| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 3 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 7 | | tagDensity | 0.429 | | leniency | 0.857 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1294 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 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) | |
| 11.13% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1294 | | totalAiIsms | 23 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | | | 13 | | | 14 | | | 15 | | | 16 | | | 17 | | | 18 | |
| | highlights | | 0 | "jaw clenched" | | 1 | "pumping" | | 2 | "glinting" | | 3 | "loomed" | | 4 | "electric" | | 5 | "pulse" | | 6 | "throbbed" | | 7 | "etched" | | 8 | "tracing" | | 9 | "echoed" | | 10 | "footsteps" | | 11 | "weight" | | 12 | "velvet" | | 13 | "echoes" | | 14 | "maw" | | 15 | "pounding" | | 16 | "echo" | | 17 | "pulsed" | | 18 | "lilt" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 2 | | maxInWindow | 1 | | found | | 0 | | label | "clenched jaw/fists" | | count | 1 |
| | 1 | | label | "jaw/fists clenched" | | count | 1 |
|
| | highlights | | 0 | "clenched fist" | | 1 | "jaw clenched" |
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| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 149 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 0 | | narrationSentences | 149 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 154 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 22 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 5 | | markdownWords | 20 | | totalWords | 1242 | | ratio | 0.016 | | matches | | 0 | "Tomás Herrera. Off-books medic. Clique hanger-on." | | 1 | "Partner's ghost whispers your name, Tommy." | | 2 | "Veil Market." | | 3 | "Fed. Stinks of law." | | 4 | "Fresh meat." |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 5 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 56 | | wordCount | 1188 | | uniqueNames | 25 | | maxNameDensity | 0.84 | | worstName | "Herrera" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Quinn" | | discoveredNames | | Quinn | 7 | | Greek | 1 | | Street | 2 | | Saint | 1 | | Christopher | 1 | | Herrera | 10 | | Raven | 1 | | Nest | 3 | | Charing | 1 | | Cross | 1 | | Road | 2 | | Pavement | 1 | | Tottenham | 1 | | Court | 1 | | Morris | 4 | | Goodge | 1 | | Rumours | 1 | | Market | 2 | | Olives | 1 | | Andalusian | 1 | | Door | 3 | | Glock | 1 | | Rain | 3 | | Military | 3 | | Bone | 3 |
| | persons | | 0 | "Quinn" | | 1 | "Saint" | | 2 | "Christopher" | | 3 | "Herrera" | | 4 | "Pavement" | | 5 | "Morris" | | 6 | "Market" | | 7 | "Door" | | 8 | "Rain" | | 9 | "Military" |
| | places | | 0 | "Greek" | | 1 | "Street" | | 2 | "Raven" | | 3 | "Nest" | | 4 | "Charing" | | 5 | "Cross" | | 6 | "Road" | | 7 | "Tottenham" | | 8 | "Court" | | 9 | "Goodge" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 99 | | glossingSentenceCount | 1 | | matches | | 0 | "smelled like human vellum, alchemical powd" |
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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 | 1242 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 154 | | matches | | 0 | "haunted that hesitation" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 39 | | mean | 31.85 | | std | 19.43 | | cv | 0.61 | | sampleLengths | | 0 | 63 | | 1 | 69 | | 2 | 15 | | 3 | 56 | | 4 | 60 | | 5 | 57 | | 6 | 54 | | 7 | 43 | | 8 | 49 | | 9 | 60 | | 10 | 31 | | 11 | 24 | | 12 | 15 | | 13 | 48 | | 14 | 50 | | 15 | 44 | | 16 | 49 | | 17 | 64 | | 18 | 25 | | 19 | 35 | | 20 | 40 | | 21 | 29 | | 22 | 14 | | 23 | 9 | | 24 | 1 | | 25 | 9 | | 26 | 13 | | 27 | 29 | | 28 | 21 | | 29 | 31 | | 30 | 17 | | 31 | 17 | | 32 | 17 | | 33 | 10 | | 34 | 22 | | 35 | 13 | | 36 | 4 | | 37 | 29 | | 38 | 6 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 149 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 260 | | matches | (empty) | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 13 | | semicolonCount | 1 | | flaggedSentences | 14 | | totalSentences | 154 | | ratio | 0.091 | | matches | | 0 | "She dodged the bow wave, lungs burning, glimpsed his profile—warm brown eyes wide in the dash." | | 1 | "The air thickened, ozone bite sharpening to something feral—herbs?" | | 2 | "Bone token flashed in his fist—yellowed shard, etched sigils glowing faint phosphorescent." | | 3 | "Footsteps splashed distant on street level—night revellers?" | | 4 | "Herrera's medallion had swung free in the dash; she'd seen the chain snag." | | 5 | "Morris's file burned in her mind—unexplained evisceration, symbols like claws on his torso." | | 6 | "Echoes multiplied—bargains hissed in tongues she half-knew from cold cases." | | 7 | "A merchant's gaze snagged hers—yellow slit-pupils in a face too smooth for human." | | 8 | "Exchanged for a satchel slung quick under jacket—potion vials?" | | 9 | "Voices faded behind, replaced by drip-echo and distant rumble—ghost trains?" | | 10 | "Satchel slipped open an inch—glass glinted inside, liquids swirling shadow." | | 11 | "Howl ripped from beyond—wind?" | | 12 | "Morris's eviscerated grin flashed—supernatural claws." | | 13 | "Something seized her ankle from shadows—taloned grip, scales rasping leather." |
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| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 119 | | adjectiveStacks | 1 | | stackExamples | | 0 | "suspect twisted ahead, his" |
| | adverbCount | 1 | | adverbRatio | 0.008403361344537815 | | lyAdverbCount | 1 | | lyAdverbRatio | 0.008403361344537815 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 154 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 154 | | mean | 8.06 | | std | 5.06 | | cv | 0.627 | | sampleLengths | | 0 | 14 | | 1 | 21 | | 2 | 8 | | 3 | 20 | | 4 | 7 | | 5 | 12 | | 6 | 15 | | 7 | 2 | | 8 | 2 | | 9 | 21 | | 10 | 10 | | 11 | 15 | | 12 | 4 | | 13 | 9 | | 14 | 20 | | 15 | 9 | | 16 | 14 | | 17 | 6 | | 18 | 22 | | 19 | 16 | | 20 | 3 | | 21 | 1 | | 22 | 6 | | 23 | 6 | | 24 | 5 | | 25 | 14 | | 26 | 11 | | 27 | 1 | | 28 | 17 | | 29 | 1 | | 30 | 8 | | 31 | 6 | | 32 | 4 | | 33 | 16 | | 34 | 15 | | 35 | 13 | | 36 | 14 | | 37 | 13 | | 38 | 9 | | 39 | 1 | | 40 | 6 | | 41 | 14 | | 42 | 15 | | 43 | 12 | | 44 | 8 | | 45 | 6 | | 46 | 9 | | 47 | 12 | | 48 | 9 | | 49 | 8 |
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| 100.00% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 0 | | diversityRatio | 0.6233766233766234 | | totalSentences | 154 | | uniqueOpeners | 96 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 124 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 29 | | totalSentences | 124 | | matches | | 0 | "He vaulted a low fence" | | 1 | "She gritted her teeth, sharp" | | 2 | "His hand had dipped into" | | 3 | "Her shout sliced the downpour," | | 4 | "He didn't break stride." | | 5 | "She followed, coat flapping heavy," | | 6 | "She dodged the bow wave," | | 7 | "He cut north, towards Tottenham" | | 8 | "She gained ground, fingers brushing" | | 9 | "He glanced back once, medallion" | | 10 | "He sprinted past a tattoo" | | 11 | "He yanked it wider, frame" | | 12 | "He dropped through the gap," | | 13 | "She thumbed it anyway." | | 14 | "Her watch hand swept past" | | 15 | "She crouched, salt-and-pepper hair spiking" | | 16 | "She knew better." | | 17 | "She wedged through, boots finding" | | 18 | "He shoved through, medallion tucked" | | 19 | "He proffered a mirror shard," |
| | ratio | 0.234 | |
| 44.68% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 103 | | totalSentences | 124 | | matches | | 0 | "Harlow Quinn's boots skidded on" | | 1 | "The suspect twisted ahead, his" | | 2 | "Rain sheeted off his jacket" | | 3 | "He vaulted a low fence" | | 4 | "She gritted her teeth, sharp" | | 5 | "Military bearing propelled her forward," | | 6 | "The worn leather watch on" | | 7 | "Clique hanger-on.* She'd clocked him" | | 8 | "His hand had dipped into" | | 9 | "Her shout sliced the downpour," | | 10 | "He didn't break stride." | | 11 | "Soho's back alleys choked tight," | | 12 | "She followed, coat flapping heavy," | | 13 | "Copper tang stung nostrils, mingled" | | 14 | "Herrera burst onto Charing Cross" | | 15 | "Horns blared as he wove" | | 16 | "She dodged the bow wave," | | 17 | "*Partner's ghost whispers your name," | | 18 | "Pavement gleamed oil-slick under headlights." | | 19 | "He cut north, towards Tottenham" |
| | ratio | 0.831 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 124 | | matches | (empty) | | ratio | 0 | |
| 91.84% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 56 | | technicalSentenceCount | 4 | | matches | | 0 | "He cut north, towards Tottenham Court Road tube, feet slapping puddles that erupted knee-high." | | 1 | "Camden's fringe loomed now, market stalls shuttered under awnings that funnelled rain in curtains." | | 2 | "A hag with gill-slits peddled eel-skin gloves that whispered secrets." | | 3 | "Herrera melted into the throng, shoulder bumping a stall that spilled iridescent scales like coins." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 3 | | uselessAdditionCount | 1 | | matches | | 0 | "Military bearing, legs pumping with eighteen years' drill precision" |
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| 7.14% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 1 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 7 | | tagDensity | 0.143 | | leniency | 0.286 | | rawRatio | 1 | | effectiveRatio | 0.286 | |