| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 8 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 29 | | tagDensity | 0.276 | | leniency | 0.552 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 89.99% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1498 | | totalAiIsmAdverbs | 3 | | 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) | |
| 19.89% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1498 | | totalAiIsms | 24 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | | | 13 | | | 14 | | | 15 | | | 16 | | | 17 | |
| | highlights | | 0 | "fluttered" | | 1 | "flicker" | | 2 | "echoed" | | 3 | "whisper" | | 4 | "hulking" | | 5 | "weight" | | 6 | "standard" | | 7 | "charm" | | 8 | "pulsed" | | 9 | "chaotic" | | 10 | "electric" | | 11 | "velvet" | | 12 | "silence" | | 13 | "shimmered" | | 14 | "pulse" | | 15 | "unreadable" | | 16 | "warmth" | | 17 | "charged" |
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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 | 0 | | narrationSentences | 185 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 185 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 204 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 41 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 5 | | markdownWords | 10 | | totalWords | 1478 | | ratio | 0.007 | | matches | | 0 | "The Nest. Midnight. Bring the bone." | | 1 | "Reforming." | | 2 | "that" | | 3 | "them" | | 4 | "survive" |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 10 | | unquotedAttributions | 0 | | matches | (empty) | |
| 33.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 73 | | wordCount | 1311 | | uniqueNames | 22 | | maxNameDensity | 1.53 | | worstName | "Quinn" | | maxWindowNameDensity | 4 | | worstWindowName | "Herrera" | | discoveredNames | | Tube | 1 | | Quinn | 20 | | Tomás | 1 | | Herrera | 19 | | London | 1 | | Veil | 3 | | Market | 3 | | Victorian | 1 | | Stoke | 1 | | Newington | 1 | | Nest | 2 | | Raven | 1 | | Tactical | 2 | | Entry | 1 | | Containment | 1 | | Unit | 1 | | Morris | 2 | | Whitechapel | 1 | | Saint | 1 | | Christopher | 1 | | Silas | 6 | | Like | 3 |
| | persons | | 0 | "Quinn" | | 1 | "Tomás" | | 2 | "Herrera" | | 3 | "Market" | | 4 | "Raven" | | 5 | "Morris" | | 6 | "Saint" | | 7 | "Christopher" | | 8 | "Silas" |
| | places | | | globalScore | 0.737 | | windowScore | 0.333 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 83 | | glossingSentenceCount | 1 | | matches | | 0 | "smelled like copper and decay" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.677 | | wordCount | 1478 | | matches | | 0 | "not like someone running, but like someone returning home" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 204 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 74 | | mean | 19.97 | | std | 19.25 | | cv | 0.964 | | sampleLengths | | 0 | 55 | | 1 | 42 | | 2 | 71 | | 3 | 60 | | 4 | 29 | | 5 | 42 | | 6 | 45 | | 7 | 3 | | 8 | 87 | | 9 | 8 | | 10 | 13 | | 11 | 65 | | 12 | 27 | | 13 | 5 | | 14 | 10 | | 15 | 73 | | 16 | 6 | | 17 | 51 | | 18 | 37 | | 19 | 12 | | 20 | 17 | | 21 | 2 | | 22 | 3 | | 23 | 36 | | 24 | 23 | | 25 | 5 | | 26 | 25 | | 27 | 53 | | 28 | 23 | | 29 | 7 | | 30 | 5 | | 31 | 38 | | 32 | 22 | | 33 | 22 | | 34 | 6 | | 35 | 3 | | 36 | 7 | | 37 | 22 | | 38 | 14 | | 39 | 30 | | 40 | 8 | | 41 | 5 | | 42 | 5 | | 43 | 13 | | 44 | 18 | | 45 | 4 | | 46 | 3 | | 47 | 2 | | 48 | 28 | | 49 | 29 |
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| 97.68% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 4 | | totalSentences | 185 | | matches | | 0 | "been smashed" | | 1 | "was piled" | | 2 | "been slipped" | | 3 | "was twisted" |
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| 0.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 8 | | totalVerbs | 226 | | matches | | 0 | "was heading" | | 1 | "was walking" | | 2 | "was circling" | | 3 | "wasn’t just watching" | | 4 | "was packing" | | 5 | "was calling" | | 6 | "was coming" | | 7 | "was rotting" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 20 | | semicolonCount | 0 | | flaggedSentences | 18 | | totalSentences | 204 | | ratio | 0.088 | | matches | | 0 | "The air shifted—thicker, warmer, laced with the scent of damp stone and something else." | | 1 | "Camden’s abandoned platform wasn’t its usual stop—it followed the moon like a hungry thing—but tonight was full moon." | | 2 | "Inside lay a small, iron bone token—cold and smooth against her fingers." | | 3 | "She caught it in the corner of her eye—dark green, the kind of workwear paramedics wear." | | 4 | "Halfway down, the air turned to syrup—heavy, unnatural." | | 5 | "Stalls lined a warren of ancient brick arches, their wares glowing under muted lanterns—vials of swirling violet liquid, jars of eyes that blinked when no one watched, a stall draped in crow feathers selling whispered prophecies written on cigarette papers." | | 6 | "Standard entry charm—made of human bone, blessed by a corrupt priest in Stoke Newington." | | 7 | "A stallkeeper’s eyes—glowing faintly yellow—locked onto her." | | 8 | "The crowd wasn’t just watching her walk in—it was circling." | | 9 | "No, not a flyer—a map." | | 10 | "And the thing that took him—it hadn’t been human." | | 11 | "Quinn took a step forward—then heard it." | | 12 | "She pressed two fingers to his throat anyway—instinct." | | 13 | "Just—empty." | | 14 | "The man’s wrist was marked—three small puncture wounds, arranged in a triangle." | | 15 | "The dying man’s eyes fluttered—once." | | 16 | "The dead man on the floor made a sound—a wet, rattling choke." | | 17 | "She charged forward—straight past him, baton raised, straight into the darkness behind the curtained archway." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1334 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 48 | | adverbRatio | 0.035982008995502246 | | lyAdverbCount | 8 | | lyAdverbRatio | 0.005997001499250375 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 204 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 204 | | mean | 7.25 | | std | 5.94 | | cv | 0.82 | | sampleLengths | | 0 | 16 | | 1 | 16 | | 2 | 17 | | 3 | 6 | | 4 | 15 | | 5 | 14 | | 6 | 9 | | 7 | 2 | | 8 | 2 | | 9 | 13 | | 10 | 25 | | 11 | 18 | | 12 | 15 | | 13 | 12 | | 14 | 13 | | 15 | 12 | | 16 | 12 | | 17 | 4 | | 18 | 7 | | 19 | 4 | | 20 | 4 | | 21 | 16 | | 22 | 3 | | 23 | 2 | | 24 | 12 | | 25 | 6 | | 26 | 8 | | 27 | 4 | | 28 | 7 | | 29 | 5 | | 30 | 16 | | 31 | 19 | | 32 | 10 | | 33 | 3 | | 34 | 11 | | 35 | 40 | | 36 | 36 | | 37 | 8 | | 38 | 13 | | 39 | 7 | | 40 | 4 | | 41 | 13 | | 42 | 11 | | 43 | 7 | | 44 | 14 | | 45 | 9 | | 46 | 7 | | 47 | 10 | | 48 | 4 | | 49 | 6 |
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| 43.79% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 19 | | diversityRatio | 0.31862745098039214 | | totalSentences | 204 | | uniqueOpeners | 65 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 9 | | totalSentences | 149 | | matches | | 0 | "Just the bare minimum of" | | 1 | "Just a quiet arrest in" | | 2 | "Then the market stallkeeper’s voice" | | 3 | "Just silence and a whisper" | | 4 | "Then, from the shadows, a" | | 5 | "Just a flicker." | | 6 | "Then, slowly, the fingers twitched." | | 7 | "No longer human." | | 8 | "Even the flickering lanterns dimmed." |
| | ratio | 0.06 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 33 | | totalSentences | 149 | | matches | | 0 | "She ducked under a sagging" | | 1 | "She pressed a button on" | | 2 | "She caught it in the" | | 3 | "She pushed through." | | 4 | "He moved with purpose, not" | | 5 | "She adjusted her grip on" | | 6 | "She tucked it into her" | | 7 | "It let you pass, but" | | 8 | "His stall was piled with" | | 9 | "He grinned, teeth too sharp." | | 10 | "She ignored the jab." | | 11 | "Her fingers tightened reflexively." | | 12 | "He wouldn’t have slipped it" | | 13 | "She reached into her coat," | | 14 | "She could bring him in" | | 15 | "She turned slowly." | | 16 | "She should call it in." | | 17 | "They had necromancers on standby." | | 18 | "She’d made the call before." | | 19 | "She pivoted, baton snapping out." |
| | ratio | 0.221 | |
| 100.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 107 | | totalSentences | 149 | | matches | | 0 | "The tunnel’s mouth yawned dark" | | 1 | "Detective Quinn’s boots skidded on" | | 2 | "She ducked under a sagging" | | 3 | "The air shifted—thicker, warmer, laced" | | 4 | "Something sharp and metallic beneath" | | 5 | "Herrera’s trail led right down" | | 6 | "The station sign above had" | | 7 | "Camden’s abandoned platform wasn’t its" | | 8 | "Quinn’s leather watch strap bit" | | 9 | "She pressed a button on" | | 10 | "A shadow moved below." | | 11 | "A flicker of fabric." | | 12 | "She caught it in the" | | 13 | "Quinn lunged for the staircase," | | 14 | "The paint peeled like sunburnt" | | 15 | "Halfway down, the air turned" | | 16 | "The acoustics shifted too." | | 17 | "A cough from below echoed" | | 18 | "A whisper became a shout." | | 19 | "A dim, amber glow spilled" |
| | ratio | 0.718 | |
| 67.11% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 149 | | matches | | 0 | "If Herrera was heading there," | | 1 | "To the way he’d looked" |
| | ratio | 0.013 | |
| 84.55% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 49 | | technicalSentenceCount | 4 | | matches | | 0 | "She ducked under a sagging strip of warning tape that fluttered like a death shroud." | | 1 | "Stalls lined a warren of ancient brick arches, their wares glowing under muted lanterns—vials of swirling violet liquid, jars of eyes that blinked when no one w…" | | 2 | "The crowd was a mix of everything that didn’t belong in the daylight: elves in long coats, hulking figures with too many limbs, a woman who looked exactly like …" | | 3 | "But the last time she’d waited for backup, Morris had bled out on a rooftop in Whitechapel, clutching a gun that wouldn’t fire." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 8 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 6 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 29 | | tagDensity | 0.207 | | leniency | 0.414 | | rawRatio | 0 | | effectiveRatio | 0 | |