| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 19 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 45 | | tagDensity | 0.422 | | leniency | 0.844 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1419 | | 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) | |
| 36.58% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1419 | | totalAiIsms | 18 | | found | | | highlights | | 0 | "gloom" | | 1 | "depths" | | 2 | "glistening" | | 3 | "lilt" | | 4 | "scanned" | | 5 | "intricate" | | 6 | "wavering" | | 7 | "velvet" | | 8 | "silk" | | 9 | "silence" | | 10 | "pulsed" | | 11 | "shattered" | | 12 | "echoed" | | 13 | "dancing" | | 14 | "weight" |
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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 | 183 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 3 | | narrationSentences | 183 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 208 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 19 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1419 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 6 | | unquotedAttributions | 0 | | matches | (empty) | |
| 16.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 54 | | wordCount | 1213 | | uniqueNames | 9 | | maxNameDensity | 2.64 | | worstName | "Quinn" | | maxWindowNameDensity | 4.5 | | worstWindowName | "Quinn" | | discoveredNames | | Camden | 2 | | Quinn | 32 | | Underground | 1 | | Seville | 1 | | Herrera | 1 | | Tomás | 7 | | Market | 2 | | Morris | 2 | | Collector | 6 |
| | persons | | 0 | "Quinn" | | 1 | "Herrera" | | 2 | "Tomás" | | 3 | "Market" | | 4 | "Morris" | | 5 | "Collector" |
| | places | | | globalScore | 0.181 | | windowScore | 0.167 | |
| 93.18% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 88 | | glossingSentenceCount | 2 | | matches | | 0 | "coat that seemed to ripple like water" | | 1 | "sounded like dry leaves skittering on ston" |
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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 | 1419 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 208 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 67 | | mean | 21.18 | | std | 15.4 | | cv | 0.727 | | sampleLengths | | 0 | 66 | | 1 | 49 | | 2 | 51 | | 3 | 56 | | 4 | 50 | | 5 | 26 | | 6 | 1 | | 7 | 39 | | 8 | 17 | | 9 | 24 | | 10 | 6 | | 11 | 10 | | 12 | 4 | | 13 | 24 | | 14 | 24 | | 15 | 14 | | 16 | 16 | | 17 | 54 | | 18 | 10 | | 19 | 28 | | 20 | 10 | | 21 | 47 | | 22 | 47 | | 23 | 24 | | 24 | 2 | | 25 | 34 | | 26 | 6 | | 27 | 13 | | 28 | 19 | | 29 | 4 | | 30 | 21 | | 31 | 27 | | 32 | 48 | | 33 | 19 | | 34 | 32 | | 35 | 10 | | 36 | 8 | | 37 | 22 | | 38 | 4 | | 39 | 31 | | 40 | 27 | | 41 | 11 | | 42 | 39 | | 43 | 14 | | 44 | 4 | | 45 | 24 | | 46 | 7 | | 47 | 24 | | 48 | 19 | | 49 | 31 |
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| 97.59% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 4 | | totalSentences | 183 | | matches | | 0 | "were swallowed" | | 1 | "were rusted" | | 2 | "was thrown" | | 3 | "was gone" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 236 | | matches | | 0 | "was discarding" | | 1 | "was pulsing" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 208 | | ratio | 0 | | matches | (empty) | |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1216 | | adjectiveStacks | 1 | | stackExamples | | 0 | "faint, sickly green light." |
| | adverbCount | 16 | | adverbRatio | 0.013157894736842105 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.004111842105263158 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 208 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 208 | | mean | 6.82 | | std | 3.84 | | cv | 0.563 | | sampleLengths | | 0 | 16 | | 1 | 4 | | 2 | 18 | | 3 | 19 | | 4 | 4 | | 5 | 5 | | 6 | 9 | | 7 | 19 | | 8 | 8 | | 9 | 8 | | 10 | 5 | | 11 | 7 | | 12 | 15 | | 13 | 11 | | 14 | 18 | | 15 | 11 | | 16 | 8 | | 17 | 18 | | 18 | 9 | | 19 | 10 | | 20 | 5 | | 21 | 5 | | 22 | 6 | | 23 | 14 | | 24 | 9 | | 25 | 11 | | 26 | 11 | | 27 | 15 | | 28 | 1 | | 29 | 7 | | 30 | 4 | | 31 | 6 | | 32 | 15 | | 33 | 7 | | 34 | 9 | | 35 | 8 | | 36 | 6 | | 37 | 9 | | 38 | 2 | | 39 | 2 | | 40 | 5 | | 41 | 6 | | 42 | 5 | | 43 | 5 | | 44 | 4 | | 45 | 10 | | 46 | 14 | | 47 | 4 | | 48 | 2 | | 49 | 2 |
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| 35.58% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 30 | | diversityRatio | 0.2403846153846154 | | totalSentences | 208 | | uniqueOpeners | 50 | |
| 39.92% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 167 | | matches | | 0 | "Just the rain and the" | | 1 | "Even the floating candles dimmed." |
| | ratio | 0.012 | |
| 71.50% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 62 | | totalSentences | 167 | | matches | | 0 | "Her breath hitched in her" | | 1 | "He knew the streets." | | 2 | "He knew where to run." | | 3 | "She wiped the water away" | | 4 | "He was discarding the evidence." | | 5 | "She pushed off the pavement," | | 6 | "He stopped at a rusted" | | 7 | "He fumbled in his pocket," | | 8 | "He dropped through the opening" | | 9 | "She stared down the hole." | | 10 | "It was not the damp" | | 11 | "It smelled of ozone, copper," | | 12 | "She holstered her sidearm and" | | 13 | "He was young, olive skin" | | 14 | "He held his hands up," | | 15 | "His accent carried the soft" | | 16 | "She recognised the scar running" | | 17 | "He pulled out a small" | | 18 | "He tossed it to her." | | 19 | "It clattered against her palm," |
| | ratio | 0.371 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 160 | | totalSentences | 167 | | matches | | 0 | "Boots slammed against the wet" | | 1 | "Quinn did not slow." | | 2 | "Her breath hitched in her" | | 3 | "The suspect wore a grey" | | 4 | "He knew the streets." | | 5 | "He knew where to run." | | 6 | "Rain lashed against her cropped" | | 7 | "She wiped the water away" | | 8 | "He was discarding the evidence." | | 9 | "She pushed off the pavement," | | 10 | "The suspect turned left into" | | 11 | "Quinn followed, her tactical boots" | | 12 | "The city lights above were" | | 13 | "He stopped at a rusted" | | 14 | "A ventilation shaft for the" | | 15 | "He fumbled in his pocket," | | 16 | "The grate groaned, hinges protesting" | | 17 | "He dropped through the opening" | | 18 | "Quinn skidded to a halt." | | 19 | "She stared down the hole." |
| | ratio | 0.958 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 167 | | matches | (empty) | | ratio | 0 | |
| 47.62% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 30 | | technicalSentenceCount | 4 | | matches | | 0 | "Boots slammed against the wet asphalt, splashing a dark puddle that smelled of diesel and rot." | | 1 | "The suspect wore a grey hooded coat that swallowed his silhouette, merging with the shadows of the Camden archway." | | 2 | "The suspect turned left into a narrow alleyway that reeked of stale beer and urine." | | 3 | "It was a wide, unnatural smile that showed too many teeth." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 19 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 7 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 45 | | tagDensity | 0.156 | | leniency | 0.311 | | rawRatio | 0 | | effectiveRatio | 0 | |