| 0.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 13 | | adverbTagCount | 3 | | adverbTags | | 0 | "he said softly [softly]" | | 1 | "she said finally [finally]" | | 2 | "she asked softly [softly]" |
| | dialogueSentences | 27 | | tagDensity | 0.481 | | leniency | 0.963 | | rawRatio | 0.231 | | effectiveRatio | 0.222 | |
| 60.63% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 889 | | totalAiIsmAdverbs | 7 | | found | | 0 | | | 1 | | | 2 | | | 3 | | adverb | "barely above a whisper" | | count | 1 |
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| | highlights | | 0 | "slightly" | | 1 | "softly" | | 2 | "really" | | 3 | "barely above a whisper" |
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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) | |
| 55.01% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 889 | | totalAiIsms | 8 | | found | | | highlights | | 0 | "furrowing" | | 1 | "familiar" | | 2 | "eyebrow" | | 3 | "clenching" | | 4 | "pounding" | | 5 | "racing" | | 6 | "reminder" | | 7 | "whisper" |
| |
| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 0 | | maxInWindow | 0 | | found | (empty) | | highlights | (empty) | |
| 99.36% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 2 | | narrationSentences | 65 | | matches | | 0 | "n in love" | | 1 | "g with hope" |
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| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 65 | | filterMatches | | | 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 | 21 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 889 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 14 | | unquotedAttributions | 0 | | matches | (empty) | |
| 85.25% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 23 | | wordCount | 695 | | uniqueNames | 9 | | maxNameDensity | 1.29 | | worstName | "Rory" | | maxWindowNameDensity | 2 | | worstWindowName | "Rory" | | discoveredNames | | Rory | 9 | | Moreau | 1 | | Frenchman | 1 | | Eva | 2 | | French | 1 | | Ptolemy | 1 | | Lucien | 6 | | Avaros | 1 | | London | 1 |
| | persons | | 0 | "Rory" | | 1 | "Moreau" | | 2 | "Frenchman" | | 3 | "Eva" | | 4 | "Ptolemy" | | 5 | "Lucien" |
| | places | | | globalScore | 0.853 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 56 | | 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 | 889 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 79 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 27 | | mean | 32.93 | | std | 17.34 | | cv | 0.527 | | sampleLengths | | 0 | 93 | | 1 | 43 | | 2 | 37 | | 3 | 37 | | 4 | 41 | | 5 | 38 | | 6 | 16 | | 7 | 24 | | 8 | 17 | | 9 | 17 | | 10 | 38 | | 11 | 51 | | 12 | 20 | | 13 | 25 | | 14 | 23 | | 15 | 27 | | 16 | 34 | | 17 | 7 | | 18 | 34 | | 19 | 65 | | 20 | 16 | | 21 | 26 | | 22 | 36 | | 23 | 25 | | 24 | 49 | | 25 | 15 | | 26 | 35 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 65 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 128 | | matches | (empty) | |
| 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) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 699 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 21 | | adverbRatio | 0.030042918454935622 | | lyAdverbCount | 10 | | lyAdverbRatio | 0.01430615164520744 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 79 | | echoCount | 0 | | echoWords | (empty) | |
| 93.38% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 79 | | mean | 11.25 | | std | 4.32 | | cv | 0.383 | | sampleLengths | | 0 | 15 | | 1 | 8 | | 2 | 8 | | 3 | 17 | | 4 | 11 | | 5 | 21 | | 6 | 13 | | 7 | 7 | | 8 | 18 | | 9 | 18 | | 10 | 6 | | 11 | 11 | | 12 | 20 | | 13 | 10 | | 14 | 16 | | 15 | 11 | | 16 | 10 | | 17 | 12 | | 18 | 10 | | 19 | 9 | | 20 | 15 | | 21 | 10 | | 22 | 13 | | 23 | 5 | | 24 | 11 | | 25 | 11 | | 26 | 13 | | 27 | 10 | | 28 | 7 | | 29 | 7 | | 30 | 6 | | 31 | 4 | | 32 | 11 | | 33 | 10 | | 34 | 6 | | 35 | 11 | | 36 | 10 | | 37 | 14 | | 38 | 12 | | 39 | 15 | | 40 | 15 | | 41 | 5 | | 42 | 7 | | 43 | 4 | | 44 | 14 | | 45 | 6 | | 46 | 17 | | 47 | 8 | | 48 | 19 | | 49 | 7 |
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| 38.82% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 11 | | diversityRatio | 0.31645569620253167 | | totalSentences | 79 | | uniqueOpeners | 25 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 62 | | matches | (empty) | | ratio | 0 | |
| 0.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 41 | | totalSentences | 62 | | matches | | 0 | "She glanced at the clock," | | 1 | "It was late, too late" | | 2 | "She padded to the door," | | 3 | "His heterochromatic eyes, one amber," | | 4 | "She hadn't seen him since" | | 5 | "She undid the three deadbolts," | | 6 | "she acknowledged, her voice cool" | | 7 | "She leaned against the doorframe," | | 8 | "Her straight, shoulder-length black hair" | | 9 | "he replied, a small smile" | | 10 | "His French accent, usually a" | | 11 | "She raised an eyebrow, stepping" | | 12 | "she asked, closing the door" | | 13 | "She bent to scratch his" | | 14 | "he countered, turning to face" | | 15 | "His ivory-handled cane, a thin" | | 16 | "He sighed, running a hand" | | 17 | "She stiffened, her hands clenching" | | 18 | "he said softly" | | 19 | "She gestured to the couch," |
| | ratio | 0.661 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 59 | | totalSentences | 62 | | matches | | 0 | "The doorbell chimed, a shrill," | | 1 | "She glanced at the clock," | | 2 | "It was late, too late" | | 3 | "She padded to the door," | | 4 | "A familiar face stared back," | | 5 | "Lucien Moreau, the Frenchman, stood" | | 6 | "His heterochromatic eyes, one amber," | | 7 | "Rory took a deep breath," | | 8 | "She hadn't seen him since" | | 9 | "She undid the three deadbolts," | | 10 | "she acknowledged, her voice cool" | | 11 | "She leaned against the doorframe," | | 12 | "Her straight, shoulder-length black hair" | | 13 | "he replied, a small smile" | | 14 | "His French accent, usually a" | | 15 | "She raised an eyebrow, stepping" | | 16 | "she asked, closing the door" | | 17 | "The tabby cat, Ptolemy, wound" | | 18 | "She bent to scratch his" | | 19 | "Lucien shrugged off his suit" |
| | ratio | 0.952 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 62 | | matches | (empty) | | ratio | 0 | |
| 67.67% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 38 | | technicalSentenceCount | 4 | | matches | | 0 | "The doorbell chimed, a shrill, insistent sound that pierced the quiet hum of Rory's flat." | | 1 | "She knew about his past, about the darkness that haunted him." | | 2 | "She knew about the realm of Avaros, about the demon blood that flowed through his veins." | | 3 | "A slow smile spread across Lucien's face, a smile that lit up his eyes, that made him look younger, happier." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 13 | | uselessAdditionCount | 7 | | matches | | 0 | "she acknowledged, her voice cool" | | 1 | "he replied, a small smile playing on his lips" | | 2 | "he countered, turning to face her" | | 3 | "she said finally, her voice steady" | | 4 | "she said, her voice steady" | | 5 | "she said, her voice soft" | | 6 | "he said, his voice barely above a whisper" |
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| 38.89% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 12 | | fancyCount | 3 | | fancyTags | | 0 | "she acknowledged (acknowledge)" | | 1 | "he admitted (admit)" | | 2 | "he agreed (agree)" |
| | dialogueSentences | 27 | | tagDensity | 0.444 | | leniency | 0.889 | | rawRatio | 0.25 | | effectiveRatio | 0.222 | |