| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 24 | | adverbTagCount | 1 | | adverbTags | | 0 | "she said flatly [flatly]" |
| | dialogueSentences | 60 | | tagDensity | 0.4 | | leniency | 0.8 | | rawRatio | 0.042 | | effectiveRatio | 0.033 | |
| 93.04% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1437 | | totalAiIsmAdverbs | 2 | | found | | | highlights | | |
| 80.00% | AI-ism character names | Target: 0 AI-default names (17 tracked, −20% each) | | codexExemptions | (empty) | | found | | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 79.12% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1437 | | totalAiIsms | 6 | | found | | | highlights | | 0 | "footsteps" | | 1 | "weight" | | 2 | "flickered" | | 3 | "charm" | | 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 | 0 | | narrationSentences | 82 | | matches | (empty) | |
| 90.59% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 3 | | narrationSentences | 82 | | filterMatches | (empty) | | hedgeMatches | | 0 | "seemed to" | | 1 | "began to" | | 2 | "happened to" |
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| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 118 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 44 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 1 | | markdownWords | 3 | | totalWords | 1437 | | ratio | 0.002 | | matches | | 0 | "What devours, remains." |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 13 | | unquotedAttributions | 0 | | matches | (empty) | |
| 83.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 31 | | wordCount | 885 | | uniqueNames | 7 | | maxNameDensity | 0.9 | | worstName | "Rory" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Lucien" | | discoveredNames | | Ptolemy | 5 | | Moreau | 3 | | Eva | 6 | | Rory | 8 | | Lucien | 7 | | Latin | 1 | | Mr | 1 |
| | persons | | 0 | "Ptolemy" | | 1 | "Moreau" | | 2 | "Eva" | | 3 | "Rory" | | 4 | "Lucien" | | 5 | "Latin" | | 6 | "Mr" |
| | places | (empty) | | globalScore | 1 | | windowScore | 0.833 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 45 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.696 | | wordCount | 1437 | | matches | | 0 | "not Eva, but you read her research" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 118 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 63 | | mean | 22.81 | | std | 19.96 | | cv | 0.875 | | sampleLengths | | 0 | 13 | | 1 | 52 | | 2 | 28 | | 3 | 31 | | 4 | 9 | | 5 | 76 | | 6 | 5 | | 7 | 20 | | 8 | 3 | | 9 | 33 | | 10 | 41 | | 11 | 5 | | 12 | 41 | | 13 | 4 | | 14 | 71 | | 15 | 23 | | 16 | 21 | | 17 | 45 | | 18 | 45 | | 19 | 2 | | 20 | 46 | | 21 | 5 | | 22 | 31 | | 23 | 6 | | 24 | 40 | | 25 | 25 | | 26 | 4 | | 27 | 24 | | 28 | 40 | | 29 | 6 | | 30 | 4 | | 31 | 1 | | 32 | 3 | | 33 | 63 | | 34 | 2 | | 35 | 15 | | 36 | 5 | | 37 | 47 | | 38 | 8 | | 39 | 41 | | 40 | 63 | | 41 | 19 | | 42 | 7 | | 43 | 1 | | 44 | 7 | | 45 | 59 | | 46 | 41 | | 47 | 22 | | 48 | 3 | | 49 | 6 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 82 | | matches | | |
| 31.22% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 4 | | totalVerbs | 158 | | matches | | 0 | "was wearing" | | 1 | "wasn't happening" | | 2 | "wasn't saying" | | 3 | "was coming" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 118 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 887 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 35 | | adverbRatio | 0.03945885005636979 | | lyAdverbCount | 8 | | lyAdverbRatio | 0.009019165727170236 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 118 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 118 | | mean | 12.18 | | std | 10.47 | | cv | 0.86 | | sampleLengths | | 0 | 13 | | 1 | 6 | | 2 | 6 | | 3 | 40 | | 4 | 8 | | 5 | 4 | | 6 | 16 | | 7 | 14 | | 8 | 17 | | 9 | 5 | | 10 | 4 | | 11 | 27 | | 12 | 25 | | 13 | 8 | | 14 | 16 | | 15 | 5 | | 16 | 8 | | 17 | 12 | | 18 | 3 | | 19 | 25 | | 20 | 8 | | 21 | 8 | | 22 | 28 | | 23 | 3 | | 24 | 2 | | 25 | 5 | | 26 | 21 | | 27 | 20 | | 28 | 4 | | 29 | 37 | | 30 | 34 | | 31 | 6 | | 32 | 2 | | 33 | 15 | | 34 | 10 | | 35 | 11 | | 36 | 13 | | 37 | 15 | | 38 | 17 | | 39 | 1 | | 40 | 6 | | 41 | 38 | | 42 | 2 | | 43 | 30 | | 44 | 16 | | 45 | 5 | | 46 | 10 | | 47 | 21 | | 48 | 6 | | 49 | 26 |
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| 55.08% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 15 | | diversityRatio | 0.4067796610169492 | | totalSentences | 118 | | uniqueOpeners | 48 | |
| 49.02% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 68 | | matches | | 0 | "Instead, she turned off the" |
| | ratio | 0.015 | |
| 67.06% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 26 | | totalSentences | 68 | | matches | | 0 | "She'd only turned the first" | | 1 | "She dried her hands on" | | 2 | "His voice came through the" | | 3 | "She unhooked the chain instead." | | 4 | "His platinum hair was slicked" | | 5 | "He tilted his head" | | 6 | "His gaze slid past her," | | 7 | "He lifted his cane and" | | 8 | "He smiled, thin and precise" | | 9 | "He'd known where she was" | | 10 | "She gripped the door handle" | | 11 | "His voice dropped, losing its" | | 12 | "she said flatly" | | 13 | "She should shut the door." | | 14 | "She should lock all three" | | 15 | "She should do a lot" | | 16 | "He shifted his weight off" | | 17 | "He lifted one shoulder" | | 18 | "His gaze dropped to her" | | 19 | "His expression flickered." |
| | ratio | 0.382 | |
| 40.88% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 57 | | totalSentences | 68 | | matches | | 0 | "The third deadbolt slid home" | | 1 | "Rory's hand froze on the" | | 2 | "She'd only turned the first" | | 3 | "Eva was at work, the" | | 4 | "She dried her hands on" | | 5 | "His voice came through the" | | 6 | "She unhooked the chain instead." | | 7 | "Lucien Moreau stood in the" | | 8 | "His platinum hair was slicked" | | 9 | "The other, black as a" | | 10 | "He tilted his head" | | 11 | "His gaze slid past her," | | 12 | "Rory stepped into the doorway," | | 13 | "The old jumper she was" | | 14 | "He lifted his cane and" | | 15 | "He smiled, thin and precise" | | 16 | "Something hot flared in Rory's" | | 17 | "He'd known where she was" | | 18 | "She gripped the door handle" | | 19 | "The movement made him taller," |
| | ratio | 0.838 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 68 | | matches | (empty) | | ratio | 0 | |
| 35.71% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 20 | | technicalSentenceCount | 3 | | matches | | 0 | "Eva was at work, the curry house below was between lunch and dinner service, and Ptolemy had retreated under the sofa the moment he'd heard footsteps on the sta…" | | 1 | "The kettle behind her began to whistle, a thin, shrill sound that made Ptolemy hiss from under the sofa." | | 2 | "The way he stood there, in a corridor that smelled of old curry and damp plaster, looking like he'd stepped out of a different century and a worse deal, and ask…" |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 24 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 5 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 60 | | tagDensity | 0.083 | | leniency | 0.167 | | rawRatio | 0 | | effectiveRatio | 0 | |