| 94.74% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 14 | | adverbTagCount | 2 | | adverbTags | | 0 | "Rory said faintly [faintly]" | | 1 | "Silas said lightly [lightly]" |
| | dialogueSentences | 38 | | tagDensity | 0.368 | | leniency | 0.737 | | rawRatio | 0.143 | | effectiveRatio | 0.105 | |
| 84.73% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 982 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | 0 | "really" | | 1 | "lightly" | | 2 | "slowly" |
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| 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) | |
| 23.63% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 982 | | totalAiIsms | 15 | | found | | | highlights | | 0 | "flickered" | | 1 | "familiar" | | 2 | "scanned" | | 3 | "silence" | | 4 | "comfortable" | | 5 | "glinting" | | 6 | "eyebrow" | | 7 | "flicker" | | 8 | "pulse" | | 9 | "racing" | | 10 | "unreadable" | | 11 | "tension" | | 12 | "furrowed" | | 13 | "churning" |
| |
| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "flicker of emotion" | | count | 1 |
|
| | highlights | | 0 | "a flicker of recognition" |
| |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 55 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 55 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 79 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 26 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 982 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 7 | | unquotedAttributions | 0 | | matches | (empty) | |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 39 | | wordCount | 704 | | uniqueNames | 6 | | maxNameDensity | 2.56 | | worstName | "Rory" | | maxWindowNameDensity | 5.5 | | worstWindowName | "Rory" | | discoveredNames | | Rory | 18 | | Raven | 1 | | Nest | 1 | | Silas | 12 | | Evan | 6 | | Cardiff | 1 |
| | persons | | 0 | "Rory" | | 1 | "Raven" | | 2 | "Silas" | | 3 | "Evan" |
| | places | | | globalScore | 0.222 | | windowScore | 0 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 46 | | 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 | 982 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 79 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 34 | | mean | 28.88 | | std | 15.05 | | cv | 0.521 | | sampleLengths | | 0 | 65 | | 1 | 45 | | 2 | 28 | | 3 | 14 | | 4 | 39 | | 5 | 46 | | 6 | 15 | | 7 | 15 | | 8 | 21 | | 9 | 44 | | 10 | 10 | | 11 | 42 | | 12 | 30 | | 13 | 9 | | 14 | 20 | | 15 | 27 | | 16 | 41 | | 17 | 12 | | 18 | 36 | | 19 | 21 | | 20 | 30 | | 21 | 28 | | 22 | 14 | | 23 | 17 | | 24 | 11 | | 25 | 10 | | 26 | 35 | | 27 | 14 | | 28 | 21 | | 29 | 46 | | 30 | 57 | | 31 | 52 | | 32 | 45 | | 33 | 22 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 55 | | matches | (empty) | |
| 50.75% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 3 | | totalVerbs | 134 | | matches | | 0 | "was racing" | | 1 | "was reeling" | | 2 | "was just beginning" |
| |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 79 | | ratio | 0 | | matches | (empty) | |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 655 | | adjectiveStacks | 1 | | stackExamples | | 0 | "small crescent-shaped scar" |
| | adverbCount | 24 | | adverbRatio | 0.0366412213740458 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.007633587786259542 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 79 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 79 | | mean | 12.43 | | std | 6.58 | | cv | 0.529 | | sampleLengths | | 0 | 26 | | 1 | 19 | | 2 | 20 | | 3 | 24 | | 4 | 14 | | 5 | 7 | | 6 | 21 | | 7 | 7 | | 8 | 12 | | 9 | 2 | | 10 | 16 | | 11 | 17 | | 12 | 6 | | 13 | 13 | | 14 | 21 | | 15 | 12 | | 16 | 2 | | 17 | 13 | | 18 | 4 | | 19 | 11 | | 20 | 13 | | 21 | 8 | | 22 | 8 | | 23 | 14 | | 24 | 22 | | 25 | 4 | | 26 | 6 | | 27 | 12 | | 28 | 14 | | 29 | 16 | | 30 | 14 | | 31 | 13 | | 32 | 3 | | 33 | 8 | | 34 | 1 | | 35 | 12 | | 36 | 8 | | 37 | 5 | | 38 | 17 | | 39 | 5 | | 40 | 6 | | 41 | 21 | | 42 | 14 | | 43 | 10 | | 44 | 2 | | 45 | 14 | | 46 | 6 | | 47 | 16 | | 48 | 21 | | 49 | 20 |
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| 70.04% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 3 | | diversityRatio | 0.4430379746835443 | | totalSentences | 79 | | uniqueOpeners | 35 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 54 | | matches | (empty) | | ratio | 0 | |
| 57.04% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 22 | | totalSentences | 54 | | matches | | 0 | "Her bright blue eyes scanned" | | 1 | "It had been too long" | | 2 | "She made her way to" | | 3 | "he said, his hazel eyes" | | 4 | "She watched him pour her" | | 5 | "He leaned against the bar," | | 6 | "He tilted his head, studying" | | 7 | "she sighed, running a finger" | | 8 | "He glanced around the bar," | | 9 | "He was tall, with dark" | | 10 | "He paused when he saw" | | 11 | "He stepped closer, and Rory" | | 12 | "He reached out, tucking a" | | 13 | "He noticed, his smile turning" | | 14 | "He turned, striding out of" | | 15 | "He nodded slowly." | | 16 | "He shook his head" | | 17 | "He squeezed her shoulder before" | | 18 | "She knew, with sudden, visceral" | | 19 | "She'd spent too long running," |
| | ratio | 0.407 | |
| 34.07% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 46 | | totalSentences | 54 | | matches | | 0 | "The distinctive green neon sign" | | 1 | "Her bright blue eyes scanned" | | 2 | "It had been too long" | | 3 | "She made her way to" | | 4 | "he said, his hazel eyes" | | 5 | "Rory brushed a strand of" | | 6 | "Silas nodded, his slight limp" | | 7 | "She watched him pour her" | | 8 | "He leaned against the bar," | | 9 | "He tilted his head, studying" | | 10 | "Silas raised an eyebrow." | | 11 | "she sighed, running a finger" | | 12 | "Silas said, his tone neutral" | | 13 | "He glanced around the bar," | | 14 | "Rory hesitated, then nodded." | | 15 | "Silas smiled his thanks before" | | 16 | "Rory stood, rounding the bar" | | 17 | "He was tall, with dark" | | 18 | "He paused when he saw" | | 19 | "Rory froze, her heart stuttering" |
| | ratio | 0.852 | |
| 92.59% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 54 | | matches | | 0 | "If Evan thought he could" |
| | ratio | 0.019 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 31 | | technicalSentenceCount | 1 | | matches | | 0 | "Her bright blue eyes scanned the bar, taking in the old maps and black-and-white photographs that papered the walls." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 14 | | uselessAdditionCount | 4 | | matches | | 0 | "he said, his hazel eyes crinkling at the corners as he smiled" | | 1 | "Silas said, his tone neutral" | | 2 | "Rory's words cut off, his expression unreadable as he took in the scene" | | 3 | "Rory said, her voice tight" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 6 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 38 | | tagDensity | 0.158 | | leniency | 0.316 | | rawRatio | 0.167 | | effectiveRatio | 0.053 | |