| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 2 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 12 | | tagDensity | 0.167 | | leniency | 0.333 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1284 | | 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) | |
| 22.12% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1284 | | totalAiIsms | 20 | | found | | | highlights | | 0 | "pulse" | | 1 | "reminder" | | 2 | "footsteps" | | 3 | "echoed" | | 4 | "pounding" | | 5 | "weight" | | 6 | "clandestine" | | 7 | "gloom" | | 8 | "echoes" | | 9 | "etched" | | 10 | "glinting" | | 11 | "hulking" | | 12 | "pulsed" |
| |
| 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 | 0 | | narrationSentences | 105 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 0 | | narrationSentences | 105 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 114 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 34 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1262 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 4 | | unquotedAttributions | 0 | | matches | (empty) | |
| 94.40% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 56 | | wordCount | 1169 | | uniqueNames | 24 | | maxNameDensity | 1.11 | | worstName | "Quinn" | | maxWindowNameDensity | 2 | | worstWindowName | "Quinn" | | discoveredNames | | Soho | 2 | | Harlow | 1 | | Quinn | 13 | | Tomás | 11 | | Herrera | 3 | | Dean | 1 | | Street | 1 | | Whitechapel | 1 | | Raven | 1 | | Nest | 1 | | Veil | 2 | | Market | 3 | | Charing | 1 | | Cross | 1 | | Road | 1 | | Traffic | 1 | | Saint | 1 | | Christopher | 1 | | Tube | 2 | | Camden | 2 | | Morris | 3 | | Northern | 1 | | Line | 1 | | Dreams | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Tomás" | | 3 | "Herrera" | | 4 | "Raven" | | 5 | "Market" | | 6 | "Traffic" | | 7 | "Saint" | | 8 | "Christopher" | | 9 | "Tube" | | 10 | "Camden" | | 11 | "Morris" |
| | places | | 0 | "Soho" | | 1 | "Dean" | | 2 | "Street" | | 3 | "Whitechapel" | | 4 | "Charing" | | 5 | "Cross" | | 6 | "Road" |
| | globalScore | 0.944 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 87 | | glossingSentenceCount | 1 | | matches | | 0 | "looked like liquid starlight" |
| |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1262 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 114 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 37 | | mean | 34.11 | | std | 19.12 | | cv | 0.561 | | sampleLengths | | 0 | 85 | | 1 | 47 | | 2 | 6 | | 3 | 81 | | 4 | 50 | | 5 | 12 | | 6 | 39 | | 7 | 51 | | 8 | 61 | | 9 | 45 | | 10 | 17 | | 11 | 54 | | 12 | 42 | | 13 | 16 | | 14 | 40 | | 15 | 44 | | 16 | 25 | | 17 | 57 | | 18 | 67 | | 19 | 34 | | 20 | 28 | | 21 | 30 | | 22 | 17 | | 23 | 22 | | 24 | 36 | | 25 | 27 | | 26 | 10 | | 27 | 29 | | 28 | 34 | | 29 | 27 | | 30 | 12 | | 31 | 17 | | 32 | 20 | | 33 | 22 | | 34 | 18 | | 35 | 19 | | 36 | 21 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 105 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 238 | | matches | (empty) | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 18 | | semicolonCount | 4 | | flaggedSentences | 20 | | totalSentences | 114 | | ratio | 0.175 | | matches | | 0 | "The suspect—Tomás Herrera, the ghost in her files, the off-the-books healer with ties to every shadow operation in the city—bolted ahead, his short curly hair plastered flat under the streetlights." | | 1 | "The Raven's Nest was too far behind; he'd lost the clique there in the hidden back room, maps and photos blurring as Quinn burst through the door." | | 2 | "Now, the Veil Market called—his only shot at vanishing." | | 3 | "Puddles reflected garish signs—porn shops, kebab joints shuttered for the night." | | 4 | "Tomás's lungs burned; paramedic days had honed his stamina, but fear added weight." | | 5 | "Full moon tomorrow; it wouldn't shift yet." | | 6 | "She remembered her partner, DS Morris, vanishing into fog three years back—supernatural whispers she'd chased ever since." | | 7 | "The stairs led to an old service door, rusted and chained—but Tomás knew the trick." | | 8 | "The air shifted at the bottom—thicker, laced with earth and something metallic, like blood under soil." | | 9 | "But graffiti marred the walls—symbols she'd seen in case files, swirling runes that made her skin crawl." | | 10 | "Stalls emerged from the shadows—ramshackle booths of wood and canvas, lit by lanterns that cast elongated shadows." | | 11 | "A vendor with eyes like polished obsidian hawked jars of swirling mist—\"Dreams bottled fresh, guv'nor?\"—while another bartered information, voice a rasp." | | 12 | "Suspicious glances turned her way; hands slipped to pockets, concealing tokens like Herrera's bone key." | | 13 | "No going back up without him—backup wouldn't know this warren." | | 14 | "There—Tomás, elbowing through a throng near a central archway." | | 15 | "One wrong move, and she'd end up like Morris—gone, unexplained." | | 16 | "He bolted right, into a side tunnel lined with alcoves—private dealings, curtains drawn on moans and negotiations." | | 17 | "She cornered him in a dead-end alcove, crates stacked high with contraband—banned potions, herbs that whispered when touched." | | 18 | "Figures emerged—market enforcers, eyes glowing faint red, clubs etched with runes." | | 19 | "She weighed it—duty against the unknown pull, the shadows that took Morris." |
| |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1191 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 22 | | adverbRatio | 0.018471872376154493 | | lyAdverbCount | 4 | | lyAdverbRatio | 0.0033585222502099076 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 114 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 114 | | mean | 11.07 | | std | 5.59 | | cv | 0.505 | | sampleLengths | | 0 | 13 | | 1 | 21 | | 2 | 30 | | 3 | 21 | | 4 | 17 | | 5 | 11 | | 6 | 9 | | 7 | 10 | | 8 | 2 | | 9 | 4 | | 10 | 14 | | 11 | 19 | | 12 | 12 | | 13 | 27 | | 14 | 9 | | 15 | 12 | | 16 | 5 | | 17 | 13 | | 18 | 20 | | 19 | 12 | | 20 | 8 | | 21 | 17 | | 22 | 14 | | 23 | 12 | | 24 | 19 | | 25 | 12 | | 26 | 8 | | 27 | 14 | | 28 | 11 | | 29 | 13 | | 30 | 16 | | 31 | 7 | | 32 | 11 | | 33 | 17 | | 34 | 3 | | 35 | 14 | | 36 | 15 | | 37 | 2 | | 38 | 3 | | 39 | 22 | | 40 | 15 | | 41 | 14 | | 42 | 7 | | 43 | 10 | | 44 | 6 | | 45 | 10 | | 46 | 9 | | 47 | 2 | | 48 | 1 | | 49 | 13 |
| |
| 64.04% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 2 | | diversityRatio | 0.39473684210526316 | | totalSentences | 114 | | uniqueOpeners | 45 | |
| 32.68% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 102 | | matches | | 0 | "Instead, he slipped down a" |
| | ratio | 0.01 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 29 | | totalSentences | 102 | | matches | | 0 | "He glanced back once, warm" | | 1 | "She radioed it in, voice" | | 2 | "He clutched the bone token" | | 3 | "He cut left, weaving past" | | 4 | "She spotted him weaving toward" | | 5 | "Her shout sliced the night," | | 6 | "Her brown eyes locked on" | | 7 | "She wiped it away, tasting" | | 8 | "He led her north now," | | 9 | "He needed the Tube entrance," | | 10 | "She remembered her partner, DS" | | 11 | "His name popped in reports" | | 12 | "She used the alias from" | | 13 | "He didn't turn." | | 14 | "He yanked the chain, a" | | 15 | "His shadow swallowed the gloom" | | 16 | "She gripped the rail, cold" | | 17 | "She descended, each step groaning" | | 18 | "She'd heard rumors in vice," | | 19 | "He flashed his bone token" |
| | ratio | 0.284 | |
| 38.43% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 86 | | totalSentences | 102 | | matches | | 0 | "Detective Harlow Quinn sprinted through" | | 1 | "The suspect—Tomás Herrera, the ghost" | | 2 | "He glanced back once, warm" | | 3 | "Quinn's breath came in sharp" | | 4 | "She radioed it in, voice" | | 5 | "The storm drowned everything." | | 6 | "Tomás vaulted a low fence," | | 7 | "The scar on his left" | | 8 | "He clutched the bone token" | | 9 | "The Raven's Nest was too" | | 10 | "He cut left, weaving past" | | 11 | "Footsteps echoed behind him, relentless." | | 12 | "Quinn exploded from the alley" | | 13 | "She spotted him weaving toward" | | 14 | "Her shout sliced the night," | | 15 | "Traffic snarled ahead, horns blaring" | | 16 | "Tomás darted across, tires screeching" | | 17 | "A lorry's headlights caught him" | | 18 | "Quinn followed without hesitation, leaping" | | 19 | "The driver swore, fist pounding" |
| | ratio | 0.843 | |
| 49.02% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 102 | | matches | | 0 | "Now, the Veil Market called—his" |
| | ratio | 0.01 | |
| 47.62% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 60 | | technicalSentenceCount | 8 | | matches | | 0 | "Detective Harlow Quinn sprinted through the downpour, her boots splashing arcs of water that soaked her trousers up to the knees." | | 1 | "Tomás vaulted a low fence, landing in a puddle that sprayed his olive skin." | | 2 | "He cut left, weaving past overflowing bins that reeked of rotting takeaway." | | 3 | "His name popped in reports on unexplained wounds, patients who walked away from morgues." | | 4 | "Instead, he slipped down a flight of metal stairs beside a derelict newsstand, the kind that dotted the city like forgotten teeth." | | 5 | "Stalls emerged from the shadows—ramshackle booths of wood and canvas, lit by lanterns that cast elongated shadows." | | 6 | "Figures huddled in cloaks, haggling over vials that glowed faint blue, amulets etched with forbidden sigils." | | 7 | "She cornered him in a dead-end alcove, crates stacked high with contraband—banned potions, herbs that whispered when touched." |
| |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 2 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 66.67% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 1 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 12 | | tagDensity | 0.083 | | leniency | 0.167 | | rawRatio | 1 | | effectiveRatio | 0.167 | |