| 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 | |
| 93.38% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1510 | | totalAiIsmAdverbs | 2 | | found | | | highlights | | |
| 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) | |
| 50.33% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1510 | | totalAiIsms | 15 | | found | | | highlights | | 0 | "scanned" | | 1 | "tension" | | 2 | "navigating" | | 3 | "treacherous" | | 4 | "flickered" | | 5 | "pumping" | | 6 | "intricate" | | 7 | "silence" | | 8 | "vibrated" | | 9 | "coded" | | 10 | "porcelain" | | 11 | "scanning" | | 12 | "familiar" | | 13 | "lilt" |
| |
| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 1 |
|
| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 80 | | matches | (empty) | |
| 89.29% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 1 | | narrationSentences | 80 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 84 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 60 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1495 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 4 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 41 | | wordCount | 1404 | | uniqueNames | 20 | | maxNameDensity | 0.71 | | worstName | "Quinn" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Quinn" | | discoveredNames | | Detective | 1 | | Harlow | 1 | | Quinn | 10 | | Raven | 2 | | Nest | 2 | | London | 2 | | Herrera | 1 | | Seville | 2 | | Soho | 1 | | Wardour | 1 | | Street | 1 | | Tomás | 5 | | Camden | 2 | | Town | 1 | | Saint | 2 | | Christopher | 2 | | Morris | 2 | | Tube | 1 | | Veil | 1 | | Market | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Raven" | | 3 | "Nest" | | 4 | "Herrera" | | 5 | "Tomás" | | 6 | "Saint" | | 7 | "Christopher" | | 8 | "Morris" |
| | places | | 0 | "London" | | 1 | "Seville" | | 2 | "Soho" | | 3 | "Wardour" | | 4 | "Street" | | 5 | "Camden" | | 6 | "Town" | | 7 | "Market" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 61 | | glossingSentenceCount | 1 | | matches | | 0 | "looked like preserved screams" |
| |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.669 | | wordCount | 1495 | | matches | | 0 | "not away, but sideways, knocking over a crate of alchemical components as" |
| |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 84 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 29 | | mean | 51.55 | | std | 33.24 | | cv | 0.645 | | sampleLengths | | 0 | 107 | | 1 | 83 | | 2 | 15 | | 3 | 7 | | 4 | 105 | | 5 | 82 | | 6 | 106 | | 7 | 75 | | 8 | 35 | | 9 | 97 | | 10 | 63 | | 11 | 24 | | 12 | 11 | | 13 | 65 | | 14 | 30 | | 15 | 3 | | 16 | 100 | | 17 | 74 | | 18 | 4 | | 19 | 73 | | 20 | 31 | | 21 | 56 | | 22 | 18 | | 23 | 52 | | 24 | 13 | | 25 | 47 | | 26 | 34 | | 27 | 56 | | 28 | 29 |
| |
| 87.72% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 4 | | totalSentences | 80 | | matches | | 0 | "was compromised" | | 1 | "been broken" | | 2 | "being released" | | 3 | "were sold" |
| |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 3 | | totalVerbs | 221 | | matches | | 0 | "was vanishing" | | 1 | "was running" | | 2 | "was buying" |
| |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 15 | | semicolonCount | 0 | | flaggedSentences | 10 | | totalSentences | 84 | | ratio | 0.119 | | matches | | 0 | "Quinn pushed off from the alley wall, her boots—polished to a military shine that the rain immediately dulled—splashing through gutter water that reflected the neon and the headlights of passing black cabs." | | 1 | "He knew these streets—she’d watched him for six weeks, ever since the whispers had started circulating about a paramedic who treated patients no hospital would touch, who stitched wounds that shouldn’t have healed and set bones that had been broken by things that left no bruises." | | 2 | "He moved with surprising speed for a man carrying a case, his left forearm—bearing the pale, raised scar from an old knife attack—flashing as he reached into his jacket." | | 3 | "She raised her left wrist, checking the worn leather watch—the band dark with water, the face showing 11:47 PM." | | 4 | "She thought of Morris’s notes, the coded references to bone tokens and abandoned Tube stations, to a black market that relocated every full moon—which was tonight—selling enchanted goods and banned alchemical substances to creatures that wore human skin." | | 5 | "The stairs spiraled down, endless concrete steps slick with moisture and something else—a faint, phosphorescent residue that glowed faintly green in the dark." | | 6 | "Vendors—some human, some wearing masks of porcelain and bone—hawked their wares in voices that ranged from guttural to melodic." | | 7 | "His warm brown eyes widened, recognition dawning, and he moved—not away, but sideways, knocking over a crate of alchemical components as he reached for the case he’d been carrying." | | 8 | "She ducked, military reflexes taking over, and he broke free, sprinting toward a side tunnel that opened into the dark beyond the platform’s edge—a passage that hadn’t been there a moment before, the architecture of the place shifting like a living thing." | | 9 | "She checked her watch—11:58 PM—and followed him into the dark, her service weapon drawn, her heart hammering against her ribs as the tunnel swallowed her whole." |
| |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1429 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 21 | | adverbRatio | 0.01469559132260322 | | lyAdverbCount | 7 | | lyAdverbRatio | 0.00489853044086774 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 84 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 84 | | mean | 17.8 | | std | 11.95 | | cv | 0.671 | | sampleLengths | | 0 | 24 | | 1 | 25 | | 2 | 32 | | 3 | 26 | | 4 | 1 | | 5 | 23 | | 6 | 2 | | 7 | 24 | | 8 | 33 | | 9 | 15 | | 10 | 3 | | 11 | 4 | | 12 | 32 | | 13 | 22 | | 14 | 37 | | 15 | 14 | | 16 | 18 | | 17 | 46 | | 18 | 6 | | 19 | 12 | | 20 | 21 | | 21 | 25 | | 22 | 60 | | 23 | 4 | | 24 | 29 | | 25 | 26 | | 26 | 16 | | 27 | 8 | | 28 | 27 | | 29 | 2 | | 30 | 16 | | 31 | 24 | | 32 | 19 | | 33 | 22 | | 34 | 14 | | 35 | 38 | | 36 | 25 | | 37 | 24 | | 38 | 5 | | 39 | 6 | | 40 | 23 | | 41 | 16 | | 42 | 26 | | 43 | 6 | | 44 | 18 | | 45 | 6 | | 46 | 3 | | 47 | 28 | | 48 | 24 | | 49 | 19 |
| |
| 57.14% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 7 | | diversityRatio | 0.39285714285714285 | | totalSentences | 84 | | uniqueOpeners | 33 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 76 | | matches | | 0 | "Of course he didn’t." | | 1 | "Then she thought of Tomás" | | 2 | "Then she saw him." |
| | ratio | 0.039 | |
| 51.58% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 32 | | totalSentences | 76 | | matches | | 0 | "She stood in the mouth" | | 1 | "Her sharp jaw was set," | | 2 | "He’d been carrying a hard" | | 3 | "He didn’t stop." | | 4 | "She moved with the precision" | | 5 | "She had a suspect, and" | | 6 | "They ran parallel to the" | | 7 | "He knew these streets—she’d watched" | | 8 | "He turned abruptly, ducking into" | | 9 | "He moved with surprising speed" | | 10 | "He pressed the bone token" | | 11 | "She stood at the threshold," | | 12 | "She raised her left wrist," | | 13 | "She thought of Morris’s notes," | | 14 | "She thought of her service" | | 15 | "She descended with military precision," | | 16 | "She emerged onto a disused" | | 17 | "It occupied the abandoned station" | | 18 | "She kept to the shadows," | | 19 | "She was a detective in" |
| | ratio | 0.421 | |
| 71.84% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 59 | | totalSentences | 76 | | matches | | 0 | "The rain had been falling" | | 1 | "She stood in the mouth" | | 2 | "Her sharp jaw was set," | | 3 | "A flash of olive skin" | | 4 | "He’d been carrying a hard" | | 5 | "The word tore from her" | | 6 | "He didn’t stop." | | 7 | "Quinn pushed off from the" | | 8 | "She moved with the precision" | | 9 | "She had a suspect, and" | | 10 | "They ran parallel to the" | | 11 | "He knew these streets—she’d watched" | | 12 | "The clique, she’d learned, used" | | 13 | "He turned abruptly, ducking into" | | 14 | "Quinn followed three seconds later," | | 15 | "The alley opened onto a" | | 16 | "Tomás reached the door." | | 17 | "He moved with surprising speed" | | 18 | "The Saint Christopher medallion around" | | 19 | "He pressed the bone token" |
| | ratio | 0.776 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 76 | | matches | (empty) | | ratio | 0 | |
| 0.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 51 | | technicalSentenceCount | 20 | | matches | | 0 | "At forty-one, with eighteen years of decorated service behind her, she knew the particular ache that settled into the knees after a sprint through London’s slic…" | | 1 | "Twenty-nine years old, five-ten, with the kind of face that belonged in a tapas bar in Seville rather than the criminal underbelly of Soho." | | 2 | "He’d been carrying a hard case when she’d spotted him leaving the clinic on Wardour Street, and now he moved with the desperate, jerking gait of a man who knew …" | | 3 | "Quinn pushed off from the alley wall, her boots—polished to a military shine that the rain immediately dulled—splashing through gutter water that reflected the …" | | 4 | "Behind her, the green sign of the Raven’s Nest flickered, casting a sickly glow over the wet cobblestones, but she had no time for the bar’s hidden back room or…" | | 5 | "He knew these streets—she’d watched him for six weeks, ever since the whispers had started circulating about a paramedic who treated patients no hospital would …" | | 6 | "He turned abruptly, ducking into a narrow passage between a shuttered bookshop and a twenty-four-hour laundrette, his shoulder brushing the brick." | | 7 | "Quinn followed three seconds later, her hand resting on the butt of her service weapon, her heart hammering a steady, military cadence against her ribs." | | 8 | "In his hand, he held a token: a small, yellowed object carved from bone, intricate and wrong, covered in symbols that hurt to look at directly." | | 9 | "Rain dripped from the brim of her cap, pattering against her shoulders, soaking through her uniform." | | 10 | "She thought of Morris’s notes, the coded references to bone tokens and abandoned Tube stations, to a black market that relocated every full moon—which was tonig…" | | 11 | "She thought of her service record, her reputation, the eighteen years of procedure that screamed for backup, for caution, for the safety of the law." | | 12 | "The stairs spiraled down, endless concrete steps slick with moisture and something else—a faint, phosphorescent residue that glowed faintly green in the dark." | | 13 | "It occupied the abandoned station beneath Camden, a bazaar that shouldn’t exist, humming with a current that made the hair on her arms stand up despite the cold…" | | 14 | "Stalls lined the platform, lit by bioluminescent fungi in glass jars and flickering gas lamps that burned with a flame that cast no heat." | | 15 | "Maps that shifted and rewrote themselves when unobserved were sold by a woman with eyes like cracked amber." | | 16 | "Tomás stood at a stall near the far end of the platform, his back to her, the scar on his left forearm visible as he reached for a vial of liquid that swirled w…" | | 17 | "The Saint Christopher medallion hung against his chest, catching the fungal light, a talisman of protection in a place that offered none." | | 18 | "She lunged, her hand closing on his wrist, her fingers finding the scar tissue on his forearm, the familiar ridge of old violence." | | 19 | "She ducked, military reflexes taking over, and he broke free, sprinting toward a side tunnel that opened into the dark beyond the platform’s edge—a passage that…" |
| |
| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 3 | | uselessAdditionCount | 1 | | matches | | 0 | "she said, her voice low and dangerous in the market’s hum" |
| |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 2 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 7 | | tagDensity | 0.286 | | leniency | 0.571 | | rawRatio | 0 | | effectiveRatio | 0 | |