| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 2 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 2 | | tagDensity | 1 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 93.86% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 814 | | 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) | |
| 57.00% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 814 | | totalAiIsms | 7 | | found | | | highlights | | 0 | "silence" | | 1 | "crystal" | | 2 | "echo" | | 3 | "weight" | | 4 | "rhythmic" | | 5 | "pulse" |
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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 | 71 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 71 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 71 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 38 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 3 | | markdownWords | 7 | | totalWords | 814 | | ratio | 0.009 | | matches | | 0 | "Tick-tock." | | 1 | "Drag. Drag. Tap." | | 2 | "Drag. Drag. Tap." |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 3 | | unquotedAttributions | 0 | | matches | (empty) | |
| 88.20% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 20 | | wordCount | 809 | | uniqueNames | 11 | | maxNameDensity | 1.24 | | worstName | "Rory" | | maxWindowNameDensity | 2 | | worstWindowName | "Rory" | | discoveredNames | | Richmond | 1 | | Grove | 1 | | London | 1 | | Heathrow | 1 | | Soho | 1 | | Canary | 1 | | Wharf | 1 | | Cardiff | 1 | | Law | 1 | | Rory | 10 | | Heartstone | 1 |
| | persons | | | places | | 0 | "Richmond" | | 1 | "Grove" | | 2 | "London" | | 3 | "Heathrow" | | 4 | "Soho" | | 5 | "Canary" | | 6 | "Cardiff" |
| | globalScore | 0.882 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 54 | | glossingSentenceCount | 1 | | matches | | 0 | "sounded like a wet finger rubbing the rim" |
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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 | 814 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 71 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 33 | | mean | 24.67 | | std | 18.63 | | cv | 0.755 | | sampleLengths | | 0 | 17 | | 1 | 39 | | 2 | 35 | | 3 | 59 | | 4 | 7 | | 5 | 52 | | 6 | 30 | | 7 | 7 | | 8 | 31 | | 9 | 12 | | 10 | 4 | | 11 | 15 | | 12 | 66 | | 13 | 11 | | 14 | 23 | | 15 | 44 | | 16 | 11 | | 17 | 10 | | 18 | 22 | | 19 | 3 | | 20 | 35 | | 21 | 3 | | 22 | 40 | | 23 | 9 | | 24 | 29 | | 25 | 7 | | 26 | 13 | | 27 | 56 | | 28 | 3 | | 29 | 9 | | 30 | 60 | | 31 | 17 | | 32 | 35 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 71 | | matches | (empty) | |
| 98.22% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 131 | | matches | | 0 | "were plunging" | | 1 | "were not springing" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 71 | | ratio | 0 | | matches | (empty) | |
| 76.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 816 | | adjectiveStacks | 4 | | stackExamples | | 0 | "central flat-topped granite" | | 1 | "small crescent-shaped scar" | | 2 | "frantic, rhythmic red pulse" | | 3 | "translucent, human-sized molars." |
| | adverbCount | 19 | | adverbRatio | 0.023284313725490197 | | lyAdverbCount | 7 | | lyAdverbRatio | 0.00857843137254902 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 71 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 71 | | mean | 11.46 | | std | 7.79 | | cv | 0.679 | | sampleLengths | | 0 | 17 | | 1 | 24 | | 2 | 15 | | 3 | 7 | | 4 | 28 | | 5 | 11 | | 6 | 37 | | 7 | 11 | | 8 | 7 | | 9 | 8 | | 10 | 21 | | 11 | 3 | | 12 | 20 | | 13 | 9 | | 14 | 21 | | 15 | 7 | | 16 | 13 | | 17 | 18 | | 18 | 5 | | 19 | 7 | | 20 | 4 | | 21 | 12 | | 22 | 3 | | 23 | 9 | | 24 | 23 | | 25 | 15 | | 26 | 19 | | 27 | 11 | | 28 | 4 | | 29 | 4 | | 30 | 15 | | 31 | 10 | | 32 | 25 | | 33 | 9 | | 34 | 11 | | 35 | 10 | | 36 | 2 | | 37 | 8 | | 38 | 3 | | 39 | 9 | | 40 | 1 | | 41 | 1 | | 42 | 1 | | 43 | 6 | | 44 | 5 | | 45 | 8 | | 46 | 14 | | 47 | 2 | | 48 | 3 | | 49 | 8 |
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| 61.03% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 5 | | diversityRatio | 0.4084507042253521 | | totalSentences | 71 | | uniqueOpeners | 29 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 63 | | matches | | 0 | "Instead of damp sweetness, a" | | 1 | "Just grey mist curling around" |
| | ratio | 0.032 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 15 | | totalSentences | 63 | | matches | | 0 | "She shook her hair back" | | 1 | "They smelled wrong." | | 2 | "She paused, lifting her chin" | | 3 | "It sounded like a wet" | | 4 | "She kept moving toward the" | | 5 | "She glanced down at the" | | 6 | "She wanted this done." | | 7 | "It had cadence." | | 8 | "She listened, tracking the rhythm." | | 9 | "It stopped four paces behind" | | 10 | "She spun around." | | 11 | "They remained flattened, crushed beneath" | | 12 | "They did not move with" | | 13 | "They crept forward against the" | | 14 | "It had no eyes, only" |
| | ratio | 0.238 | |
| 47.30% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 52 | | totalSentences | 63 | | matches | | 0 | "Aurora jammed her boot into" | | 1 | "The rough bark scraped her" | | 2 | "She shook her hair back" | | 3 | "Silence fell like a dropcloth" | | 4 | "The distant hum of the" | | 5 | "The oilskin packet in her" | | 6 | "Silas had given clear instructions" | | 7 | "Rory took three paces into" | | 8 | "Bluebells and pale white anemones" | | 9 | "They smelled wrong." | | 10 | "She paused, lifting her chin" | | 11 | "The ancient oaks ringed the" | | 12 | "A sound brushed past her" | | 13 | "It sounded like a wet" | | 14 | "Rory pivoted, the small crescent-shaped" | | 15 | "Nothing stood among the ferns." | | 16 | "Rory called out" | | 17 | "The name dropped flat onto" | | 18 | "She kept moving toward the" | | 19 | "She glanced down at the" |
| | ratio | 0.825 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 63 | | matches | (empty) | | ratio | 0 | |
| 58.82% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 34 | | technicalSentenceCount | 4 | | matches | | 0 | "Bluebells and pale white anemones crowded her ankles, blooming in thick clusters that defied the frost clinging to the park outside." | | 1 | "With every step, her inner ear popped, the pressure dropping as if she were plunging down an express lift shaft in Canary Wharf." | | 2 | "Rory stepped closer, her boots squelching on ground that looked bone-dry." | | 3 | "They remained flattened, crushed beneath an invisible weight that forged a direct, unbroken trail from the perimeter stones straight to where she stood." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 2 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 1 | | fancyCount | 1 | | fancyTags | | 0 | "Rory muttered (mutter)" |
| | dialogueSentences | 2 | | tagDensity | 0.5 | | leniency | 1 | | rawRatio | 1 | | effectiveRatio | 1 | |