| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 10 | | adverbTagCount | 1 | | adverbTags | | 0 | "She leaned back [back]" |
| | dialogueSentences | 48 | | tagDensity | 0.208 | | leniency | 0.417 | | rawRatio | 0.1 | | effectiveRatio | 0.042 | |
| 95.55% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1124 | | totalAiIsmAdverbs | 1 | | 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 | 1124 | | totalAiIsms | 29 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | | | 13 | | | 14 | | | 15 | | | 16 | | | 17 | | | 18 | | | 19 | | | 20 | | | 21 | | | 22 | | | 23 | | | 24 | |
| | highlights | | 0 | "scanning" | | 1 | "familiar" | | 2 | "charm" | | 3 | "measured" | | 4 | "lilt" | | 5 | "tracing" | | 6 | "raced" | | 7 | "flickered" | | 8 | "unspoken" | | 9 | "reminder" | | 10 | "unreadable" | | 11 | "calculating" | | 12 | "silence" | | 13 | "traced" | | 14 | "navigate" | | 15 | "flicker" | | 16 | "intensity" | | 17 | "palpable" | | 18 | "echoing" | | 19 | "weight" | | 20 | "tension" | | 21 | "sense of" | | 22 | "unwavering" | | 23 | "warmth" | | 24 | "loomed" |
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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 | 1 | | narrationSentences | 71 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 71 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 107 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 32 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1112 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 4 | | unquotedAttributions | 0 | | matches | (empty) | |
| 95.91% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 28 | | wordCount | 832 | | uniqueNames | 6 | | maxNameDensity | 1.08 | | worstName | "Rory" | | maxWindowNameDensity | 2 | | worstWindowName | "Evan" | | discoveredNames | | Rory | 9 | | Raven | 1 | | Nest | 1 | | Evan | 9 | | Memories | 1 | | Silas | 7 |
| | persons | | 0 | "Rory" | | 1 | "Raven" | | 2 | "Evan" | | 3 | "Silas" |
| | places | (empty) | | globalScore | 0.959 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 62 | | glossingSentenceCount | 1 | | matches | | 0 | "as if releasing a weight he’d been carrying for years" |
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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 | 1112 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 107 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 51 | | mean | 21.8 | | std | 17.69 | | cv | 0.811 | | sampleLengths | | 0 | 108 | | 1 | 56 | | 2 | 52 | | 3 | 32 | | 4 | 19 | | 5 | 19 | | 6 | 27 | | 7 | 14 | | 8 | 7 | | 9 | 7 | | 10 | 12 | | 11 | 16 | | 12 | 24 | | 13 | 28 | | 14 | 28 | | 15 | 2 | | 16 | 29 | | 17 | 19 | | 18 | 6 | | 19 | 11 | | 20 | 16 | | 21 | 21 | | 22 | 10 | | 23 | 11 | | 24 | 8 | | 25 | 59 | | 26 | 9 | | 27 | 11 | | 28 | 14 | | 29 | 2 | | 30 | 21 | | 31 | 19 | | 32 | 25 | | 33 | 16 | | 34 | 32 | | 35 | 23 | | 36 | 31 | | 37 | 17 | | 38 | 5 | | 39 | 19 | | 40 | 7 | | 41 | 19 | | 42 | 42 | | 43 | 14 | | 44 | 25 | | 45 | 10 | | 46 | 18 | | 47 | 23 | | 48 | 19 | | 49 | 6 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 71 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 157 | | matches | (empty) | |
| 9.35% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 7 | | semicolonCount | 0 | | flaggedSentences | 5 | | totalSentences | 107 | | ratio | 0.047 | | matches | | 0 | "The angle of his jaw, the way he carried himself—she knew that posture, that familiar tilt of the head." | | 1 | "He wore a tailored suit, the kind that spoke of money and power, and his eyes—those piercing grey eyes—locked onto hers the moment they met." | | 2 | "Memories she’d buried came rushing back—the late-night phone calls, the promises, the fights." | | 3 | "She’d imagined this moment countless times—what she’d say, how she’d feel." | | 4 | "The past was behind her now, a chapter closed, but the future—raw and uncertain—loomed ahead." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 843 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 25 | | adverbRatio | 0.02965599051008304 | | lyAdverbCount | 10 | | lyAdverbRatio | 0.011862396204033215 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 107 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 107 | | mean | 10.39 | | std | 5.88 | | cv | 0.566 | | sampleLengths | | 0 | 18 | | 1 | 18 | | 2 | 22 | | 3 | 21 | | 4 | 13 | | 5 | 16 | | 6 | 10 | | 7 | 16 | | 8 | 8 | | 9 | 19 | | 10 | 3 | | 11 | 3 | | 12 | 3 | | 13 | 21 | | 14 | 25 | | 15 | 14 | | 16 | 18 | | 17 | 13 | | 18 | 6 | | 19 | 7 | | 20 | 12 | | 21 | 10 | | 22 | 13 | | 23 | 4 | | 24 | 9 | | 25 | 5 | | 26 | 5 | | 27 | 2 | | 28 | 7 | | 29 | 9 | | 30 | 3 | | 31 | 14 | | 32 | 2 | | 33 | 18 | | 34 | 6 | | 35 | 15 | | 36 | 13 | | 37 | 14 | | 38 | 14 | | 39 | 2 | | 40 | 12 | | 41 | 8 | | 42 | 9 | | 43 | 19 | | 44 | 6 | | 45 | 4 | | 46 | 7 | | 47 | 6 | | 48 | 10 | | 49 | 21 |
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| 64.17% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 3 | | diversityRatio | 0.40186915887850466 | | totalSentences | 107 | | uniqueOpeners | 43 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 71 | | matches | (empty) | | ratio | 0 | |
| 0.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 40 | | totalSentences | 71 | | matches | | 0 | "He glanced up, nodded once," | | 1 | "She’d barely settled in when" | | 2 | "He hesitated, scanning the room," | | 3 | "It was Evan." | | 4 | "Her breath caught." | | 5 | "His once unruly blond hair" | | 6 | "He wore a tailored suit," | | 7 | "He strode over, his steps" | | 8 | "His voice was deeper now," | | 9 | "She leaned back, her fingers" | | 10 | "He shrugged, a gesture that" | | 11 | "Her tone was light, but" | | 12 | "She studied him, searching for" | | 13 | "His gaze flickered to her" | | 14 | "She took a sip of" | | 15 | "His voice was tight, as" | | 16 | "He paused as Silas returned" | | 17 | "She didn’t elaborate, didn’t mention" | | 18 | "She shook her head." | | 19 | "He studied her, his gaze" |
| | ratio | 0.563 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 68 | | totalSentences | 71 | | matches | | 0 | "The green neon sign buzzed" | | 1 | "The smell of aged whiskey" | | 2 | "The bar was quiet tonight," | | 3 | "Silas stood behind the counter," | | 4 | "He glanced up, nodded once," | | 5 | "Rory headed for her usual" | | 6 | "She’d barely settled in when" | | 7 | "A man stepped in, tall" | | 8 | "He hesitated, scanning the room," | | 9 | "The angle of his jaw," | | 10 | "It was Evan." | | 11 | "Her breath caught." | | 12 | "Evan looked different." | | 13 | "His once unruly blond hair" | | 14 | "He wore a tailored suit," | | 15 | "He strode over, his steps" | | 16 | "His voice was deeper now," | | 17 | "She leaned back, her fingers" | | 18 | "He shrugged, a gesture that" | | 19 | "Her tone was light, but" |
| | ratio | 0.958 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 71 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 36 | | technicalSentenceCount | 2 | | matches | | 0 | "Silas stood behind the counter, polishing a glass with the meticulous precision of a man who took pride in his craft." | | 1 | "He let out a slow breath, as if releasing a weight he’d been carrying for years." |
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| 25.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 10 | | uselessAdditionCount | 2 | | matches | | 0 | "She leaned back, her fingers tracing the crescent-shaped scar on her wrist" | | 1 | "She took, the bitterness grounding her" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |