57 | | 13 | 53 | | 14 | 35 | | 15 | 5 | | 16 | 73 | | 17 | 56 | | 18 | 43 | | 19 | 43 | | 20 | 8 | | 21 | 63 | | 22 | 49 | | 23 | 31 | | 24 | 42 | | 25 | 24 | | 26 | 37 | | 27 | 52 | | 28 | 21 | | 29 | 22 | | 30 | 47 | | 31 | 33 | | 32 | 43 | | 33 | 26 | | 34 | 16 | | 35 | 19 | | 36 | 55 | | 37 | 42 | | 38 | 16 | | 39 | 49 | | 40 | 64 | | 41 | 43 | | 42 | 12 | | 43 | 50 | | 44 | 29 | | 45 | 12 | | 46 | 54 | | 47 | 10 | | 48 | 41 | | 49 | 38 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 208 | | matches | | 0 | "been widened" | | 1 | "been made" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 357 | | matches | (empty) | |
| 38.01% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 14 | | semicolonCount | 0 | | flaggedSentences | 8 | | totalSentences | 218 | | ratio | 0.037 | | matches | | 0 | "Up ahead, the suspect—a lean figure in a hooded jacket—darted between clusters of late-night revellers spilling out of pubs." | | 1 | "Herrera linked to the clique—the loose network of supernatural operators she’d been building a case against for months." | | 2 | "Creatures—things that looked almost human but weren’t—haggled over vials of glowing liquid and artefacts that hummed with power." | | 3 | "There—Herrera’s hooded jacket disappearing behind a stall selling caged sprites that buzzed angrily against their bars." | | 4 | "A creature that might once have been human lay sprawled on a table while Tomás Herrera—because of course it was him—worked on a wound that wept black ichor instead of blood." | | 5 | "Around them, armed guards—hulking things with horns—eyed her with open hostility." | | 6 | "Its eyes—vertical slits—fixed on her." | | 7 | "Whatever waited at the end of this tunnel—answers about Morris, proof against the clique, or something far worse—she would face it." |
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| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 2051 | | adjectiveStacks | 1 | | stackExamples | | 0 | "seedier, graffiti-tagged shutters" |
| | adverbCount | 63 | | adverbRatio | 0.030716723549488054 | | lyAdverbCount | 22 | | lyAdverbRatio | 0.010726474890297415 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 218 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 218 | | mean | 10.17 | | std | 6.6 | | cv | 0.649 | | sampleLengths | | 0 | 15 | | 1 | 12 | | 2 | 13 | | 3 | 19 | | 4 | 2 | | 5 | 24 | | 6 | 10 | | 7 | 7 | | 8 | 4 | | 9 | 14 | | 10 | 23 | | 11 | 9 | | 12 | 10 | | 13 | 17 | | 14 | 4 | | 15 | 1 | | 16 | 6 | | 17 | 14 | | 18 | 13 | | 19 | 7 | | 20 | 14 | | 21 | 13 | | 22 | 4 | | 23 | 2 | | 24 | 8 | | 25 | 17 | | 26 | 9 | | 27 | 10 | | 28 | 7 | | 29 | 5 | | 30 | 18 | | 31 | 12 | | 32 | 3 | | 33 | 19 | | 34 | 14 | | 35 | 7 | | 36 | 4 | | 37 | 6 | | 38 | 7 | | 39 | 10 | | 40 | 5 | | 41 | 5 | | 42 | 11 | | 43 | 10 | | 44 | 15 | | 45 | 4 | | 46 | 1 | | 47 | 9 | | 48 | 9 | | 49 | 11 |
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| 63.15% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 4 | | diversityRatio | 0.38990825688073394 | | totalSentences | 218 | | uniqueOpeners | 85 | |
| 87.72% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 5 | | totalSentences | 190 | | matches | | 0 | "Too many civilians." | | 1 | "Too many unknowns." | | 2 | "Only then did he turn." | | 3 | "Then she thought of the" | | 4 | "Then he spoke, words careful" |
| | ratio | 0.026 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 47 | | totalSentences | 190 | | matches | | 0 | "Her boots splashed through puddles" | | 1 | "She’d clocked him leaving The" | | 2 | "He vaulted a low barrier" | | 3 | "She slipped once, catching herself" | | 4 | "She wasn’t about to lose" | | 5 | "He clutched his left forearm," | | 6 | "She’d read his file." | | 7 | "He cut left toward Camden," | | 8 | "She radioed her location anyway," | | 9 | "She ignored it and descended." | | 10 | "She nudged the door wider" | | 11 | "She’d heard rumours during the" | | 12 | "She plunged in after him," | | 13 | "Her bearing stayed rigid, jaw" | | 14 | "She kept moving, eyes locked" | | 15 | "She ignored him and pressed" | | 16 | "Her boots squelched." | | 17 | "He glanced back for the" | | 18 | "Their eyes met across twenty" | | 19 | "His warm brown gaze held" |
| | ratio | 0.247 | |
| 52.11% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 155 | | totalSentences | 190 | | matches | | 0 | "Detective Harlow Quinn gripped the" | | 1 | "Her boots splashed through puddles" | | 2 | "She’d clocked him leaving The" | | 3 | "Quinn shouted, her voice cutting" | | 4 | "The words dissolved into the" | | 5 | "Herrera didn’t glance back." | | 6 | "He vaulted a low barrier" | | 7 | "Quinn cursed under her breath" | | 8 | "The alley narrowed, brick walls" | | 9 | "Water cascaded from overflowing gutters," | | 10 | "She slipped once, catching herself" | | 11 | "The leather strap held." | | 12 | "That watch had belonged to" | | 13 | "She wasn’t about to lose" | | 14 | "Herrera emerged onto Charing Cross" | | 15 | "Quinn followed, breath burning in" | | 16 | "The suspect’s curly dark hair" | | 17 | "He clutched his left forearm," | | 18 | "She’d read his file." | | 19 | "Things that had killed her" |
| | ratio | 0.816 | |
| 78.95% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 3 | | totalSentences | 190 | | matches | | 0 | "If she could flip him," | | 1 | "Now it pulsed with illicit" | | 2 | "Now the real danger began." |
| | ratio | 0.016 | |
| 54.57% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 89 | | technicalSentenceCount | 11 | | matches | | 0 | "Her boots splashed through puddles that reflected the garish glow of neon signs." | | 1 | "She wasn’t about to lose it chasing some off-the-books medic who patched up criminals." | | 2 | "Herrera emerged onto Charing Cross Road, weaving through taxis that honked in protest." | | 3 | "The hidden passage opened into a vast chamber that had once been an abandoned Tube platform." | | 4 | "Creatures—things that looked almost human but weren’t—haggled over vials of glowing liquid and artefacts that hummed with power." | | 5 | "There—Herrera’s hooded jacket disappearing behind a stall selling caged sprites that buzzed angrily against their bars." | | 6 | "She plunged in after him, shoulders brushing against a hooded figure who snarled something in what might have been ancient Greek." | | 7 | "Herrera ducked under a rope barrier marked with symbols that made her eyes water." | | 8 | "These ones dealt in darker wares: banned alchemical substances in stoppered crystal bottles, scrolls that bled when touched, information traded in whispers that…" | | 9 | "It exploded into brilliant green smoke that stung her eyes and burned her throat." | | 10 | "Of the unexplained circumstances that had left her partner broken on a warehouse floor while something ancient laughed in the rafters." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 7 | | uselessAdditionCount | 2 | | matches | | 0 | "Quinn shouted, her voice cutting through the storm" | | 1 | "she called, voice steady despite the adrenaline surge" |
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| 91.18% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 4 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 17 | | tagDensity | 0.235 | | leniency | 0.471 | | rawRatio | 0.25 | | effectiveRatio | 0.118 | |