| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 24 | | adverbTagCount | 1 | | adverbTags | | 0 | "Aurora's voice cracked just [just]" |
| | dialogueSentences | 60 | | tagDensity | 0.4 | | leniency | 0.8 | | rawRatio | 0.042 | | effectiveRatio | 0.033 | |
| 90.72% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1617 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | 0 | "suddenly" | | 1 | "carefully" | | 2 | "slightly" |
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| 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) | |
| 41.25% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1617 | | totalAiIsms | 19 | | found | | | highlights | | 0 | "echoing" | | 1 | "throbbed" | | 2 | "weight" | | 3 | "chill" | | 4 | "navigating" | | 5 | "etched" | | 6 | "glint" | | 7 | "tension" | | 8 | "silence" | | 9 | "could feel" | | 10 | "tangible" | | 11 | "constructed" | | 12 | "amidst" | | 13 | "tinged" | | 14 | "loomed" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 2 | | maxInWindow | 1 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 1 |
| | 1 | | label | "sent a shiver through" | | count | 1 |
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| | highlights | | 0 | "eyes widened" | | 1 | "sent a jolt through" |
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| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 83 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 83 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 119 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 46 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1609 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 17 | | unquotedAttributions | 0 | | matches | (empty) | |
| 79.18% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 36 | | wordCount | 1059 | | uniqueNames | 9 | | maxNameDensity | 1.42 | | worstName | "Lucien" | | maxWindowNameDensity | 2 | | worstWindowName | "Aurora" | | discoveredNames | | Brick | 1 | | Lane | 1 | | Aurora | 12 | | Carter | 1 | | Moreau | 1 | | Ptolemy | 3 | | Pots | 1 | | Lucien | 15 | | Marseille | 1 |
| | persons | | 0 | "Aurora" | | 1 | "Carter" | | 2 | "Moreau" | | 3 | "Ptolemy" | | 4 | "Pots" | | 5 | "Lucien" |
| | places | | 0 | "Brick" | | 1 | "Lane" | | 2 | "Marseille" |
| | globalScore | 0.792 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 69 | | 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 | 1609 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 119 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 48 | | mean | 33.52 | | std | 20.37 | | cv | 0.608 | | sampleLengths | | 0 | 78 | | 1 | 63 | | 2 | 27 | | 3 | 39 | | 4 | 4 | | 5 | 61 | | 6 | 4 | | 7 | 14 | | 8 | 43 | | 9 | 35 | | 10 | 4 | | 11 | 55 | | 12 | 67 | | 13 | 43 | | 14 | 40 | | 15 | 24 | | 16 | 33 | | 17 | 4 | | 18 | 57 | | 19 | 18 | | 20 | 69 | | 21 | 33 | | 22 | 10 | | 23 | 28 | | 24 | 59 | | 25 | 60 | | 26 | 28 | | 27 | 26 | | 28 | 21 | | 29 | 27 | | 30 | 6 | | 31 | 47 | | 32 | 67 | | 33 | 29 | | 34 | 9 | | 35 | 20 | | 36 | 36 | | 37 | 67 | | 38 | 13 | | 39 | 41 | | 40 | 29 | | 41 | 18 | | 42 | 32 | | 43 | 36 | | 44 | 13 | | 45 | 27 | | 46 | 3 | | 47 | 42 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 83 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 171 | | matches | (empty) | |
| 94.84% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 3 | | semicolonCount | 0 | | flaggedSentences | 2 | | totalSentences | 119 | | ratio | 0.017 | | matches | | 0 | "His heterochromatic eyes—one amber, one void-black—locked onto hers without blinking." | | 1 | "The ambient noise of the city outside—the sirens, the distant traffic, the muffled voices from the curry house—seemed to drop away." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1066 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 37 | | adverbRatio | 0.03470919324577861 | | lyAdverbCount | 10 | | lyAdverbRatio | 0.009380863039399626 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 119 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 119 | | mean | 13.52 | | std | 7.91 | | cv | 0.585 | | sampleLengths | | 0 | 20 | | 1 | 3 | | 2 | 15 | | 3 | 32 | | 4 | 8 | | 5 | 21 | | 6 | 14 | | 7 | 18 | | 8 | 10 | | 9 | 6 | | 10 | 16 | | 11 | 5 | | 12 | 11 | | 13 | 21 | | 14 | 7 | | 15 | 4 | | 16 | 7 | | 17 | 5 | | 18 | 22 | | 19 | 24 | | 20 | 3 | | 21 | 4 | | 22 | 14 | | 23 | 17 | | 24 | 18 | | 25 | 8 | | 26 | 14 | | 27 | 21 | | 28 | 4 | | 29 | 25 | | 30 | 15 | | 31 | 15 | | 32 | 18 | | 33 | 6 | | 34 | 3 | | 35 | 11 | | 36 | 17 | | 37 | 12 | | 38 | 21 | | 39 | 12 | | 40 | 10 | | 41 | 25 | | 42 | 15 | | 43 | 15 | | 44 | 9 | | 45 | 3 | | 46 | 21 | | 47 | 9 | | 48 | 4 | | 49 | 5 |
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| 62.75% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 2 | | diversityRatio | 0.3865546218487395 | | totalSentences | 119 | | uniqueOpeners | 46 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 81 | | matches | (empty) | | ratio | 0 | |
| 71.85% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 30 | | totalSentences | 81 | | matches | | 0 | "She wore an apron stained" | | 1 | "Her bright blue eyes widened," | | 2 | "He leaned heavily on his" | | 3 | "His heterochromatic eyes—one amber, one" | | 4 | "His voice carried that smooth," | | 5 | "She didn't step back" | | 6 | "She didn't invite him in." | | 7 | "She finally stepped back, but" | | 8 | "She let him step inside," | | 9 | "He filled the small space" | | 10 | "She turned her back on" | | 11 | "She froze, her hand hovering" | | 12 | "He stopped an arm's length" | | 13 | "She found only a raw," | | 14 | "She gestured at his soaked" | | 15 | "His touch was light, careful," | | 16 | "she said, her voice quieter" | | 17 | "He met her gaze, unflinching" | | 18 | "She looked at the three" | | 19 | "He took another step, closing" |
| | ratio | 0.37 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 75 | | totalSentences | 81 | | matches | | 0 | "The chain rattled." | | 1 | "The door swung inward, revealing" | | 2 | "She wore an apron stained" | | 3 | "Her bright blue eyes widened," | | 4 | "Lucien Moreau stood on the" | | 5 | "He leaned heavily on his" | | 6 | "Rain dripped from the brim" | | 7 | "His heterochromatic eyes—one amber, one" | | 8 | "His voice carried that smooth," | | 9 | "Aurora gripped the edge of" | | 10 | "The small crescent scar on" | | 11 | "She didn't step back" | | 12 | "She didn't invite him in." | | 13 | "The cramped hallway behind her" | | 14 | "A tabby cat named Ptolemy" | | 15 | "Lucien shifted his weight, wincing" | | 16 | "The movement drew her eye" | | 17 | "Aurora's voice cracked, just once," | | 18 | "She finally stepped back, but" | | 19 | "The warm, stuffy air of" |
| | ratio | 0.926 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 81 | | matches | (empty) | | ratio | 0 | |
| 71.43% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 40 | | technicalSentenceCount | 4 | | matches | | 0 | "His voice carried that smooth, trans-Atlantic cadence that used to make her forget her own name." | | 1 | "A tabby cat named Ptolemy wound itself around her ankles, weaving through her legs and letting out a low, suspicious meow at the stranger." | | 2 | "The anger still simmered in her chest, hot and bright, but beneath it lay the old ache, the memory of rainy nights in Marseille and conversations that lasted un…" | | 3 | "He placed it on the table, smoothing it out next to Ptolemy, who sniffed it suspiciously before retreating." |
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| 62.50% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 24 | | uselessAdditionCount | 3 | | matches | | 0 | "she said, her voice quieter now" | | 1 | "she said, her voice steady despite the tremor in her hands," | | 2 | "Lucien said, his voice dropping to a murmur" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 7 | | fancyCount | 1 | | fancyTags | | 0 | "Lucien whispered (whisper)" |
| | dialogueSentences | 60 | | tagDensity | 0.117 | | leniency | 0.233 | | rawRatio | 0.143 | | effectiveRatio | 0.033 | |