| 0.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 7 | | adverbTagCount | 3 | | adverbTags | | 0 | "Quinn asked sharply [sharply]" | | 1 | "she said gruffly [gruffly]" | | 2 | "Quinn muttered darkly [darkly]" |
| | dialogueSentences | 18 | | tagDensity | 0.389 | | leniency | 0.778 | | rawRatio | 0.429 | | effectiveRatio | 0.333 | |
| 83.54% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1519 | | totalAiIsmAdverbs | 5 | | found | | | highlights | | 0 | "sharply" | | 1 | "slightly" | | 2 | "cautiously" | | 3 | "really" |
| |
| 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) | |
| 60.50% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1519 | | totalAiIsms | 12 | | found | | | highlights | | 0 | "depths" | | 1 | "quickened" | | 2 | "flickered" | | 3 | "pulse" | | 4 | "pounding" | | 5 | "otherworldly" | | 6 | "gleaming" | | 7 | "etched" | | 8 | "crystal" | | 9 | "surreal" | | 10 | "shimmered" | | 11 | "grave" |
| |
| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "air was thick with" | | count | 1 |
|
| | highlights | | 0 | "the air was thick with" |
| |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 79 | | matches | (empty) | |
| 70.52% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 2 | | narrationSentences | 79 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 91 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 62 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1514 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 9 | | unquotedAttributions | 0 | | matches | (empty) | |
| 47.50% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 54 | | wordCount | 1122 | | uniqueNames | 11 | | maxNameDensity | 2.05 | | worstName | "Quinn" | | maxWindowNameDensity | 3 | | worstWindowName | "Quinn" | | discoveredNames | | Harlow | 1 | | Quinn | 23 | | Tomás | 2 | | Herrera | 16 | | Morris | 4 | | Veil | 2 | | Market | 2 | | London | 1 | | Adam | 1 | | Saint | 1 | | Christopher | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Tomás" | | 3 | "Herrera" | | 4 | "Morris" | | 5 | "Adam" | | 6 | "Saint" | | 7 | "Christopher" |
| | places | | | globalScore | 0.475 | | windowScore | 0.667 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 72 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1514 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 91 | | matches | (empty) | |
| 58.70% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 31 | | mean | 48.84 | | std | 17.36 | | cv | 0.355 | | sampleLengths | | 0 | 29 | | 1 | 46 | | 2 | 54 | | 3 | 59 | | 4 | 49 | | 5 | 48 | | 6 | 73 | | 7 | 90 | | 8 | 52 | | 9 | 65 | | 10 | 28 | | 11 | 42 | | 12 | 57 | | 13 | 42 | | 14 | 38 | | 15 | 23 | | 16 | 31 | | 17 | 40 | | 18 | 83 | | 19 | 54 | | 20 | 64 | | 21 | 66 | | 22 | 60 | | 23 | 26 | | 24 | 50 | | 25 | 20 | | 26 | 51 | | 27 | 36 | | 28 | 60 | | 29 | 59 | | 30 | 19 |
| |
| 96.38% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 79 | | matches | | 0 | "were concerned" | | 1 | "was made" |
| |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 189 | | matches | | 0 | "was telling" | | 1 | "was stumbling" |
| |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 4 | | semicolonCount | 2 | | flaggedSentences | 6 | | totalSentences | 91 | | ratio | 0.066 | | matches | | 0 | "The rain had started an hour ago—in the clammy depths of Silas' bar, The Raven's Nest, where Quinn had first picked up Herrera's trail." | | 1 | "A strange hum seemed to resonate in Quinn's bones; the thrum of powerful machinery or perhaps an otherworldly energy source." | | 2 | "She'd heard whispered rumors about this place—the Veil Market, a nomadic black-market bazaar catering to London's supernatural underworld." | | 3 | "Her gut told her that Herrera was telling the truth—at least as far as his fear and desperation were concerned." | | 4 | "The decision was made; now it was time to act before the chance slipped through her fingers." | | 5 | "The hunt was over—for now." |
| |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 546 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 15 | | adverbRatio | 0.027472527472527472 | | lyAdverbCount | 6 | | lyAdverbRatio | 0.01098901098901099 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 91 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 91 | | mean | 16.64 | | std | 9.47 | | cv | 0.569 | | sampleLengths | | 0 | 18 | | 1 | 11 | | 2 | 24 | | 3 | 13 | | 4 | 9 | | 5 | 20 | | 6 | 19 | | 7 | 15 | | 8 | 11 | | 9 | 11 | | 10 | 18 | | 11 | 19 | | 12 | 13 | | 13 | 17 | | 14 | 19 | | 15 | 21 | | 16 | 12 | | 17 | 15 | | 18 | 9 | | 19 | 20 | | 20 | 18 | | 21 | 26 | | 22 | 13 | | 23 | 18 | | 24 | 12 | | 25 | 16 | | 26 | 22 | | 27 | 9 | | 28 | 11 | | 29 | 11 | | 30 | 14 | | 31 | 16 | | 32 | 18 | | 33 | 15 | | 34 | 20 | | 35 | 12 | | 36 | 10 | | 37 | 18 | | 38 | 11 | | 39 | 14 | | 40 | 4 | | 41 | 13 | | 42 | 5 | | 43 | 22 | | 44 | 30 | | 45 | 11 | | 46 | 12 | | 47 | 19 | | 48 | 11 | | 49 | 18 |
| |
| 75.82% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 1 | | diversityRatio | 0.46153846153846156 | | totalSentences | 91 | | uniqueOpeners | 42 | |
| 85.47% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 78 | | matches | | 0 | "Then, with a shuddering sigh," | | 1 | "Then Tomás Herrera was stumbling" |
| | ratio | 0.026 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 19 | | totalSentences | 78 | | matches | | 0 | "She reached for her phone" | | 1 | "She nudged the fire exit" | | 2 | "She'd heard whispered rumors about" | | 3 | "It was more information than" | | 4 | "It felt strangely like stumbling" | | 5 | "She could see her breath" | | 6 | "He held a knife in" | | 7 | "He glanced from Quinn to" | | 8 | "Her eyes raked over Herrera," | | 9 | "He sagged back against the" | | 10 | "She kept her baton at" | | 11 | "He shuddered, his skin taking" | | 12 | "His hand drifted unconsciously to" | | 13 | "Her gut told her that" | | 14 | "Her partner had died trying" | | 15 | "she said gruffly" | | 16 | "She grabbed Herrera's arm, hauling" | | 17 | "She frog-marched Herrera back through" | | 18 | "She turned her back on" |
| | ratio | 0.244 | |
| 100.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 55 | | totalSentences | 78 | | matches | | 0 | "Detective Harlow Quinn pushed through" | | 1 | "The rain had started an" | | 2 | "Quinn cursed under her breath" | | 3 | "The neon signs and streetlamps" | | 4 | "An old woman, her head" | | 5 | "Quinn swerved to avoid a" | | 6 | "Quinn shouted, but the surging" | | 7 | "She reached for her phone" | | 8 | "Herrera veered sharply left into" | | 9 | "Quinn followed, nearly choking on" | | 10 | "Quinn edged toward the door," | | 11 | "A swift flick of the" | | 12 | "She nudged the fire exit" | | 13 | "A strange hum seemed to" | | 14 | "The floor sloped down, a" | | 15 | "Vendors and patrons alike paused" | | 16 | "Quinn kept her baton at" | | 17 | "She'd heard whispered rumors about" | | 18 | "It was more information than" | | 19 | "It felt strangely like stumbling" |
| | ratio | 0.705 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 3 | | totalSentences | 78 | | matches | | 0 | "Now thunder rumbled overhead, an" | | 1 | "If Herrera's intel could help" | | 2 | "Even if it led to" |
| | ratio | 0.038 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 63 | | technicalSentenceCount | 1 | | matches | | 0 | "A shiver ran down Quinn's spine, as if someone had stepped over her grave." |
| |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 7 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 6 | | fancyCount | 3 | | fancyTags | | 0 | "Quinn shouted (shout)" | | 1 | "he stammered (stammer)" | | 2 | "Quinn muttered darkly (mutter)" |
| | dialogueSentences | 18 | | tagDensity | 0.333 | | leniency | 0.667 | | rawRatio | 0.5 | | effectiveRatio | 0.333 | |