| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 1 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 0 | | tagDensity | 1 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 96.29% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1346 | | totalAiIsmAdverbs | 1 | | found | | | highlights | | |
| 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) | |
| 36.85% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1346 | | totalAiIsms | 17 | | found | | | highlights | | 0 | "rhythmic" | | 1 | "silence" | | 2 | "weight" | | 3 | "stark" | | 4 | "velvet" | | 5 | "pulse" | | 6 | "throbbed" | | 7 | "reminder" | | 8 | "perfect" | | 9 | "wavered" | | 10 | "facade" | | 11 | "flicker" | | 12 | "firmly" | | 13 | "flickered" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "hung in the air" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 178 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 3 | | hedgeCount | 2 | | narrationSentences | 178 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 178 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 24 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 1 | | markdownWords | 1 | | totalWords | 1346 | | ratio | 0.001 | | matches | | |
| 0.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 17 | | unquotedAttributions | 12 | | matches | | 0 | "You left, she said." | | 1 | "I need something, he said." | | 2 | "Because I lied, he admitted." | | 3 | "You have three days to decide, Lucien said." | | 4 | "There is nowhere else, Lucien said." | | 5 | "You leave, she said." | | 6 | "I am not asking you to beg, Rory said." | | 7 | "Then I will stay, he replied." | | 8 | "I told you I would handle it, he said." | | 9 | "I am human, she said firmly." | | 10 | "I know, Lucien said." | | 11 | "We have work to do, Lucien said." |
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| 66.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 48 | | wordCount | 1344 | | uniqueNames | 13 | | maxNameDensity | 1.12 | | worstName | "You" | | maxWindowNameDensity | 3 | | worstWindowName | "You" | | discoveredNames | | Moreau | 1 | | Laila | 2 | | Evan | 1 | | Cardiff | 1 | | Venice | 1 | | Marseille | 1 | | North | 1 | | Sea | 1 | | Rory | 9 | | Lucien | 13 | | London | 1 | | Avaros | 1 | | You | 15 |
| | persons | | 0 | "Moreau" | | 1 | "Laila" | | 2 | "Evan" | | 3 | "Rory" | | 4 | "Lucien" | | 5 | "You" |
| | places | | 0 | "Cardiff" | | 1 | "Venice" | | 2 | "Marseille" | | 3 | "London" | | 4 | "Avaros" |
| | globalScore | 0.942 | | windowScore | 0.667 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 102 | | glossingSentenceCount | 2 | | matches | | 0 | "sounded like a breaking bone" | | 1 | "looked like he was about to smile when th" |
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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 | 1346 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 2 | | totalSentences | 178 | | matches | | 0 | "knew that rhythm" | | 1 | "see that scar" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 55 | | mean | 24.47 | | std | 14.2 | | cv | 0.58 | | sampleLengths | | 0 | 51 | | 1 | 44 | | 2 | 55 | | 3 | 20 | | 4 | 30 | | 5 | 50 | | 6 | 8 | | 7 | 48 | | 8 | 29 | | 9 | 19 | | 10 | 27 | | 11 | 13 | | 12 | 47 | | 13 | 26 | | 14 | 38 | | 15 | 27 | | 16 | 32 | | 17 | 55 | | 18 | 18 | | 19 | 19 | | 20 | 31 | | 21 | 13 | | 22 | 28 | | 23 | 39 | | 24 | 6 | | 25 | 15 | | 26 | 2 | | 27 | 7 | | 28 | 36 | | 29 | 19 | | 30 | 30 | | 31 | 10 | | 32 | 16 | | 33 | 26 | | 34 | 34 | | 35 | 17 | | 36 | 25 | | 37 | 3 | | 38 | 15 | | 39 | 30 | | 40 | 6 | | 41 | 15 | | 42 | 19 | | 43 | 33 | | 44 | 6 | | 45 | 52 | | 46 | 18 | | 47 | 21 | | 48 | 26 | | 49 | 9 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 178 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 3 | | totalVerbs | 246 | | matches | | 0 | "wasn’t lying" | | 1 | "were lying" | | 2 | "were lying" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 178 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 34 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 1 | | adverbRatio | 0.029411764705882353 | | lyAdverbCount | 0 | | lyAdverbRatio | 0 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 178 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 178 | | mean | 7.56 | | std | 4.66 | | cv | 0.616 | | sampleLengths | | 0 | 15 | | 1 | 21 | | 2 | 4 | | 3 | 11 | | 4 | 13 | | 5 | 8 | | 6 | 5 | | 7 | 14 | | 8 | 4 | | 9 | 10 | | 10 | 17 | | 11 | 17 | | 12 | 11 | | 13 | 5 | | 14 | 5 | | 15 | 10 | | 16 | 4 | | 17 | 9 | | 18 | 17 | | 19 | 10 | | 20 | 18 | | 21 | 10 | | 22 | 12 | | 23 | 5 | | 24 | 3 | | 25 | 19 | | 26 | 8 | | 27 | 21 | | 28 | 4 | | 29 | 7 | | 30 | 18 | | 31 | 4 | | 32 | 3 | | 33 | 2 | | 34 | 2 | | 35 | 8 | | 36 | 4 | | 37 | 12 | | 38 | 5 | | 39 | 2 | | 40 | 4 | | 41 | 6 | | 42 | 4 | | 43 | 3 | | 44 | 7 | | 45 | 7 | | 46 | 15 | | 47 | 3 | | 48 | 15 | | 49 | 4 |
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| 29.78% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 36 | | diversityRatio | 0.21348314606741572 | | totalSentences | 178 | | uniqueOpeners | 38 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 5 | | totalSentences | 161 | | matches | | 0 | "Then the North Sea." | | 1 | "Just get the hell away" | | 2 | "Just the material." | | 3 | "Then I will stay, he" | | 4 | "Just an exhaustion that matched" |
| | ratio | 0.031 | |
| 0.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 90 | | totalSentences | 161 | | matches | | 0 | "She knew that rhythm." | | 1 | "She wiped her palms on" | | 2 | "She ignored the first two." | | 3 | "She opened the door." | | 4 | "His slicked-back platinum-blond hair drooped" | | 5 | "She didn’t invite him in." | | 6 | "Her hand rested on the" | | 7 | "You’re drunk, she said." | | 8 | "Her voice sounded too loud" | | 9 | "He stepped closer into the" | | 10 | "I drove myself." | | 11 | "He used the name that" | | 12 | "It hit her chest like" | | 13 | "She crossed her arms, the" | | 14 | "You left, she said." | | 15 | "You disappear from the only" | | 16 | "I had business in Venice." | | 17 | "You had a phone, Rory" | | 18 | "You had the connection." | | 19 | "You had me." |
| | ratio | 0.559 | |
| 37.64% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 136 | | totalSentences | 161 | | matches | | 0 | "The knock came three times," | | 1 | "Rory stood frozen in the" | | 2 | "She knew that rhythm." | | 3 | "She wiped her palms on" | | 4 | "She ignored the first two." | | 5 | "The third slid open with" | | 6 | "She opened the door." | | 7 | "Lucien Moreau stood in the" | | 8 | "Water soaked the hem of" | | 9 | "His slicked-back platinum-blond hair drooped" | | 10 | "Rory didn’t close the door." | | 11 | "She didn’t invite him in." | | 12 | "Her hand rested on the" | | 13 | "You’re drunk, she said." | | 14 | "Her voice sounded too loud" | | 15 | "The smell of the curry" | | 16 | "Lucien shifted the weight of" | | 17 | "The ivory handle gleamed in" | | 18 | "He stepped closer into the" | | 19 | "The blade concealed within the" |
| | ratio | 0.845 | |
| 93.17% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 3 | | totalSentences | 161 | | matches | | 0 | "Because I lied, he admitted." | | 1 | "To the organization." | | 2 | "If I don’t get the" |
| | ratio | 0.019 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 49 | | technicalSentenceCount | 2 | | matches | | 0 | "The rain dripped from his hair onto the hallway floor, creating a small pool that reflected his face." | | 1 | "She shoved her hands into the pockets of her jeans, hiding her shaking fingers." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 1 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |