| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 10 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 31 | | tagDensity | 0.323 | | leniency | 0.645 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 690 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 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) | |
| 78.26% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 690 | | totalAiIsms | 3 | | found | | | highlights | | 0 | "unreadable" | | 1 | "flicked" | | 2 | "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 | 0 | | narrationSentences | 62 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 62 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 82 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 29 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 2 | | markdownWords | 2 | | totalWords | 684 | | ratio | 0.003 | | matches | | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 9 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 18 | | wordCount | 517 | | uniqueNames | 7 | | maxNameDensity | 0.97 | | worstName | "Rory" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Rory" | | discoveredNames | | Moreau | 1 | | Like | 1 | | Soho | 1 | | Rory | 5 | | Lucien | 5 | | Slid | 1 | | Ptolemy | 4 |
| | persons | | 0 | "Moreau" | | 1 | "Rory" | | 2 | "Lucien" | | 3 | "Ptolemy" |
| | places | | | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 32 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 53.80% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 1.462 | | wordCount | 684 | | matches | | 0 | "not for a weapon, but for a folded piece of paper" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 82 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 32 | | mean | 21.38 | | std | 15.89 | | cv | 0.743 | | sampleLengths | | 0 | 43 | | 1 | 8 | | 2 | 43 | | 3 | 44 | | 4 | 14 | | 5 | 28 | | 6 | 12 | | 7 | 40 | | 8 | 11 | | 9 | 12 | | 10 | 38 | | 11 | 49 | | 12 | 9 | | 13 | 18 | | 14 | 5 | | 15 | 16 | | 16 | 9 | | 17 | 16 | | 18 | 43 | | 19 | 39 | | 20 | 30 | | 21 | 7 | | 22 | 7 | | 23 | 1 | | 24 | 1 | | 25 | 12 | | 26 | 9 | | 27 | 10 | | 28 | 56 | | 29 | 33 | | 30 | 11 | | 31 | 10 |
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| 99.60% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 62 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 98 | | matches | (empty) | |
| 38.33% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 3 | | semicolonCount | 0 | | flaggedSentences | 3 | | totalSentences | 82 | | ratio | 0.037 | | matches | | 0 | "Lucien’s gaze flicked to the cat, then to the stack of half-unpacked boxes in the corner—her life suspended mid-transition, like she’d been waiting." | | 1 | "Instead, he ran a gloved finger along the spine of a book on the nearest shelf—some obscure tome on demonic binding rituals, its leather cover cracked with age." | | 2 | "“They’re saying you’re still breathing.” He reached into his coat—not for a weapon, but for a folded piece of paper." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 523 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 19 | | adverbRatio | 0.036328871892925434 | | lyAdverbCount | 2 | | lyAdverbRatio | 0.0038240917782026767 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 82 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 82 | | mean | 8.34 | | std | 6.62 | | cv | 0.794 | | sampleLengths | | 0 | 10 | | 1 | 4 | | 2 | 4 | | 3 | 16 | | 4 | 9 | | 5 | 6 | | 6 | 2 | | 7 | 9 | | 8 | 28 | | 9 | 6 | | 10 | 15 | | 11 | 29 | | 12 | 5 | | 13 | 5 | | 14 | 4 | | 15 | 23 | | 16 | 5 | | 17 | 7 | | 18 | 5 | | 19 | 5 | | 20 | 28 | | 21 | 7 | | 22 | 3 | | 23 | 8 | | 24 | 4 | | 25 | 4 | | 26 | 4 | | 27 | 12 | | 28 | 2 | | 29 | 2 | | 30 | 16 | | 31 | 6 | | 32 | 12 | | 33 | 27 | | 34 | 10 | | 35 | 9 | | 36 | 2 | | 37 | 9 | | 38 | 7 | | 39 | 5 | | 40 | 1 | | 41 | 10 | | 42 | 5 | | 43 | 8 | | 44 | 1 | | 45 | 9 | | 46 | 7 | | 47 | 5 | | 48 | 1 | | 49 | 4 |
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| 67.89% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 6 | | diversityRatio | 0.45121951219512196 | | totalSentences | 82 | | uniqueOpeners | 37 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 52 | | matches | | 0 | "Instead, he ran a gloved" | | 1 | "Then she sank onto the" |
| | ratio | 0.038 | |
| 89.23% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 17 | | totalSentences | 52 | | matches | | 0 | "She knew that sound." | | 1 | "she said, voice steady" | | 2 | "he said, stepping inside like" | | 3 | "She crossed her arms" | | 4 | "He didn’t answer right away." | | 5 | "His head snapped up." | | 6 | "She cut herself off" | | 7 | "He took another step forward," | | 8 | "His expression shut down, all" | | 9 | "His voice dropped" | | 10 | "He reached into his coat—not" | | 11 | "Her name, scrawled in jagged" | | 12 | "She crumpled the paper in" | | 13 | "His jaw tightened." | | 14 | "She met his gaze, unblinking." | | 15 | "He turned toward the door," | | 16 | "She should’ve known better than" |
| | ratio | 0.327 | |
| 75.38% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 40 | | totalSentences | 52 | | matches | | 0 | "The third deadbolt clicked shut" | | 1 | "Rory didn’t turn around." | | 2 | "She knew that sound." | | 3 | "Ptolemy’s tail twitched against her" | | 4 | "she said, voice steady" | | 5 | "The door swung open before" | | 6 | "Lucien Moreau filled the threshold," | | 7 | "The black one stayed shadowed," | | 8 | "he said, stepping inside like" | | 9 | "Ptolemy hissed, arching his back." | | 10 | "Rory didn’t reach for him." | | 11 | "Lucien’s gaze flicked to the" | | 12 | "She crossed her arms" | | 13 | "He didn’t answer right away." | | 14 | "His head snapped up." | | 15 | "The amber eye burned." | | 16 | "She cut herself off" | | 17 | "The words stuck in her" | | 18 | "Lucien exhaled through his nose," | | 19 | "He took another step forward," |
| | ratio | 0.769 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 52 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 17 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 25.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 10 | | uselessAdditionCount | 2 | | matches | | 0 | "she said, voice steady" | | 1 | "He turned, cane tapping against the floorboards" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 3 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 31 | | tagDensity | 0.097 | | leniency | 0.194 | | rawRatio | 0 | | effectiveRatio | 0 | |