| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 22 | | adverbTagCount | 1 | | adverbTags | | 0 | "Eva flipped exactly [exactly]" |
| | dialogueSentences | 53 | | tagDensity | 0.415 | | leniency | 0.83 | | rawRatio | 0.045 | | effectiveRatio | 0.038 | |
| 96.53% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1440 | | 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) | |
| 27.08% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1440 | | totalAiIsms | 21 | | found | | | highlights | | 0 | "echoed" | | 1 | "silence" | | 2 | "weight" | | 3 | "velvet" | | 4 | "sturdy" | | 5 | "fascinating" | | 6 | "perfect" | | 7 | "standard" | | 8 | "traced" | | 9 | "pristine" | | 10 | "chaotic" | | 11 | "complex" | | 12 | "whisper" | | 13 | "vibrated" |
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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 | 97 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 97 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 128 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 37 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1420 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 6 | | unquotedAttributions | 0 | | matches | (empty) | |
| 33.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 51 | | wordCount | 1013 | | uniqueNames | 18 | | maxNameDensity | 1.78 | | worstName | "Quinn" | | maxWindowNameDensity | 4 | | worstWindowName | "Quinn" | | discoveredNames | | Harlow | 1 | | Quinn | 18 | | Camden | 1 | | Veil | 2 | | Market | 1 | | London | 1 | | Collins | 2 | | Two | 2 | | Romanian | 1 | | Eva | 14 | | Kowalski | 1 | | Ancient | 1 | | History | 1 | | Oxford | 1 | | British | 1 | | Museum | 1 | | Shade-crafted | 1 | | Glock | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Collins" | | 3 | "Two" | | 4 | "Eva" | | 5 | "Kowalski" | | 6 | "Museum" |
| | places | | 0 | "Veil" | | 1 | "London" | | 2 | "Ancient" | | 3 | "Oxford" | | 4 | "British" |
| | globalScore | 0.612 | | windowScore | 0.333 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 83 | | glossingSentenceCount | 1 | | matches | | 0 | "sounded like crashing thunder over the ste" |
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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 | 1420 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 128 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 55 | | mean | 25.82 | | std | 21.2 | | cv | 0.821 | | sampleLengths | | 0 | 3 | | 1 | 14 | | 2 | 85 | | 3 | 11 | | 4 | 25 | | 5 | 1 | | 6 | 1 | | 7 | 30 | | 8 | 95 | | 9 | 27 | | 10 | 6 | | 11 | 32 | | 12 | 51 | | 13 | 11 | | 14 | 57 | | 15 | 2 | | 16 | 5 | | 17 | 56 | | 18 | 55 | | 19 | 24 | | 20 | 14 | | 21 | 11 | | 22 | 2 | | 23 | 33 | | 24 | 12 | | 25 | 28 | | 26 | 10 | | 27 | 31 | | 28 | 1 | | 29 | 17 | | 30 | 12 | | 31 | 32 | | 32 | 39 | | 33 | 30 | | 34 | 31 | | 35 | 25 | | 36 | 34 | | 37 | 19 | | 38 | 1 | | 39 | 18 | | 40 | 26 | | 41 | 80 | | 42 | 5 | | 43 | 29 | | 44 | 4 | | 45 | 48 | | 46 | 27 | | 47 | 34 | | 48 | 45 | | 49 | 11 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 97 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 156 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 128 | | ratio | 0 | | matches | (empty) | |
| 64.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1030 | | adjectiveStacks | 6 | | stackExamples | | 0 | "hideous large old square" | | 1 | "green Shade-crafted brass" | | 2 | "thick leather-bound reference" | | 3 | "heavy rubber-soled boots" | | 4 | "liquid zig-zagged uphill" | | 5 | "twisted, impossible jagged shapes" |
| | adverbCount | 18 | | adverbRatio | 0.017475728155339806 | | lyAdverbCount | 8 | | lyAdverbRatio | 0.007766990291262136 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 128 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 128 | | mean | 11.09 | | std | 6.24 | | cv | 0.562 | | sampleLengths | | 0 | 3 | | 1 | 14 | | 2 | 8 | | 3 | 15 | | 4 | 13 | | 5 | 5 | | 6 | 14 | | 7 | 11 | | 8 | 19 | | 9 | 9 | | 10 | 1 | | 11 | 1 | | 12 | 17 | | 13 | 8 | | 14 | 1 | | 15 | 1 | | 16 | 11 | | 17 | 4 | | 18 | 15 | | 19 | 10 | | 20 | 8 | | 21 | 12 | | 22 | 9 | | 23 | 30 | | 24 | 13 | | 25 | 7 | | 26 | 6 | | 27 | 9 | | 28 | 18 | | 29 | 6 | | 30 | 21 | | 31 | 11 | | 32 | 12 | | 33 | 10 | | 34 | 13 | | 35 | 16 | | 36 | 11 | | 37 | 11 | | 38 | 16 | | 39 | 7 | | 40 | 7 | | 41 | 6 | | 42 | 10 | | 43 | 2 | | 44 | 5 | | 45 | 20 | | 46 | 36 | | 47 | 5 | | 48 | 7 | | 49 | 10 |
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| 65.89% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 9 | | diversityRatio | 0.4375 | | totalSentences | 128 | | uniqueOpeners | 56 | |
| 35.84% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 93 | | matches | | 0 | "Only a fool touched cursed" |
| | ratio | 0.011 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 26 | | totalSentences | 93 | | matches | | 0 | "Its nomadic merchants usually brought" | | 1 | "They moved their bizarre stalls" | | 2 | "They sold banned alchemical substances," | | 3 | "She catalogued every detail with" | | 4 | "She possessed a master's degree" | | 5 | "She worked deep inside the" | | 6 | "She stared unblinking at the" | | 7 | "She popped the brass buckles," | | 8 | "She slipped them on with" | | 9 | "She knelt beside the pooling" | | 10 | "She sniffed the charred fabric" | | 11 | "She inspected the merchant's soot-stained" | | 12 | "They hung inside out, emptied" | | 13 | "She spotted a telltale glimmer" | | 14 | "She ran her finger down" | | 15 | "It spun in a violent," | | 16 | "His heavy rubber-soled boots echoed" | | 17 | "She noticed a bizarre environmental" | | 18 | "It crept over the dirty" | | 19 | "Her confident voice dropped to" |
| | ratio | 0.28 | |
| 3.01% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 85 | | totalSentences | 93 | | matches | | 0 | "Detective Harlow Quinn stepped over" | | 1 | "Water dripped from the vaulted" | | 2 | "The damp pitter-patter echoed through" | | 3 | "The stagnant underground air tasted" | | 4 | "Its nomadic merchants usually brought" | | 5 | "They moved their bizarre stalls" | | 6 | "They sold banned alchemical substances," | | 7 | "A public dismemberment broke their" | | 8 | "PC Collins shined a blinding" | | 9 | "Quinn checked her worn leather" | | 10 | "Quinn walked a slow, deliberate" | | 11 | "She catalogued every detail with" | | 12 | "The dead victim wore a" | | 13 | "A small fortune in black" | | 14 | "Opportunists sweep expensive tables clean" | | 15 | "The killer ignored the valuable" | | 16 | "Someone ducked under the plastic" | | 17 | "Quinn squared her shoulders" | | 18 | "Eva Kowalski tucked a stubborn" | | 19 | "Eva adjusted her round wire-rimmed" |
| | ratio | 0.914 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 93 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 42 | | technicalSentenceCount | 1 | | matches | | 0 | "They stretched across the platform floor, forming twisted, impossible jagged shapes that defied human geometry." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 22 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 2 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 53 | | tagDensity | 0.038 | | leniency | 0.075 | | rawRatio | 0.5 | | effectiveRatio | 0.038 | |