| 88.89% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 15 | | adverbTagCount | 2 | | adverbTags | | 0 | "She stepped aside [aside]" | | 1 | "he said softly [softly]" |
| | dialogueSentences | 36 | | tagDensity | 0.417 | | leniency | 0.833 | | rawRatio | 0.133 | | effectiveRatio | 0.111 | |
| 76.04% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 626 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | 0 | "really" | | 1 | "softly" | | 2 | "tenderly" |
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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) | |
| 28.12% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 626 | | totalAiIsms | 9 | | found | | | highlights | | 0 | "unreadable" | | 1 | "gleaming" | | 2 | "navigated" | | 3 | "weight" | | 4 | "silence" | | 5 | "wavered" | | 6 | "tension" | | 7 | "absolutely" | | 8 | "tracing" |
| |
| 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 | 34 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 34 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 55 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 35 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 627 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 5 | | unquotedAttributions | 0 | | matches | (empty) | |
| 77.11% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 16 | | wordCount | 343 | | uniqueNames | 6 | | maxNameDensity | 1.46 | | worstName | "Lucien" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Lucien" | | discoveredNames | | Lucien | 5 | | Eva | 2 | | Ptolemy | 3 | | Aurora | 4 | | Heat | 1 | | French | 1 |
| | persons | | 0 | "Lucien" | | 1 | "Eva" | | 2 | "Ptolemy" | | 3 | "Aurora" | | 4 | "Heat" |
| | places | (empty) | | globalScore | 0.771 | | windowScore | 1 | |
| 50.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 25 | | glossingSentenceCount | 1 | | matches | | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 627 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 55 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 28 | | mean | 22.39 | | std | 11.67 | | cv | 0.521 | | sampleLengths | | 0 | 26 | | 1 | 13 | | 2 | 12 | | 3 | 30 | | 4 | 17 | | 5 | 35 | | 6 | 21 | | 7 | 30 | | 8 | 5 | | 9 | 12 | | 10 | 39 | | 11 | 4 | | 12 | 17 | | 13 | 20 | | 14 | 16 | | 15 | 33 | | 16 | 7 | | 17 | 30 | | 18 | 4 | | 19 | 26 | | 20 | 32 | | 21 | 18 | | 22 | 23 | | 23 | 26 | | 24 | 17 | | 25 | 31 | | 26 | 26 | | 27 | 57 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 34 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 67 | | matches | (empty) | |
| 90.91% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 2 | | semicolonCount | 0 | | flaggedSentences | 1 | | totalSentences | 55 | | ratio | 0.018 | | matches | | 0 | "The way he said her name — soft, almost reverent — made her chest ache." |
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| 99.18% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 342 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 14 | | adverbRatio | 0.04093567251461988 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.014619883040935672 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 55 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 55 | | mean | 11.4 | | std | 6.28 | | cv | 0.551 | | sampleLengths | | 0 | 15 | | 1 | 11 | | 2 | 13 | | 3 | 8 | | 4 | 4 | | 5 | 10 | | 6 | 17 | | 7 | 3 | | 8 | 11 | | 9 | 6 | | 10 | 15 | | 11 | 20 | | 12 | 7 | | 13 | 14 | | 14 | 12 | | 15 | 18 | | 16 | 5 | | 17 | 4 | | 18 | 8 | | 19 | 8 | | 20 | 18 | | 21 | 13 | | 22 | 4 | | 23 | 13 | | 24 | 4 | | 25 | 15 | | 26 | 5 | | 27 | 13 | | 28 | 3 | | 29 | 10 | | 30 | 23 | | 31 | 3 | | 32 | 4 | | 33 | 15 | | 34 | 15 | | 35 | 4 | | 36 | 9 | | 37 | 17 | | 38 | 20 | | 39 | 12 | | 40 | 9 | | 41 | 9 | | 42 | 5 | | 43 | 18 | | 44 | 21 | | 45 | 5 | | 46 | 11 | | 47 | 6 | | 48 | 17 | | 49 | 14 |
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| 78.18% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 2 | | diversityRatio | 0.4909090909090909 | | totalSentences | 55 | | uniqueOpeners | 27 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 33 | | matches | (empty) | | ratio | 0 | |
| 26.06% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 16 | | totalSentences | 33 | | matches | | 0 | "She hesitated, glancing over her" | | 1 | "He leaned on his cane," | | 2 | "She stepped aside, letting him" | | 3 | "His cologne, subtle notes of" | | 4 | "He shifted his weight, fingers" | | 5 | "His voice carried an edge" | | 6 | "She touched her left wrist" | | 7 | "His jaw tightened." | | 8 | "She met his gaze, refusing" | | 9 | "He closed the distance between" | | 10 | "Her voice wavered" | | 11 | "he said softly, His free" | | 12 | "He dropped his hand" | | 13 | "she cut in" | | 14 | "His expression softened, vulnerability replacing" | | 15 | "He touched her cheek at" |
| | ratio | 0.485 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 32 | | totalSentences | 33 | | matches | | 0 | "The door creaked open to" | | 1 | "Aurora's fingers tightened around the" | | 2 | "The words came out sharper" | | 3 | "Lucien's mismatched eyes met hers," | | 4 | "She hesitated, glancing over her" | | 5 | "Books teetered in precarious towers" | | 6 | "He leaned on his cane," | | 7 | "The way he said her" | | 8 | "She stepped aside, letting him" | | 9 | "His cologne, subtle notes of" | | 10 | "Ptolemy raised his head, yellow" | | 11 | "The half-demon navigated around the" | | 12 | "Aurora crossed her arms." | | 13 | "A ghost of a smile" | | 14 | "He shifted his weight, fingers" | | 15 | "His voice carried an edge" | | 16 | "She touched her left wrist" | | 17 | "Lucien stepped closer, and she" | | 18 | "Heat crept into her cheeks" | | 19 | "His jaw tightened." |
| | ratio | 0.97 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 33 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 13 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 15 | | uselessAdditionCount | 4 | | matches | | 0 | "He leaned, the ivory handle gleaming" | | 1 | "He shifted, fingers drumming against his cane" | | 2 | "She met, refusing to look away from those strange, beautiful eyes" | | 3 | "He touched, his thumb tracing her jaw" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 3 | | fancyCount | 1 | | fancyTags | | 0 | "Aurora laughed (laugh)" |
| | dialogueSentences | 36 | | tagDensity | 0.083 | | leniency | 0.167 | | rawRatio | 0.333 | | effectiveRatio | 0.056 | |