| 18.18% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 11 | | adverbTagCount | 2 | | adverbTags | | 0 | "She glanced away [away]" | | 1 | "he said gently [gently]" |
| | dialogueSentences | 22 | | tagDensity | 0.5 | | leniency | 1 | | rawRatio | 0.182 | | effectiveRatio | 0.182 | |
| 88.07% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 838 | | totalAiIsmAdverbs | 2 | | found | | | highlights | | |
| 100.00% | AI-ism character names | Target: 0 AI-default names (16 tracked, −20% each) | | codexExemptions | | | found | (empty) | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 0.00% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 838 | | totalAiIsms | 18 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | word | "carried the weight" | | count | 1 |
| | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | | | 13 | | | 14 | | | 15 | |
| | highlights | | 0 | "familiar" | | 1 | "gloom" | | 2 | "pulsed" | | 3 | "sanctuary" | | 4 | "whisper" | | 5 | "warmth" | | 6 | "carried the weight" | | 7 | "sense of" | | 8 | "reminder" | | 9 | "fascinating" | | 10 | "glinting" | | 11 | "constructed" | | 12 | "intensity" | | 13 | "resonance" | | 14 | "comforting" | | 15 | "clandestine" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "hung in the air" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 35 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 35 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 46 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 40 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 832 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 8 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 10 | | wordCount | 540 | | uniqueNames | 2 | | maxNameDensity | 0.93 | | worstName | "Aurora" | | maxWindowNameDensity | 2 | | worstWindowName | "Silas" | | discoveredNames | | | persons | | | places | (empty) | | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 31 | | 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 | 832 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 46 | | matches | (empty) | |
| 39.47% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 17 | | mean | 48.94 | | std | 14.1 | | cv | 0.288 | | sampleLengths | | 0 | 85 | | 1 | 61 | | 2 | 30 | | 3 | 46 | | 4 | 39 | | 5 | 48 | | 6 | 68 | | 7 | 42 | | 8 | 40 | | 9 | 38 | | 10 | 55 | | 11 | 25 | | 12 | 61 | | 13 | 57 | | 14 | 47 | | 15 | 44 | | 16 | 46 |
| |
| 85.21% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 35 | | matches | | 0 | "was unchanged" | | 1 | "was unchanged" |
| |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 77 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 46 | | ratio | 0 | | matches | (empty) | |
| 88.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 242 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 13 | | adverbRatio | 0.05371900826446281 | | lyAdverbCount | 1 | | lyAdverbRatio | 0.004132231404958678 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 46 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 46 | | mean | 18.09 | | std | 7.72 | | cv | 0.427 | | sampleLengths | | 0 | 18 | | 1 | 12 | | 2 | 30 | | 3 | 25 | | 4 | 11 | | 5 | 19 | | 6 | 31 | | 7 | 19 | | 8 | 11 | | 9 | 11 | | 10 | 21 | | 11 | 14 | | 12 | 10 | | 13 | 18 | | 14 | 11 | | 15 | 14 | | 16 | 14 | | 17 | 20 | | 18 | 21 | | 19 | 13 | | 20 | 19 | | 21 | 15 | | 22 | 25 | | 23 | 17 | | 24 | 10 | | 25 | 30 | | 26 | 19 | | 27 | 19 | | 28 | 8 | | 29 | 23 | | 30 | 24 | | 31 | 19 | | 32 | 6 | | 33 | 5 | | 34 | 40 | | 35 | 16 | | 36 | 16 | | 37 | 19 | | 38 | 22 | | 39 | 9 | | 40 | 38 | | 41 | 13 | | 42 | 23 | | 43 | 8 | | 44 | 28 | | 45 | 18 |
| |
| 86.23% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 2 | | diversityRatio | 0.5434782608695652 | | totalSentences | 46 | | uniqueOpeners | 25 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 35 | | matches | (empty) | | ratio | 0 | |
| 2.86% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 19 | | totalSentences | 35 | | matches | | 0 | "She moved deeper into the" | | 1 | "She hadn't expected this face" | | 2 | "she asked, her voice a" | | 3 | "he finished for her, his" | | 4 | "His once keen hazel eyes" | | 5 | "His laugh, rich and deep," | | 6 | "She noted the slight strain" | | 7 | "She chuckled, the sound taking" | | 8 | "His keen mind, his endless" | | 9 | "He poured two whiskies, the" | | 10 | "She shrugged, lifting the glass" | | 11 | "His tone was as dry" | | 12 | "she admitted, her tone light" | | 13 | "He tilted his head, studying" | | 14 | "Her throat tightened at his" | | 15 | "She glanced away, focusing on" | | 16 | "he said gently" | | 17 | "It held a new resonance" | | 18 | "She sipped her whisky" |
| | ratio | 0.543 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 34 | | totalSentences | 35 | | matches | | 0 | "Aurora slipped into" | | 1 | "The music pulsed outside, a" | | 2 | "The cloying, sweet fragrance of" | | 3 | "She moved deeper into the" | | 4 | "The voice, gravelly and warm" | | 5 | "Aurora stilled, staring at the" | | 6 | "She hadn't expected this face" | | 7 | "she asked, her voice a" | | 8 | "he finished for her, his" | | 9 | "His once keen hazel eyes" | | 10 | "Aurora nodded, feeling a sense" | | 11 | "The memory of her past" | | 12 | "His laugh, rich and deep," | | 13 | "She noted the slight strain" | | 14 | "She chuckled, the sound taking" | | 15 | "Silas had been her father's" | | 16 | "His keen mind, his endless" | | 17 | "Time had tempered his disposition," | | 18 | "He poured two whiskies, the" | | 19 | "She shrugged, lifting the glass" |
| | ratio | 0.971 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 35 | | matches | (empty) | | ratio | 0 | |
| 0.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 21 | | technicalSentenceCount | 5 | | matches | | 0 | "The cloying, sweet fragrance of coconut and lime hung in the air, a heady contrast to the musty smell of old tomes and faded photographs that were the bar's hal…" | | 1 | "Aurora stilled, staring at the unfamiliar face, her mind searching for a name to pair with the broad smile." | | 2 | "His once keen hazel eyes held a warmth that hadn't diminished but now also carried the weight of many tales untold." | | 3 | "Free-spirited and impetuous, she had challenged every authority figure that had crossed her path, from teachers to corrupt politicians, never once backing down." | | 4 | "Silas inclined his head towards the hidden room at the back, the room that had served as a centre of clandestine meetings and countless conspiracies over the ye…" |
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| 79.55% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 11 | | uselessAdditionCount | 1 | | matches | | 0 | "he finished, his smile turning a hint wistful" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 3 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 22 | | tagDensity | 0.136 | | leniency | 0.273 | | rawRatio | 0.333 | | effectiveRatio | 0.091 | |