| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 16 | | adverbTagCount | 2 | | adverbTags | | 0 | "she said finally [finally]" | | 1 | "he said quietly [quietly]" |
| | dialogueSentences | 71 | | tagDensity | 0.225 | | leniency | 0.451 | | rawRatio | 0.125 | | effectiveRatio | 0.056 | |
| 93.09% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1447 | | totalAiIsmAdverbs | 2 | | found | | | highlights | | |
| 80.00% | AI-ism character names | Target: 0 AI-default names (16 tracked, −20% each) | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 82.72% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1447 | | totalAiIsms | 5 | | found | | | highlights | | 0 | "scanned" | | 1 | "weight" | | 2 | "tracing" | | 3 | "flicker" | | 4 | "silence" |
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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 | 98 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 98 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 153 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 37 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1441 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 20 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 24 | | wordCount | 888 | | uniqueNames | 10 | | maxNameDensity | 0.79 | | worstName | "Danny" | | maxWindowNameDensity | 2 | | worstWindowName | "Danny" | | discoveredNames | | November | 1 | | London | 3 | | Pierce | 1 | | Cardiff | 1 | | Evan | 1 | | Tuesday | 1 | | Closed | 1 | | Danny | 7 | | Paris | 1 | | Rory | 7 |
| | persons | | 0 | "Pierce" | | 1 | "Evan" | | 2 | "Danny" | | 3 | "Rory" |
| | places | | 0 | "London" | | 1 | "Cardiff" | | 2 | "Paris" |
| | globalScore | 1 | | windowScore | 1 | |
| 68.03% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 61 | | glossingSentenceCount | 2 | | matches | | 0 | "quite reach his eyes" | | 1 | "looked like the boy she'd known—the one w" |
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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 | 1441 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 153 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 82 | | mean | 17.57 | | std | 15.4 | | cv | 0.876 | | sampleLengths | | 0 | 10 | | 1 | 30 | | 2 | 27 | | 3 | 2 | | 4 | 49 | | 5 | 3 | | 6 | 22 | | 7 | 2 | | 8 | 6 | | 9 | 52 | | 10 | 35 | | 11 | 2 | | 12 | 11 | | 13 | 14 | | 14 | 3 | | 15 | 43 | | 16 | 5 | | 17 | 3 | | 18 | 16 | | 19 | 60 | | 20 | 15 | | 21 | 16 | | 22 | 7 | | 23 | 11 | | 24 | 2 | | 25 | 30 | | 26 | 54 | | 27 | 25 | | 28 | 5 | | 29 | 21 | | 30 | 1 | | 31 | 16 | | 32 | 18 | | 33 | 9 | | 34 | 7 | | 35 | 32 | | 36 | 31 | | 37 | 5 | | 38 | 32 | | 39 | 35 | | 40 | 5 | | 41 | 31 | | 42 | 12 | | 43 | 23 | | 44 | 2 | | 45 | 13 | | 46 | 36 | | 47 | 2 | | 48 | 3 | | 49 | 1 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 98 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 177 | | matches | | 0 | "was wiping" | | 1 | "was getting" |
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| 68.16% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 5 | | semicolonCount | 0 | | flaggedSentences | 4 | | totalSentences | 153 | | ratio | 0.026 | | matches | | 0 | "Not much—fifteen pounds, maybe twenty—but it settled around his middle like a man who'd traded youth for comfort." | | 1 | "Just looked at her, his eyes tracing the changes she knew were there—the sharper angles of her face, the shadows beneath her eyes that never quite faded." | | 2 | "He talked about Paris like it was a religion—the galleries, the light, the way the city breathed art through its streets." | | 3 | "For a moment, he looked like the boy she'd known—the one with paint under his nails and stars in his eyes." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 895 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 25 | | adverbRatio | 0.027932960893854747 | | lyAdverbCount | 6 | | lyAdverbRatio | 0.0067039106145251395 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 153 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 153 | | mean | 9.42 | | std | 7.62 | | cv | 0.809 | | sampleLengths | | 0 | 10 | | 1 | 18 | | 2 | 12 | | 3 | 11 | | 4 | 5 | | 5 | 11 | | 6 | 2 | | 7 | 4 | | 8 | 18 | | 9 | 15 | | 10 | 12 | | 11 | 3 | | 12 | 8 | | 13 | 14 | | 14 | 2 | | 15 | 5 | | 16 | 1 | | 17 | 2 | | 18 | 19 | | 19 | 8 | | 20 | 4 | | 21 | 19 | | 22 | 23 | | 23 | 12 | | 24 | 2 | | 25 | 8 | | 26 | 3 | | 27 | 14 | | 28 | 3 | | 29 | 9 | | 30 | 7 | | 31 | 27 | | 32 | 5 | | 33 | 3 | | 34 | 2 | | 35 | 9 | | 36 | 5 | | 37 | 7 | | 38 | 25 | | 39 | 12 | | 40 | 16 | | 41 | 8 | | 42 | 7 | | 43 | 14 | | 44 | 2 | | 45 | 7 | | 46 | 3 | | 47 | 6 | | 48 | 2 | | 49 | 2 |
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| 48.15% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 18 | | diversityRatio | 0.35947712418300654 | | totalSentences | 153 | | uniqueOpeners | 55 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 83 | | matches | | 0 | "Then his face cracked open" | | 1 | "Just looked at her, his" | | 2 | "Just a flicker, there and" |
| | ratio | 0.036 | |
| 0.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 47 | | totalSentences | 83 | | matches | | 0 | "He shook an umbrella, collapsing" | | 1 | "She knew the shape of" | | 2 | "He'd put on weight." | | 3 | "His hair was shorter, neater," | | 4 | "He wore a navy overcoat" | | 5 | "Their eyes met." | | 6 | "She set down the glass." | | 7 | "He'd moved to London before" | | 8 | "He crossed to the bar," | | 9 | "He gestured at the bottles" | | 10 | "She poured it, set it" | | 11 | "He didn't pick it up" | | 12 | "It came out flat, a" | | 13 | "He said it like an" | | 14 | "His jaw tightened." | | 15 | "He picked up the whiskey," | | 16 | "She watched him." | | 17 | "He spent his last ten" | | 18 | "He talked about Paris like" | | 19 | "His hands were clean, nails" |
| | ratio | 0.566 | |
| 14.22% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 74 | | totalSentences | 83 | | matches | | 0 | "Rory was wiping down the" | | 1 | "The November wind slipped in" | | 2 | "He shook an umbrella, collapsing" | | 3 | "She knew the shape of" | | 4 | "The way he held himself." | | 5 | "The slight tilt of his" | | 6 | "He'd put on weight." | | 7 | "His hair was shorter, neater," | | 8 | "He wore a navy overcoat" | | 9 | "Their eyes met." | | 10 | "Recognition dawned slow, like morning" | | 11 | "She set down the glass." | | 12 | "Danny had been there for" | | 13 | "He'd moved to London before" | | 14 | "He crossed to the bar," | | 15 | "He gestured at the bottles" | | 16 | "She poured it, set it" | | 17 | "He didn't pick it up" | | 18 | "It came out flat, a" | | 19 | "The bar was quiet for" |
| | ratio | 0.892 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 83 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 39 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 16 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 10 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 71 | | tagDensity | 0.141 | | leniency | 0.282 | | rawRatio | 0 | | effectiveRatio | 0 | |