| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 20 | | adverbTagCount | 2 | | adverbTags | | 0 | "He leaned back [back]" | | 1 | "he said again [again]" |
| | dialogueSentences | 197 | | tagDensity | 0.102 | | leniency | 0.203 | | rawRatio | 0.1 | | effectiveRatio | 0.02 | |
| 88.47% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 2602 | | totalAiIsmAdverbs | 6 | | found | | | highlights | | 0 | "softly" | | 1 | "very" | | 2 | "carefully" | | 3 | "really" | | 4 | "quickly" |
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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) | |
| 69.25% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 2602 | | totalAiIsms | 16 | | found | | | highlights | | 0 | "lilt" | | 1 | "echoed" | | 2 | "familiar" | | 3 | "warmth" | | 4 | "silence" | | 5 | "weight" | | 6 | "glinting" | | 7 | "could feel" | | 8 | "stomach" | | 9 | "sense of" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "let out a breath" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 203 | | matches | (empty) | |
| 86.56% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 6 | | narrationSentences | 203 | | filterMatches | | | hedgeMatches | | 0 | "seemed to" | | 1 | "tend to" | | 2 | "started to" | | 3 | "try to" | | 4 | "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 | 380 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 29 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 2602 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 49 | | unquotedAttributions | 0 | | matches | (empty) | |
| 83.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 40 | | wordCount | 1679 | | uniqueNames | 5 | | maxNameDensity | 1.25 | | worstName | "Rory" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Rory" | | discoveredNames | | Ptolemy | 6 | | Moreau | 1 | | Rory | 21 | | French | 1 | | Lucien | 11 |
| | persons | | 0 | "Ptolemy" | | 1 | "Moreau" | | 2 | "Rory" | | 3 | "Lucien" |
| | places | (empty) | | globalScore | 0.875 | | windowScore | 0.833 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 128 | | 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 | 2602 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 2 | | totalSentences | 380 | | matches | | 0 | "hated that place" | | 1 | "believed that his" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 251 | | mean | 10.37 | | std | 11.12 | | cv | 1.073 | | sampleLengths | | 0 | 13 | | 1 | 44 | | 2 | 5 | | 3 | 11 | | 4 | 40 | | 5 | 8 | | 6 | 23 | | 7 | 5 | | 8 | 5 | | 9 | 1 | | 10 | 1 | | 11 | 35 | | 12 | 15 | | 13 | 2 | | 14 | 2 | | 15 | 4 | | 16 | 16 | | 17 | 5 | | 18 | 5 | | 19 | 2 | | 20 | 3 | | 21 | 4 | | 22 | 5 | | 23 | 46 | | 24 | 15 | | 25 | 6 | | 26 | 4 | | 27 | 5 | | 28 | 1 | | 29 | 1 | | 30 | 31 | | 31 | 4 | | 32 | 13 | | 33 | 7 | | 34 | 14 | | 35 | 1 | | 36 | 3 | | 37 | 9 | | 38 | 6 | | 39 | 4 | | 40 | 5 | | 41 | 55 | | 42 | 16 | | 43 | 12 | | 44 | 18 | | 45 | 4 | | 46 | 7 | | 47 | 1 | | 48 | 1 | | 49 | 10 |
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| 98.35% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 4 | | totalSentences | 203 | | matches | | 0 | "been invited" | | 1 | "was cramped" | | 2 | "was creased" | | 3 | "was allowed" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 3 | | totalVerbs | 315 | | matches | | 0 | "was holding" | | 1 | "was trying" | | 2 | "was still standing" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 1 | | flaggedSentences | 1 | | totalSentences | 380 | | ratio | 0.003 | | matches | | 0 | "The corridor light had left them; under the kitchen lamp, his amber eye looked almost gold." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1681 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 57 | | adverbRatio | 0.03390838786436645 | | lyAdverbCount | 14 | | lyAdverbRatio | 0.008328375966686495 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 380 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 380 | | mean | 6.85 | | std | 5.09 | | cv | 0.744 | | sampleLengths | | 0 | 13 | | 1 | 8 | | 2 | 20 | | 3 | 16 | | 4 | 5 | | 5 | 11 | | 6 | 5 | | 7 | 15 | | 8 | 10 | | 9 | 10 | | 10 | 8 | | 11 | 8 | | 12 | 15 | | 13 | 5 | | 14 | 5 | | 15 | 1 | | 16 | 1 | | 17 | 20 | | 18 | 7 | | 19 | 8 | | 20 | 10 | | 21 | 5 | | 22 | 2 | | 23 | 2 | | 24 | 4 | | 25 | 7 | | 26 | 9 | | 27 | 5 | | 28 | 5 | | 29 | 2 | | 30 | 3 | | 31 | 4 | | 32 | 5 | | 33 | 8 | | 34 | 1 | | 35 | 17 | | 36 | 8 | | 37 | 12 | | 38 | 11 | | 39 | 4 | | 40 | 6 | | 41 | 4 | | 42 | 5 | | 43 | 1 | | 44 | 1 | | 45 | 9 | | 46 | 5 | | 47 | 17 | | 48 | 4 | | 49 | 13 |
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| 45.00% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 19 | | diversityRatio | 0.17894736842105263 | | totalSentences | 380 | | uniqueOpeners | 68 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 6 | | totalSentences | 183 | | matches | | 0 | "Then she noticed the cut" | | 1 | "Then he had looked her" | | 2 | "Instead he sat in her" | | 3 | "Then he seemed to think" | | 4 | "Then Lucien unbuttoned his jacket." | | 5 | "Instead, he gave her the" |
| | ratio | 0.033 | |
| 12.35% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 95 | | totalSentences | 183 | | matches | | 0 | "It was past midnight, and" | | 1 | "She pulled the door inward." | | 2 | "His charcoal suit was immaculate." | | 3 | "His platinum hair, slicked back" | | 4 | "He said her name softly," | | 5 | "His amber eye caught the" | | 6 | "She kept one hand on" | | 7 | "She looked past him into" | | 8 | "She stepped back, but didn’t" | | 9 | "It landed exactly where it" | | 10 | "She hated that place." | | 11 | "She might have believed that" | | 12 | "She’d waited for the rest." | | 13 | "He’d let the silence do" | | 14 | "He lowered his eyes for" | | 15 | "He shifted his weight, the" | | 16 | "His suit was unmarked, but" | | 17 | "He was holding his left" | | 18 | "His face had that controlled" | | 19 | "It disappeared before she could" |
| | ratio | 0.519 | |
| 11.91% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 164 | | totalSentences | 183 | | matches | | 0 | "The door opened on the" | | 1 | "Rory had turned each key" | | 2 | "It was past midnight, and" | | 3 | "The flat was quiet except" | | 4 | "She pulled the door inward." | | 5 | "Lucien Moreau stood in the" | | 6 | "His charcoal suit was immaculate." | | 7 | "His platinum hair, slicked back" | | 8 | "The other was empty, which" | | 9 | "A narrow line of blood" | | 10 | "He said her name softly," | | 11 | "His amber eye caught the" | | 12 | "The other was black as" | | 13 | "She kept one hand on" | | 14 | "Ptolemy appeared between her ankles," | | 15 | "The cat stared at Lucien," | | 16 | "She looked past him into" | | 17 | "That didn’t mean no one" | | 18 | "Lucien had taught her that" | | 19 | "She stepped back, but didn’t" |
| | ratio | 0.896 | |
| 27.32% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 183 | | matches | | | ratio | 0.005 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 66 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 20 | | uselessAdditionCount | 1 | | matches | | 0 | "He shifted, the cane tip tapping once against the floor" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 15 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 197 | | tagDensity | 0.076 | | leniency | 0.152 | | rawRatio | 0 | | effectiveRatio | 0 | |