| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 7 | | adverbTagCount | 1 | | adverbTags | | | dialogueSentences | 114 | | tagDensity | 0.061 | | leniency | 0.123 | | rawRatio | 0.143 | | effectiveRatio | 0.018 | |
| 92.99% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 2141 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | 0 | "carefully" | | 1 | "suddenly" | | 2 | "sharply" |
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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) | |
| 81.32% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 2141 | | totalAiIsms | 8 | | found | | | highlights | | 0 | "gloom" | | 1 | "flicked" | | 2 | "silence" | | 3 | "pulse" | | 4 | "stomach" | | 5 | "whisper" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 152 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 3 | | narrationSentences | 152 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 259 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 37 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 2141 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 17 | | unquotedAttributions | 0 | | matches | (empty) | |
| 59.64% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 62 | | wordCount | 1494 | | uniqueNames | 7 | | maxNameDensity | 1.81 | | worstName | "Rory" | | maxWindowNameDensity | 3 | | worstWindowName | "Rory" | | discoveredNames | | Moreau | 1 | | Eva | 5 | | Rory | 27 | | Lucien | 16 | | Ptolemy | 7 | | Like | 3 | | Close | 3 |
| | persons | | 0 | "Moreau" | | 1 | "Eva" | | 2 | "Rory" | | 3 | "Lucien" | | 4 | "Ptolemy" |
| | places | (empty) | | globalScore | 0.596 | | windowScore | 0.667 | |
| 96.24% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 93 | | glossingSentenceCount | 2 | | matches | | 0 | "not quite a smile" | | 1 | "as if measuring the room for ears" |
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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 | 2141 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 259 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 148 | | mean | 14.47 | | std | 16.1 | | cv | 1.113 | | sampleLengths | | 0 | 8 | | 1 | 43 | | 2 | 68 | | 3 | 6 | | 4 | 4 | | 5 | 12 | | 6 | 2 | | 7 | 1 | | 8 | 11 | | 9 | 20 | | 10 | 27 | | 11 | 9 | | 12 | 26 | | 13 | 4 | | 14 | 2 | | 15 | 28 | | 16 | 1 | | 17 | 35 | | 18 | 10 | | 19 | 23 | | 20 | 4 | | 21 | 11 | | 22 | 9 | | 23 | 9 | | 24 | 2 | | 25 | 4 | | 26 | 7 | | 27 | 9 | | 28 | 18 | | 29 | 1 | | 30 | 1 | | 31 | 38 | | 32 | 53 | | 33 | 67 | | 34 | 11 | | 35 | 28 | | 36 | 9 | | 37 | 6 | | 38 | 16 | | 39 | 12 | | 40 | 24 | | 41 | 9 | | 42 | 10 | | 43 | 4 | | 44 | 79 | | 45 | 5 | | 46 | 1 | | 47 | 10 | | 48 | 20 | | 49 | 10 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 152 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 254 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 259 | | ratio | 0 | | matches | (empty) | |
| 92.97% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1499 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 72 | | adverbRatio | 0.04803202134756504 | | lyAdverbCount | 9 | | lyAdverbRatio | 0.00600400266844563 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 259 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 259 | | mean | 8.27 | | std | 7.01 | | cv | 0.848 | | sampleLengths | | 0 | 8 | | 1 | 37 | | 2 | 6 | | 3 | 24 | | 4 | 7 | | 5 | 10 | | 6 | 27 | | 7 | 6 | | 8 | 4 | | 9 | 7 | | 10 | 5 | | 11 | 2 | | 12 | 1 | | 13 | 6 | | 14 | 5 | | 15 | 13 | | 16 | 7 | | 17 | 6 | | 18 | 10 | | 19 | 11 | | 20 | 4 | | 21 | 5 | | 22 | 22 | | 23 | 4 | | 24 | 4 | | 25 | 2 | | 26 | 13 | | 27 | 15 | | 28 | 1 | | 29 | 3 | | 30 | 2 | | 31 | 5 | | 32 | 25 | | 33 | 7 | | 34 | 3 | | 35 | 19 | | 36 | 4 | | 37 | 3 | | 38 | 1 | | 39 | 11 | | 40 | 9 | | 41 | 9 | | 42 | 2 | | 43 | 3 | | 44 | 1 | | 45 | 7 | | 46 | 9 | | 47 | 15 | | 48 | 3 | | 49 | 1 |
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| 45.75% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 11 | | diversityRatio | 0.2702702702702703 | | totalSentences | 259 | | uniqueOpeners | 70 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 5 | | totalSentences | 136 | | matches | | 0 | "Of course he did." | | 1 | "Even the curry house downstairs" | | 2 | "Of course he did." | | 3 | "Instead she dragged a hand" | | 4 | "Then the wood split down" |
| | ratio | 0.037 | |
| 67.06% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 52 | | totalSentences | 136 | | matches | | 0 | "She stopped with the blade" | | 1 | "His amber eye fixed on" | | 2 | "His mouth curved, not quite" | | 3 | "She gave him a flat" | | 4 | "He let his gaze drop" | | 5 | "He flattened himself against Rory’s" | | 6 | "He shifted his cane, the" | | 7 | "His jaw ticked." | | 8 | "His expression shifted then, gone" | | 9 | "She hated the way he" | | 10 | "She pushed the chain loose" | | 11 | "His nostrils flared once." | | 12 | "His gaze flicked to the" | | 13 | "His tone sharpened" | | 14 | "Her pulse thudded once, heavy." | | 15 | "She stared at him, then" | | 16 | "He stepped closer." | | 17 | "His gaze dropped to her" | | 18 | "His expression changed so fast" | | 19 | "His mouth went flat." |
| | ratio | 0.382 | |
| 26.18% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 118 | | totalSentences | 136 | | matches | | 0 | "Rory yanked the door open" | | 1 | "She stopped with the blade" | | 2 | "Lucien Moreau stood in the" | | 3 | "The other hung loose at" | | 4 | "His amber eye fixed on" | | 5 | "Rory’s grip tightened around the" | | 6 | "His mouth curved, not quite" | | 7 | "She gave him a flat" | | 8 | "He let his gaze drop" | | 9 | "A hiss sounded at her" | | 10 | "Ptolemy had materialised, fur bristling," | | 11 | "He flattened himself against Rory’s" | | 12 | "Lucien inclined his head." | | 13 | "Rory cracked the door wider" | | 14 | "He shifted his cane, the" | | 15 | "His jaw ticked." | | 16 | "Rory folded her arm around" | | 17 | "Lucien’s gaze moved over her" | | 18 | "Rory didn’t blink." | | 19 | "Rory’s throat tightened." |
| | ratio | 0.868 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 136 | | matches | (empty) | | ratio | 0 | |
| 81.28% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 58 | | technicalSentenceCount | 5 | | matches | | 0 | "Lucien Moreau stood in the corridor outside Eva’s flat like he belonged there, immaculate in a charcoal suit that fit him with insulting precision." | | 1 | "His amber eye fixed on her, his black eye held the hallway behind her, as if he had come equipped with patience and menace in equal measure." | | 2 | "Lucien’s gaze moved over her face, slow and infuriatingly precise, as if he still knew where every fracture lived." | | 3 | "His amber eye lifted to the ceiling, then the window, then the book stacks, as if measuring the room for ears." | | 4 | "The cupboard door at the far end of Eva’s narrow kitchen bulged inward once, then again, as if something heavy and patient pressed from the other side." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 7 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 5 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 114 | | tagDensity | 0.044 | | leniency | 0.088 | | rawRatio | 0.2 | | effectiveRatio | 0.018 | |