| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 3 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 9 | | tagDensity | 0.333 | | leniency | 0.667 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 94.43% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 898 | | totalAiIsmAdverbs | 1 | | 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) | |
| 16.48% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 898 | | totalAiIsms | 15 | | found | | | highlights | | 0 | "gloom" | | 1 | "weight" | | 2 | "pulse" | | 3 | "tracing" | | 4 | "tinged" | | 5 | "footsteps" | | 6 | "echoed" | | 7 | "glinting" | | 8 | "calculating" | | 9 | "familiar" | | 10 | "pulsed" | | 11 | "could feel" |
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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 | 75 | | matches | (empty) | |
| 85.71% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 1 | | narrationSentences | 75 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 81 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 36 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 888 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 2 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 24 | | wordCount | 829 | | uniqueNames | 12 | | maxNameDensity | 0.72 | | worstName | "Market" | | maxWindowNameDensity | 1 | | worstWindowName | "Quinn" | | discoveredNames | | Dean | 1 | | Street | 1 | | Quinn | 5 | | Soho | 1 | | Raven | 1 | | Nest | 1 | | Veil | 3 | | Market | 6 | | Morris | 2 | | Saint | 1 | | Christopher | 1 | | Herrera | 1 |
| | persons | | 0 | "Quinn" | | 1 | "Raven" | | 2 | "Market" | | 3 | "Morris" | | 4 | "Saint" | | 5 | "Christopher" | | 6 | "Herrera" |
| | places | | | globalScore | 1 | | windowScore | 1 | |
| 66.67% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 60 | | glossingSentenceCount | 2 | | matches | | 0 | "felt like a live wire" | | 1 | "quite human" |
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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 | 888 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 81 | | matches | | 0 | "crossed that threshold" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 27 | | mean | 32.89 | | std | 23.01 | | cv | 0.7 | | sampleLengths | | 0 | 77 | | 1 | 93 | | 2 | 64 | | 3 | 43 | | 4 | 8 | | 5 | 8 | | 6 | 22 | | 7 | 41 | | 8 | 34 | | 9 | 18 | | 10 | 46 | | 11 | 15 | | 12 | 52 | | 13 | 40 | | 14 | 55 | | 15 | 45 | | 16 | 3 | | 17 | 8 | | 18 | 54 | | 19 | 38 | | 20 | 7 | | 21 | 10 | | 22 | 14 | | 23 | 37 | | 24 | 19 | | 25 | 31 | | 26 | 6 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 75 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 138 | | matches | | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 10 | | semicolonCount | 0 | | flaggedSentences | 8 | | totalSentences | 81 | | ratio | 0.099 | | matches | | 0 | "The suspect—a wiry man with a hunched shoulder and a duffel bag slung low—had vanished into the maze of Soho’s side streets, his silhouette swallowed by the green neon glow of The Raven’s Nest." | | 1 | "Inside, the air hung thick with the scent of stale beer and something else—something metallic, like old blood." | | 2 | "She stepped back into the main room, adjusting her grip on the worn leather watch at her wrist—DS Morris’s watch, still ticking despite everything." | | 3 | "Her shoe caught on something—a loose stone, half-buried in grime." | | 4 | "The Veil Market sprawled before her—tents and stalls carved from salvaged metal and black cloth, their wares glinting under phosphorescent fungi." | | 5 | "She stepped onto the uneven ground, her boots crunching over broken glass and something softer—bone, maybe, or teeth." | | 6 | "The vendor—hooded, faceless—glanced at her." | | 7 | "His eyes met hers—warm brown, questioning." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 841 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 17 | | adverbRatio | 0.020214030915576695 | | lyAdverbCount | 2 | | lyAdverbRatio | 0.0023781212841854932 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 81 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 81 | | mean | 10.96 | | std | 6.62 | | cv | 0.603 | | sampleLengths | | 0 | 21 | | 1 | 22 | | 2 | 34 | | 3 | 18 | | 4 | 13 | | 5 | 18 | | 6 | 20 | | 7 | 24 | | 8 | 7 | | 9 | 11 | | 10 | 6 | | 11 | 20 | | 12 | 10 | | 13 | 10 | | 14 | 6 | | 15 | 24 | | 16 | 13 | | 17 | 8 | | 18 | 3 | | 19 | 5 | | 20 | 7 | | 21 | 15 | | 22 | 6 | | 23 | 18 | | 24 | 8 | | 25 | 9 | | 26 | 13 | | 27 | 6 | | 28 | 15 | | 29 | 13 | | 30 | 5 | | 31 | 7 | | 32 | 10 | | 33 | 10 | | 34 | 5 | | 35 | 14 | | 36 | 3 | | 37 | 4 | | 38 | 8 | | 39 | 8 | | 40 | 14 | | 41 | 17 | | 42 | 13 | | 43 | 4 | | 44 | 10 | | 45 | 10 | | 46 | 10 | | 47 | 6 | | 48 | 10 | | 49 | 21 |
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| 47.53% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 2 | | diversityRatio | 0.2962962962962963 | | totalSentences | 81 | | uniqueOpeners | 24 | |
| 46.30% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 72 | | matches | | 0 | "Somewhere, a bell chimed." |
| | ratio | 0.014 | |
| 81.11% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 25 | | totalSentences | 72 | | matches | | 0 | "She skidded to a halt" | | 1 | "She moved past the bar," | | 2 | "She stepped back into the" | | 3 | "He returned his gaze to" | | 4 | "She’d heard the whispers about" | | 5 | "She couldn’t let him disappear" | | 6 | "Her fingers found the handle" | | 7 | "She turned toward the back" | | 8 | "He hesitated, glancing sideways" | | 9 | "She didn’t wait for him" | | 10 | "Her shoe caught on something—a" | | 11 | "She knelt, brushing it free." | | 12 | "Her pulse spiked." | | 13 | "She pocketed it, fingers tracing" | | 14 | "She pried it open with" | | 15 | "Her breath fogged in the" | | 16 | "She followed, each step a" | | 17 | "She gripped the rail of" | | 18 | "Their movements were too fluid," | | 19 | "She’d seen faces like theirs" |
| | ratio | 0.347 | |
| 22.50% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 63 | | totalSentences | 72 | | matches | | 0 | "The rain fell in sheets," | | 1 | "Harlow Quinn’s boots slapped against" | | 2 | "The suspect—a wiry man with" | | 3 | "She skidded to a halt" | | 4 | "The sign buzzed lazily above," | | 5 | "The maps on the walls" | | 6 | "She moved past the bar," | | 7 | "The shelf creaked when she" | | 8 | "A hidden door yawned open," | | 9 | "Quinn’s hand hovered over the" | | 10 | "The bone token requirement of" | | 11 | "A floorboard groaned beneath her" | | 12 | "She stepped back into the" | | 13 | "The bartender, a gaunt man" | | 14 | "Quinn’s jaw tightened." | | 15 | "He returned his gaze to" | | 16 | "The words hit like a" | | 17 | "She’d heard the whispers about" | | 18 | "She couldn’t let him disappear" | | 19 | "Her fingers found the handle" |
| | ratio | 0.875 | |
| 69.44% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 72 | | matches | | 0 | "If she didn’t follow, he’d" |
| | ratio | 0.014 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 38 | | technicalSentenceCount | 1 | | matches | | 0 | "Shadows writhed at the market’s edges, forming shapes that weren’t quite human." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 3 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 38.89% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 2 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 9 | | tagDensity | 0.222 | | leniency | 0.444 | | rawRatio | 0.5 | | effectiveRatio | 0.222 | |