| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 10 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 128 | | tagDensity | 0.078 | | leniency | 0.156 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 2329 | | 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) | |
| 84.97% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 2329 | | totalAiIsms | 7 | | found | | | highlights | | 0 | "weight" | | 1 | "dance" | | 2 | "silence" | | 3 | "complex" | | 4 | "chill" | | 5 | "tenderness" |
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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 | 1 | | narrationSentences | 166 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 0 | | narrationSentences | 166 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 284 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 46 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 2329 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 32 | | unquotedAttributions | 0 | | matches | (empty) | |
| 64.71% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 62 | | wordCount | 1407 | | uniqueNames | 9 | | maxNameDensity | 1.71 | | worstName | "Rory" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Lucien" | | discoveredNames | | Lucien | 21 | | Moreau | 1 | | Rory | 24 | | Eva | 3 | | Brick | 1 | | Lane | 1 | | French | 2 | | Châteauneuf-du-Pape | 1 | | Ptolemy | 8 |
| | persons | | 0 | "Lucien" | | 1 | "Moreau" | | 2 | "Rory" | | 3 | "Eva" | | 4 | "Châteauneuf-du-Pape" | | 5 | "Ptolemy" |
| | places | | | globalScore | 0.647 | | windowScore | 0.833 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 106 | | 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 | 2329 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 284 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 180 | | mean | 12.94 | | std | 13.97 | | cv | 1.079 | | sampleLengths | | 0 | 10 | | 1 | 52 | | 2 | 5 | | 3 | 3 | | 4 | 19 | | 5 | 5 | | 6 | 29 | | 7 | 15 | | 8 | 27 | | 9 | 10 | | 10 | 29 | | 11 | 5 | | 12 | 9 | | 13 | 6 | | 14 | 22 | | 15 | 3 | | 16 | 59 | | 17 | 1 | | 18 | 5 | | 19 | 4 | | 20 | 10 | | 21 | 22 | | 22 | 4 | | 23 | 57 | | 24 | 2 | | 25 | 1 | | 26 | 2 | | 27 | 12 | | 28 | 7 | | 29 | 14 | | 30 | 4 | | 31 | 12 | | 32 | 6 | | 33 | 7 | | 34 | 28 | | 35 | 11 | | 36 | 2 | | 37 | 2 | | 38 | 3 | | 39 | 9 | | 40 | 17 | | 41 | 2 | | 42 | 2 | | 43 | 9 | | 44 | 7 | | 45 | 31 | | 46 | 8 | | 47 | 58 | | 48 | 12 | | 49 | 4 |
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| 98.92% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 166 | | matches | | 0 | "was gone" | | 1 | "been dated" | | 2 | "been made" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 246 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 2 | | flaggedSentences | 2 | | totalSentences | 284 | | ratio | 0.007 | | matches | | 0 | "The movement pulled at his side; he hid the wince behind reaching for his coat." | | 1 | "Lucien swore in French; Rory laughed into his mouth." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1415 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 30 | | adverbRatio | 0.02120141342756184 | | lyAdverbCount | 0 | | lyAdverbRatio | 0 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 284 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 284 | | mean | 8.2 | | std | 6.74 | | cv | 0.822 | | sampleLengths | | 0 | 10 | | 1 | 9 | | 2 | 21 | | 3 | 4 | | 4 | 18 | | 5 | 5 | | 6 | 3 | | 7 | 7 | | 8 | 12 | | 9 | 5 | | 10 | 8 | | 11 | 13 | | 12 | 8 | | 13 | 6 | | 14 | 9 | | 15 | 4 | | 16 | 12 | | 17 | 2 | | 18 | 9 | | 19 | 10 | | 20 | 8 | | 21 | 21 | | 22 | 5 | | 23 | 5 | | 24 | 4 | | 25 | 6 | | 26 | 10 | | 27 | 12 | | 28 | 3 | | 29 | 8 | | 30 | 26 | | 31 | 10 | | 32 | 9 | | 33 | 6 | | 34 | 1 | | 35 | 5 | | 36 | 4 | | 37 | 3 | | 38 | 7 | | 39 | 15 | | 40 | 7 | | 41 | 4 | | 42 | 10 | | 43 | 15 | | 44 | 15 | | 45 | 4 | | 46 | 4 | | 47 | 9 | | 48 | 2 | | 49 | 1 |
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| 47.18% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 8 | | diversityRatio | 0.29225352112676056 | | totalSentences | 284 | | uniqueOpeners | 83 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 5 | | totalSentences | 150 | | matches | | 0 | "Somewhere near the street entrance," | | 1 | "Then, she had worn one" | | 2 | "Even the crescent scar on" | | 3 | "Instead, she took his coat" | | 4 | "Then she drew him back" |
| | ratio | 0.033 | |
| 65.33% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 58 | | totalSentences | 150 | | matches | | 0 | "He lifted his head." | | 1 | "She gripped the edge of" | | 2 | "She seized Lucien by the" | | 3 | "she told him" | | 4 | "He padded over and rubbed" | | 5 | "She shoved Lucien’s shoulder towards" | | 6 | "His mouth twitched." | | 7 | "She took his cane and" | | 8 | "She unbuttoned them herself." | | 9 | "His watch was gone." | | 10 | "He sucked air through his" | | 11 | "She held up the green" | | 12 | "Its label featured a skull" | | 13 | "Her father’s chambers." | | 14 | "Her mother’s school." | | 15 | "She threaded the needle." | | 16 | "He caught the edge instead" | | 17 | "He swore in French." | | 18 | "She took the next stitch." | | 19 | "His skin carried the chill" |
| | ratio | 0.387 | |
| 30.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 129 | | totalSentences | 150 | | matches | | 0 | "The door opened and Lucien" | | 1 | "Rain had pasted his platinum" | | 2 | "He lifted his head." | | 3 | "Amber and black, those mismatched" | | 4 | "She gripped the edge of" | | 5 | "A dark patch spread beneath" | | 6 | "Lucien’s fingers tightened around his" | | 7 | "Rory looked past him." | | 8 | "The other tilted his face" | | 9 | "She seized Lucien by the" | | 10 | "The three deadbolts snapped home," | | 11 | "Ptolemy shot off a stack" | | 12 | "she told him" | | 13 | "Lucien leaned against the wall." | | 14 | "The tabby’s outrage collapsed at" | | 15 | "He padded over and rubbed" | | 16 | "She shoved Lucien’s shoulder towards" | | 17 | "Every surface held some piece" | | 18 | "Rory cleared the table with" | | 19 | "A treatise on thresholds landed" |
| | ratio | 0.86 | |
| 66.67% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 150 | | matches | | 0 | "To wrap it, she had" | | 1 | "Now it developed an edge" |
| | ratio | 0.013 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 56 | | technicalSentenceCount | 3 | | matches | | 0 | "Even the crescent scar on her left wrist had earned a line, as though her childhood belonged in his inventory." | | 1 | "She laid her palm against his jaw, avoiding the bruise forming at his cheekbone." | | 2 | "His fingers spread against her back, holding rather than steering." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 10 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 10 | | fancyCount | 1 | | fancyTags | | 0 | "Rory muttered (mutter)" |
| | dialogueSentences | 128 | | tagDensity | 0.078 | | leniency | 0.156 | | rawRatio | 0.1 | | effectiveRatio | 0.016 | |