| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 12 | | adverbTagCount | 1 | | adverbTags | | 0 | "Herrera's voice echoed back [back]" |
| | dialogueSentences | 16 | | tagDensity | 0.75 | | leniency | 1 | | rawRatio | 0.083 | | effectiveRatio | 0.083 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1296 | | 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) | |
| 11.27% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1296 | | totalAiIsms | 23 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | | | 13 | | | 14 | | | 15 | | | 16 | | | 17 | | | 18 | | | 19 | | | 20 | |
| | highlights | | 0 | "pounding" | | 1 | "streaming" | | 2 | "reminder" | | 3 | "echoes" | | 4 | "gleaming" | | 5 | "raced" | | 6 | "depths" | | 7 | "glinting" | | 8 | "racing" | | 9 | "echoed" | | 10 | "footsteps" | | 11 | "gloom" | | 12 | "flickered" | | 13 | "measured" | | 14 | "loomed" | | 15 | "standard" | | 16 | "potential" | | 17 | "etched" | | 18 | "unravel" | | 19 | "pulse" | | 20 | "scanning" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 0 | | maxInWindow | 0 | | found | (empty) | | highlights | (empty) | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 1 | | narrationSentences | 50 | | matches | | |
| 85.71% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 1 | | narrationSentences | 50 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 51 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 82 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1278 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 8 | | unquotedAttributions | 0 | | matches | (empty) | |
| 82.32% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 49 | | wordCount | 1182 | | uniqueNames | 23 | | maxNameDensity | 1.35 | | worstName | "Herrera" | | maxWindowNameDensity | 2 | | worstWindowName | "Herrera" | | discoveredNames | | Soho | 1 | | Harlow | 1 | | Quinn | 8 | | Herrera | 16 | | Morris | 2 | | London | 1 | | Raven | 1 | | Nest | 1 | | Wardour | 1 | | Street | 1 | | Saint | 1 | | Christopher | 1 | | Shaftesbury | 1 | | Avenue | 1 | | Circus | 1 | | Camden | 3 | | Euston | 1 | | Road | 1 | | Underground | 2 | | Town | 1 | | Tube | 1 | | Veil | 1 | | Market | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Herrera" | | 3 | "Morris" | | 4 | "Raven" | | 5 | "Saint" | | 6 | "Christopher" | | 7 | "Circus" | | 8 | "Market" |
| | places | | 0 | "Soho" | | 1 | "London" | | 2 | "Wardour" | | 3 | "Street" | | 4 | "Shaftesbury" | | 5 | "Avenue" | | 6 | "Camden" | | 7 | "Euston" | | 8 | "Road" | | 9 | "Underground" | | 10 | "Town" |
| | globalScore | 0.823 | | windowScore | 1 | |
| 0.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 44 | | glossingSentenceCount | 3 | | matches | | 0 | "looked like an abandoned Tube station ben" | | 1 | "tattoos that seemed to writhe, leaned forward" | | 2 | "looked like forbidden herbs and glowing c" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.782 | | wordCount | 1278 | | matches | | 0 | "not the sterile white of station lights, but something warmer, erratic" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 51 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 32 | | mean | 39.94 | | std | 24.27 | | cv | 0.608 | | sampleLengths | | 0 | 80 | | 1 | 121 | | 2 | 37 | | 3 | 84 | | 4 | 53 | | 5 | 40 | | 6 | 11 | | 7 | 21 | | 8 | 62 | | 9 | 13 | | 10 | 9 | | 11 | 51 | | 12 | 39 | | 13 | 41 | | 14 | 20 | | 15 | 10 | | 16 | 40 | | 17 | 30 | | 18 | 53 | | 19 | 16 | | 20 | 40 | | 21 | 21 | | 22 | 41 | | 23 | 36 | | 24 | 78 | | 25 | 33 | | 26 | 42 | | 27 | 42 | | 28 | 23 | | 29 | 32 | | 30 | 45 | | 31 | 14 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 50 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 218 | | matches | (empty) | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 10 | | semicolonCount | 0 | | flaggedSentences | 9 | | totalSentences | 51 | | ratio | 0.176 | | matches | | 0 | "Eighteen years on the force, and this chase felt personal—echoes of DS Morris's unexplained death three years back, the case that left her with more questions than closures." | | 1 | "The words stung, fueling her pursuit. She leaped over a puddle, her coat flapping like wings. They raced north, the city blurring into a frenzy of lights and shadows. Piccadilly Circus flashed by, its screens bleeding colors into the rain. Herrera cut through side streets, heading toward Camden, his path deliberate now, not random. She clocked it— he aimed for something specific." | | 2 | "Quinn hesitated for a split second—protocol screamed for caution—but momentum carried her down the steps. The air grew thick, damp with the scent of wet concrete and ozone. Fluorescent lights buzzed overhead, casting harsh shadows on tiled walls scarred by graffiti." | | 3 | "She dropped down, gravel crunching under her boots. The tunnel narrowed, pipes dripping condensation that mixed with the rain still trickling from above. Her flashlight beam sliced through the gloom, catching glimpses of rusted metal and forgotten debris. Ahead, a faint glow flickered—not the sterile white of station lights, but something warmer, erratic." | | 4 | "\"Try me,\" she shot back, her words bouncing off the walls. She advanced, each step measured, her military bearing keeping her steady. The tunnel bent, and the air shifted—thicker, laced with incense and something metallic, like blood or old coins." | | 5 | "She paused, breath steady despite the chase. This wasn't the standard Underground. Her instincts screamed trap—unfamiliar territory, potential hostiles. But Herrera's trail led here, and with it, answers to the shadows that had claimed her partner." | | 6 | "The Veil Market. Whispers from informants had mentioned it—a supernatural black market that shifted every full moon, entry by bone token only. Banned substances, enchanted goods, information that could unravel cases like Morris's." | | 7 | "Herrera melted into the crowd, his dark curls bobbing among hooded figures and beings that didn't look entirely human—eyes too bright, skin shimmering unnaturally. He flashed something small and white at a gatekeeper, a bone token, and slipped through an inner barrier." | | 8 | "Decision time. Follow, and step into the unknown—risk everything on a hunch that this market held the key to the clique's secrets. Or pull back, call it in, lose the trail forever." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 355 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 11 | | adverbRatio | 0.030985915492957747 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.014084507042253521 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 51 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 51 | | mean | 25.06 | | std | 17.08 | | cv | 0.682 | | sampleLengths | | 0 | 19 | | 1 | 15 | | 2 | 20 | | 3 | 26 | | 4 | 21 | | 5 | 16 | | 6 | 28 | | 7 | 8 | | 8 | 1 | | 9 | 12 | | 10 | 35 | | 11 | 18 | | 12 | 19 | | 13 | 12 | | 14 | 20 | | 15 | 28 | | 16 | 24 | | 17 | 53 | | 18 | 40 | | 19 | 9 | | 20 | 2 | | 21 | 17 | | 22 | 4 | | 23 | 62 | | 24 | 10 | | 25 | 3 | | 26 | 9 | | 27 | 51 | | 28 | 39 | | 29 | 41 | | 30 | 20 | | 31 | 9 | | 32 | 1 | | 33 | 40 | | 34 | 30 | | 35 | 53 | | 36 | 8 | | 37 | 8 | | 38 | 40 | | 39 | 21 | | 40 | 41 | | 41 | 36 | | 42 | 78 | | 43 | 33 | | 44 | 42 | | 45 | 38 | | 46 | 4 | | 47 | 23 | | 48 | 32 | | 49 | 45 |
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| 83.01% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 1 | | diversityRatio | 0.5098039215686274 | | totalSentences | 51 | | uniqueOpeners | 26 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 47 | | matches | (empty) | | ratio | 0 | |
| 66.81% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 18 | | totalSentences | 47 | | matches | | 0 | "She pushed harder, her sharp" | | 1 | "Her voice cut through the" | | 2 | "He veered left into an" | | 3 | "He skidded on a slick" | | 4 | "She closed the gap, lungs" | | 5 | "He burst onto Shaftesbury Avenue," | | 6 | "He shot her a look" | | 7 | "Her radio crackled in her" | | 8 | "she muttered, silencing it. This" | | 9 | "He broke free, darting down" | | 10 | "She followed, flashing her badge" | | 11 | "She dropped down, gravel crunching" | | 12 | "You have no idea what" | | 13 | "she shot back, her words" | | 14 | "She paused, breath steady despite" | | 15 | "She ignored him, scanning for" | | 16 | "Her fingers tightened on the" | | 17 | "She took a breath, weighing" |
| | ratio | 0.383 | |
| 13.19% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 42 | | totalSentences | 47 | | matches | | 0 | "Detective Harlow Quinn sprinted through" | | 1 | "Tomás Herrera, the former paramedic" | | 2 | "She pushed harder, her sharp" | | 3 | "The worn leather watch on" | | 4 | "Tonight, she'd caught him slipping" | | 5 | "Her voice cut through the" | | 6 | "He veered left into an" | | 7 | "Quinn vaulted the debris, her" | | 8 | "The alley narrowed, garbage bags" | | 9 | "He skidded on a slick" | | 10 | "That Saint Christopher medallion bounced" | | 11 | "She closed the gap, lungs" | | 12 | "He burst onto Shaftesbury Avenue," | | 13 | "Quinn followed, shoving past a" | | 14 | "He shot her a look" | | 15 | "This isn't your" | | 16 | "The words stung, fueling her" | | 17 | "Her radio crackled in her" | | 18 | "she muttered, silencing it. This" | | 19 | "The rain intensified as they" |
| | ratio | 0.894 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 47 | | matches | (empty) | | ratio | 0 | |
| 0.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 32 | | technicalSentenceCount | 13 | | matches | | 0 | "Rain hammered the pavement, turning Soho's narrow streets into slick mirrors that reflected the garish glow of neon signs." | | 1 | "Ahead, the suspect ducked under a flickering streetlamp, his silhouette cutting through the storm like a shadow fleeing the light." | | 2 | "Eighteen years on the force, and this chase felt personal—echoes of DS Morris's unexplained death three years back, the case that left her with more questions t…" | | 3 | "Tonight, she'd caught him slipping out of The Raven's Nest, that dimly lit bar with its green neon sign and walls plastered in old maps, clutching a satchel tha…" | | 4 | "He burst onto Shaftesbury Avenue, weaving between honking taxis and umbrellas clutched by late-night crowds. A double-decker bus lumbered past, its headlights c…" | | 5 | "The words stung, fueling her pursuit. She leaped over a puddle, her coat flapping like wings. They raced north, the city blurring into a frenzy of lights and sh…" | | 6 | "The rain intensified as they hit Euston Road, thunder rumbling overhead like a warning. Herrera slipped into a throng of people spilling from a pub, using them …" | | 7 | "Herrera vaulted the turnstile, his medallion glinting as he landed. Alarms blared, but he didn't stop, racing toward the platform." | | 8 | "The platform echoed with the whine of departing trains, wind tunneling through like a beast's breath. Herrera leaped onto the tracks, a reckless move that had h…" | | 9 | "She dropped down, gravel crunching under her boots. The tunnel narrowed, pipes dripping condensation that mixed with the rain still trickling from above. Her fl…" | | 10 | "She paused, breath steady despite the chase. This wasn't the standard Underground. Her instincts screamed trap—unfamiliar territory, potential hostiles. But Her…" | | 11 | "The Veil Market. Whispers from informants had mentioned it—a supernatural black market that shifted every full moon, entry by bone token only. Banned substances…" | | 12 | "Herrera melted into the crowd, his dark curls bobbing among hooded figures and beings that didn't look entirely human—eyes too bright, skin shimmering unnatural…" |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 6 | | uselessAdditionCount | 2 | | matches | | 0 | "She closed, lungs burning, her 5'9" 5/9/2001, 12:00:00 AM | | 1 | "she shot back, her words bouncing off the walls" |
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| 87.50% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 1 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 16 | | tagDensity | 0.063 | | leniency | 0.125 | | rawRatio | 1 | | effectiveRatio | 0.125 | |