| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 10 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 138 | | tagDensity | 0.072 | | leniency | 0.145 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 94.71% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1892 | | totalAiIsmAdverbs | 2 | | 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) | |
| 81.50% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1892 | | totalAiIsms | 7 | | found | | | highlights | | 0 | "warmth" | | 1 | "familiar" | | 2 | "pulse" | | 3 | "silence" | | 4 | "velvet" |
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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 | 134 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 3 | | narrationSentences | 134 | | filterMatches | | | hedgeMatches | | 0 | "seemed to" | | 1 | "began to" | | 2 | "managed to" |
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| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 262 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 38 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1890 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 23 | | unquotedAttributions | 0 | | matches | (empty) | |
| 47.50% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 58 | | wordCount | 1122 | | uniqueNames | 12 | | maxNameDensity | 2.05 | | worstName | "Lucien" | | maxWindowNameDensity | 3 | | worstWindowName | "Aurora" | | discoveredNames | | Lucien | 23 | | Moreau | 1 | | Carter | 1 | | Brick | 2 | | Lane | 2 | | Ptolemy | 4 | | Aurora | 20 | | Avarosi | 1 | | Voss | 1 | | Earth | 1 | | Avaros | 1 | | Thames | 1 |
| | persons | | 0 | "Lucien" | | 1 | "Moreau" | | 2 | "Carter" | | 3 | "Ptolemy" | | 4 | "Aurora" | | 5 | "Voss" |
| | places | | | globalScore | 0.475 | | windowScore | 0.667 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 76 | | 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 | 1890 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 262 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 218 | | mean | 8.67 | | std | 9.31 | | cv | 1.074 | | sampleLengths | | 0 | 17 | | 1 | 5 | | 2 | 49 | | 3 | 5 | | 4 | 3 | | 5 | 22 | | 6 | 2 | | 7 | 2 | | 8 | 25 | | 9 | 7 | | 10 | 8 | | 11 | 4 | | 12 | 8 | | 13 | 4 | | 14 | 45 | | 15 | 6 | | 16 | 9 | | 17 | 8 | | 18 | 26 | | 19 | 7 | | 20 | 6 | | 21 | 9 | | 22 | 5 | | 23 | 8 | | 24 | 43 | | 25 | 4 | | 26 | 4 | | 27 | 2 | | 28 | 5 | | 29 | 2 | | 30 | 10 | | 31 | 31 | | 32 | 6 | | 33 | 1 | | 34 | 5 | | 35 | 5 | | 36 | 11 | | 37 | 9 | | 38 | 7 | | 39 | 11 | | 40 | 5 | | 41 | 50 | | 42 | 5 | | 43 | 10 | | 44 | 27 | | 45 | 4 | | 46 | 5 | | 47 | 3 | | 48 | 5 | | 49 | 25 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 134 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 191 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 2 | | semicolonCount | 0 | | flaggedSentences | 1 | | totalSentences | 262 | | ratio | 0.004 | | matches | | 0 | "Aurora snatched the nearest object from the counter—a brass pestle—and raised it between them." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1127 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 24 | | adverbRatio | 0.02129547471162378 | | lyAdverbCount | 3 | | lyAdverbRatio | 0.0026619343389529724 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 262 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 262 | | mean | 7.21 | | std | 5.77 | | cv | 0.8 | | sampleLengths | | 0 | 17 | | 1 | 5 | | 2 | 11 | | 3 | 38 | | 4 | 5 | | 5 | 3 | | 6 | 11 | | 7 | 11 | | 8 | 2 | | 9 | 2 | | 10 | 11 | | 11 | 7 | | 12 | 7 | | 13 | 7 | | 14 | 3 | | 15 | 5 | | 16 | 4 | | 17 | 8 | | 18 | 4 | | 19 | 29 | | 20 | 16 | | 21 | 6 | | 22 | 9 | | 23 | 8 | | 24 | 5 | | 25 | 21 | | 26 | 7 | | 27 | 6 | | 28 | 9 | | 29 | 5 | | 30 | 8 | | 31 | 14 | | 32 | 11 | | 33 | 18 | | 34 | 4 | | 35 | 4 | | 36 | 2 | | 37 | 5 | | 38 | 2 | | 39 | 4 | | 40 | 6 | | 41 | 31 | | 42 | 6 | | 43 | 1 | | 44 | 5 | | 45 | 4 | | 46 | 1 | | 47 | 7 | | 48 | 4 | | 49 | 9 |
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| 47.71% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 6 | | diversityRatio | 0.21374045801526717 | | totalSentences | 262 | | uniqueOpeners | 56 | |
| 26.67% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 125 | | matches | | 0 | "Then the morning after." |
| | ratio | 0.008 | |
| 88.80% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 41 | | totalSentences | 125 | | matches | | 0 | "She kept her fingers wrapped" | | 1 | "His mouth curved, but the" | | 2 | "His attention paused at her" | | 3 | "It still struck like a" | | 4 | "Her grip tightened on the" | | 5 | "he reminded her" | | 6 | "She released the chain and" | | 7 | "His charcoal suit carried the" | | 8 | "He tapped the tip of" | | 9 | "She turned towards him." | | 10 | "He removed his gloves, finger" | | 11 | "His jaw tightened." | | 12 | "Her voice held steady." | | 13 | "It rose beneath each word," | | 14 | "His hand stopped." | | 15 | "He drew out a folded" | | 16 | "She had seen it in" | | 17 | "She had never met him." | | 18 | "She looked at him." | | 19 | "His amber eye held hers." |
| | ratio | 0.328 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 115 | | totalSentences | 125 | | matches | | 0 | "The door opened three inches," | | 1 | "Aurora Carter stared at him." | | 2 | "Ptolemy wound between her ankles," | | 3 | "Lucien lifted one gloved hand." | | 4 | "She kept her fingers wrapped" | | 5 | "His mouth curved, but the" | | 6 | "The other held its usual" | | 7 | "Lucien glanced down." | | 8 | "Lucien’s gaze moved over her" | | 9 | "His attention paused at her" | | 10 | "The pause lasted half a" | | 11 | "It still struck like a" | | 12 | "Aurora gave a short laugh." | | 13 | "Her grip tightened on the" | | 14 | "Lucien watched her notice the" | | 15 | "he reminded her" | | 16 | "She released the chain and" | | 17 | "Lucien stepped inside with the" | | 18 | "His charcoal suit carried the" | | 19 | "He tapped the tip of" |
| | ratio | 0.92 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 125 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 38 | | technicalSentenceCount | 2 | | matches | | 0 | "It rose beneath each word, hot and familiar, as if the three months since he had left had done nothing but teach it patience." | | 1 | "Matteo Voss had been the broker who sold information about crossings between Earth and Avaros." |
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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 | 9 | | fancyCount | 2 | | fancyTags | | 0 | "she whispered (whisper)" | | 1 | "he murmured (murmur)" |
| | dialogueSentences | 138 | | tagDensity | 0.065 | | leniency | 0.13 | | rawRatio | 0.222 | | effectiveRatio | 0.029 | |