| 57.14% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 7 | | adverbTagCount | 1 | | adverbTags | | 0 | "Quinn said finally [finally]" |
| | dialogueSentences | 9 | | tagDensity | 0.778 | | leniency | 1 | | rawRatio | 0.143 | | effectiveRatio | 0.143 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 677 | | 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) | |
| 3.99% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 677 | | totalAiIsms | 13 | | found | | | highlights | | 0 | "glinting" | | 1 | "fragmented" | | 2 | "scanning" | | 3 | "depths" | | 4 | "footsteps" | | 5 | "echoed" | | 6 | "clandestine" | | 7 | "treacherous" | | 8 | "velvet" | | 9 | "racing" | | 10 | "fleeting" |
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| 66.67% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 2 | | maxInWindow | 2 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 1 |
| | 1 | | label | "air was thick with" | | count | 1 |
|
| | highlights | | 0 | "eyes narrowed" | | 1 | "The air was heavy with" |
| |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 1 | | narrationSentences | 38 | | matches | | |
| 0.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 3 | | narrationSentences | 38 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 40 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 35 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 679 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 4 | | unquotedAttributions | 0 | | matches | (empty) | |
| 45.83% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 36 | | wordCount | 624 | | uniqueNames | 12 | | maxNameDensity | 2.08 | | worstName | "Quinn" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Quinn" | | discoveredNames | | Soho | 1 | | Harlow | 1 | | Quinn | 13 | | Tomás | 9 | | Herrera | 1 | | Wardour | 1 | | Street | 1 | | Tube | 3 | | Saint | 2 | | Christopher | 2 | | Veil | 1 | | Market | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Tomás" | | 3 | "Herrera" | | 4 | "Saint" | | 5 | "Christopher" | | 6 | "Market" |
| | places | | 0 | "Soho" | | 1 | "Wardour" | | 2 | "Street" | | 3 | "Tube" |
| | globalScore | 0.458 | | windowScore | 0.833 | |
| 14.86% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 37 | | glossingSentenceCount | 2 | | matches | | 0 | "artifacts that seemed to ripple with a malevolent energy" | | 1 | "as if daring her to take the token" |
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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 | 679 | | matches | (empty) | |
| 83.33% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 40 | | matches | | |
| 96.27% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 19 | | mean | 35.74 | | std | 17.4 | | cv | 0.487 | | sampleLengths | | 0 | 61 | | 1 | 32 | | 2 | 48 | | 3 | 45 | | 4 | 46 | | 5 | 51 | | 6 | 67 | | 7 | 23 | | 8 | 55 | | 9 | 34 | | 10 | 47 | | 11 | 29 | | 12 | 15 | | 13 | 22 | | 14 | 44 | | 15 | 26 | | 16 | 9 | | 17 | 24 | | 18 | 1 |
| |
| 96.03% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 38 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 103 | | matches | | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 4 | | semicolonCount | 1 | | flaggedSentences | 5 | | totalSentences | 40 | | ratio | 0.125 | | matches | | 0 | "As she followed Tomás into the depths of the tunnel system, the walls began to change – peeling advertisements gave way to ancient brickwork, and the air thickened with the scent of smoke and something else..." | | 1 | "Quinn's grip on her pistol tightened; this was no ordinary part of the Tube." | | 2 | "Stalls and makeshift vendors filled the platform, peddling goods that made her skin crawl – jars of glowing, pulsing liquids, and artifacts that seemed to ripple with a malevolent energy." | | 3 | "Her mind reeled – this was what she'd been searching for, the clandestine underbelly of the city's supernatural scene." | | 4 | "She knew the stories – once you accepted a token, you were bound by the Veil Market's rules..." |
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| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 481 | | adjectiveStacks | 1 | | stackExamples | | 0 | "short curly brown hair" |
| | adverbCount | 12 | | adverbRatio | 0.02494802494802495 | | lyAdverbCount | 7 | | lyAdverbRatio | 0.014553014553014554 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 40 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 40 | | mean | 16.98 | | std | 7.6 | | cv | 0.448 | | sampleLengths | | 0 | 19 | | 1 | 23 | | 2 | 19 | | 3 | 22 | | 4 | 10 | | 5 | 34 | | 6 | 14 | | 7 | 21 | | 8 | 13 | | 9 | 11 | | 10 | 29 | | 11 | 17 | | 12 | 36 | | 13 | 1 | | 14 | 14 | | 15 | 15 | | 16 | 22 | | 17 | 30 | | 18 | 23 | | 19 | 22 | | 20 | 19 | | 21 | 14 | | 22 | 16 | | 23 | 18 | | 24 | 9 | | 25 | 18 | | 26 | 11 | | 27 | 9 | | 28 | 14 | | 29 | 15 | | 30 | 15 | | 31 | 11 | | 32 | 11 | | 33 | 9 | | 34 | 15 | | 35 | 20 | | 36 | 26 | | 37 | 9 | | 38 | 24 | | 39 | 1 |
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| 91.67% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 0 | | diversityRatio | 0.55 | | totalSentences | 40 | | uniqueOpeners | 22 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 37 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 7 | | totalSentences | 37 | | matches | | 0 | "Her military-honed bearing allowed her" | | 1 | "He vanished into the crowd" | | 2 | "she muttered, holstered pistol heavy" | | 3 | "Her mind reeled – this" | | 4 | "She knew the stories –" | | 5 | "she whispered to herself, the" | | 6 | "She could back out, call" |
| | ratio | 0.189 | |
| 27.57% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 32 | | totalSentences | 37 | | matches | | 0 | "Rain lashed down on the" | | 1 | "Detective Harlow Quinn's eyes, narrowed" | | 2 | "Her military-honed bearing allowed her" | | 3 | "Quinn's voice cut through the" | | 4 | "He vanished into the crowd" | | 5 | "Quinn sprinted after him, shouldering" | | 6 | "A train roared out of" | | 7 | "Tomás reappeared at the far" | | 8 | "Quinn hesitated for a heartbeat," | | 9 | "The air was heavy with" | | 10 | "she muttered, holstered pistol heavy" | | 11 | "The only sound was the" | | 12 | "Quinn's grip on her pistol" | | 13 | "The tunnel opened up into" | | 14 | "Quinn's footsteps echoed off the" | | 15 | "Stalls and makeshift vendors filled" | | 16 | "a low, husky voice drawled" | | 17 | "Quinn's gaze swept past the" | | 18 | "Her mind reeled – this" | | 19 | "A figure emerged from the" |
| | ratio | 0.865 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 37 | | matches | (empty) | | ratio | 0 | |
| 85.71% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 25 | | technicalSentenceCount | 2 | | matches | | 0 | "Quinn's footsteps echoed off the walls as she entered, her eyes gradually adjusting to the warm, golden light that permeated the space." | | 1 | "Stalls and makeshift vendors filled the platform, peddling goods that made her skin crawl – jars of glowing, pulsing liquids, and artifacts that seemed to rippl…" |
| |
| 53.57% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 7 | | uselessAdditionCount | 1 | | matches | | 0 | "Quinn said finally, her voice firm," |
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| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 5 | | fancyCount | 3 | | fancyTags | | 0 | "she muttered (mutter)" | | 1 | "husky voice drawled (drawl)" | | 2 | "she whispered (whisper)" |
| | dialogueSentences | 9 | | tagDensity | 0.556 | | leniency | 1 | | rawRatio | 0.6 | | effectiveRatio | 0.6 | |