| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 12 | | adverbTagCount | 1 | | adverbTags | | 0 | "he said simply [simply]" |
| | dialogueSentences | 45 | | tagDensity | 0.267 | | leniency | 0.533 | | rawRatio | 0.083 | | effectiveRatio | 0.044 | |
| 85.99% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 714 | | totalAiIsmAdverbs | 2 | | found | | | highlights | | |
| 100.00% | AI-ism character names | Target: 0 AI-default names (16 tracked, −20% each) | | codexExemptions | | | found | (empty) | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 36.97% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 714 | | totalAiIsms | 9 | | found | | | highlights | | 0 | "scanning" | | 1 | "flickered" | | 2 | "flicked" | | 3 | "predictable" | | 4 | "eyebrow" | | 5 | "silence" | | 6 | "traced" | | 7 | "weight" |
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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 | 64 | | matches | (empty) | |
| 98.21% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 2 | | narrationSentences | 64 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 95 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 21 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 711 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 4 | | unquotedAttributions | 0 | | matches | (empty) | |
| 89.27% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 16 | | wordCount | 494 | | uniqueNames | 6 | | maxNameDensity | 1.21 | | worstName | "Aurora" | | maxWindowNameDensity | 2 | | worstWindowName | "Aurora" | | discoveredNames | | Raven | 1 | | Nest | 1 | | Carter | 1 | | Blackwood | 1 | | Aurora | 6 | | Silas | 6 |
| | persons | | 0 | "Nest" | | 1 | "Carter" | | 2 | "Blackwood" | | 3 | "Aurora" | | 4 | "Silas" |
| | places | | | globalScore | 0.893 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 39 | | 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 | 711 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 95 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 39 | | mean | 18.23 | | std | 13.39 | | cv | 0.734 | | sampleLengths | | 0 | 69 | | 1 | 7 | | 2 | 53 | | 3 | 11 | | 4 | 22 | | 5 | 24 | | 6 | 28 | | 7 | 23 | | 8 | 8 | | 9 | 19 | | 10 | 10 | | 11 | 22 | | 12 | 40 | | 13 | 5 | | 14 | 9 | | 15 | 10 | | 16 | 13 | | 17 | 7 | | 18 | 11 | | 19 | 28 | | 20 | 6 | | 21 | 10 | | 22 | 25 | | 23 | 12 | | 24 | 21 | | 25 | 8 | | 26 | 17 | | 27 | 36 | | 28 | 13 | | 29 | 14 | | 30 | 14 | | 31 | 9 | | 32 | 20 | | 33 | 8 | | 34 | 30 | | 35 | 8 | | 36 | 5 | | 37 | 9 | | 38 | 27 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 64 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 93 | | matches | (empty) | |
| 82.71% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 3 | | semicolonCount | 0 | | flaggedSentences | 2 | | totalSentences | 95 | | ratio | 0.021 | | matches | | 0 | "His eyes—hazel, unchanged—narrowed slightly as he studied her." | | 1 | "Silas studied her face—the sharpness of her jaw, the way her dark hair fell over her left ear." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 497 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 10 | | adverbRatio | 0.02012072434607646 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.01006036217303823 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 95 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 95 | | mean | 7.48 | | std | 4.57 | | cv | 0.611 | | sampleLengths | | 0 | 17 | | 1 | 14 | | 2 | 5 | | 3 | 17 | | 4 | 16 | | 5 | 6 | | 6 | 1 | | 7 | 2 | | 8 | 13 | | 9 | 13 | | 10 | 17 | | 11 | 8 | | 12 | 7 | | 13 | 4 | | 14 | 4 | | 15 | 15 | | 16 | 3 | | 17 | 6 | | 18 | 13 | | 19 | 1 | | 20 | 2 | | 21 | 2 | | 22 | 3 | | 23 | 21 | | 24 | 4 | | 25 | 10 | | 26 | 13 | | 27 | 4 | | 28 | 4 | | 29 | 14 | | 30 | 5 | | 31 | 7 | | 32 | 3 | | 33 | 11 | | 34 | 11 | | 35 | 14 | | 36 | 18 | | 37 | 8 | | 38 | 5 | | 39 | 6 | | 40 | 3 | | 41 | 5 | | 42 | 5 | | 43 | 6 | | 44 | 7 | | 45 | 2 | | 46 | 5 | | 47 | 6 | | 48 | 5 | | 49 | 13 |
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| 71.58% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 2 | | diversityRatio | 0.4421052631578947 | | totalSentences | 95 | | uniqueOpeners | 42 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 56 | | matches | (empty) | | ratio | 0 | |
| 0.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 34 | | totalSentences | 56 | | matches | | 0 | "She paused, scanning the room." | | 1 | "Her fingers brushed the small" | | 2 | "His beard was shorter now," | | 3 | "He wore a dark coat," | | 4 | "His eyes—hazel, unchanged—narrowed slightly as" | | 5 | "she said, voice steady but" | | 6 | "He nodded once, slow." | | 7 | "His gaze flicked to her" | | 8 | "She’d always been the same" | | 9 | "He smiled faintly." | | 10 | "His hand moved to the" | | 11 | "She gestured to the bag" | | 12 | "She took a seat at" | | 13 | "He leaned forward, elbows on" | | 14 | "Her eyes drifted to the" | | 15 | "he said simply" | | 16 | "She met his gaze" | | 17 | "He exhaled through his nose." | | 18 | "Her voice softened" | | 19 | "His tone was gentle, but" |
| | ratio | 0.607 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 54 | | totalSentences | 56 | | matches | | 0 | "The air inside The Raven’s" | | 1 | "Aurora Carter pushed through the" | | 2 | "She paused, scanning the room." | | 3 | "The green neon sign flickered" | | 4 | "Her fingers brushed the small" | | 5 | "A voice cut through the" | | 6 | "Silas Blackwood stood near the" | | 7 | "His beard was shorter now," | | 8 | "He wore a dark coat," | | 9 | "His eyes—hazel, unchanged—narrowed slightly as" | | 10 | "she said, voice steady but" | | 11 | "He nodded once, slow." | | 12 | "His gaze flicked to her" | | 13 | "Aurora shrugged, though it wasn’t" | | 14 | "She’d always been the same" | | 15 | "He smiled faintly." | | 16 | "His hand moved to the" | | 17 | "She gestured to the bag" | | 18 | "Silas raised an eyebrow." | | 19 | "She took a seat at" |
| | ratio | 0.964 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 56 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 18 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 41.67% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 12 | | uselessAdditionCount | 2 | | matches | | 0 | "she said, voice steady but cautious" | | 1 | "His hand moved, fingers drumming a rhythm only he knew" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 3 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 45 | | tagDensity | 0.067 | | leniency | 0.133 | | rawRatio | 0 | | effectiveRatio | 0 | |