| 77.7778% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 6 | | adverbTagCount | 1 | | adverbTags | | 0 | "Silas said gently, as if reading her thoughts [gently]" |
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| 34.7471% | AI-ism adverb frequency | Target: <1% AI-ism adverbs (57 tracked) | | wordCount | 613 | | totalAiIsmAdverbs | 4 | | found | | 0 | | | 1 | | adverb | "barely above a whisper" | | count | 1 |
| | 2 | | | 3 | |
| | highlights | | 0 | "gently" | | 1 | "barely above a whisper" | | 2 | "really" | | 3 | "truly" |
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| 100.0000% | AI-ism character names | Target: 0 AI-default names (16 tracked, −20% each) | | codexExemptions | | | found | (empty) | |
| 100.0000% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 0.0000% | AI-ism word frequency | Target: <1% AI-ism words (140 tracked) | | wordCount | 613 | | totalAiIsms | 7 | | found | | | highlights | | 0 | "flickered" | | 1 | "flicker" | | 2 | "glinting" | | 3 | "unspoken" | | 4 | "solace" | | 5 | "weight" | | 6 | "echoed" |
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| 0.0000% | Cliche density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 5 | | maxInWindow | 5 | | found | | 0 | | label | "heart pounded in chest" | | count | 1 |
| | 1 | | label | "lump in throat" | | count | 1 |
| | 2 | | label | "couldn't help but" | | count | 2 |
| | 3 | | label | "flicker of emotion" | | count | 1 |
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| | highlights | | 0 | "heart pounded in her chest" | | 1 | "A lump formed in her throat" | | 2 | "couldn't help but feel" | | 3 | "couldn't help but wonder" | | 4 | "a flicker of recognition" |
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| 100.0000% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 34 | | matches | (empty) | |
| 100.0000% | Filter word density | Target: ≤12% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 34 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.0000% | Overuse of "that" (subordinate clause padding) | Target: ≤10% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 47 | | matches | | |
| 81.8421% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 23 | | mean | 26.52 | | std | 11.58 | | cv | 0.436 | | sampleLengths | | 0 | 55 | | 1 | 56 | | 2 | 19 | | 3 | 16 | | 4 | 44 | | 5 | 18 | | 6 | 15 | | 7 | 25 | | 8 | 21 | | 9 | 30 | | 10 | 22 | | 11 | 24 | | 12 | 33 | | 13 | 32 | | 14 | 13 | | 15 | 19 | | 16 | 32 | | 17 | 23 | | 18 | 21 | | 19 | 26 | | 20 | 20 | | 21 | 13 | | 22 | 33 |
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| 100.0000% | Passive voice overuse | Target: ≤5% passive sentences | | passiveCount | 0 | | totalSentences | 34 | | matches | (empty) | |
| 100.0000% | Past progressive (was/were + -ing) overuse | Target: ≤10% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 81 | | matches | (empty) | |
| 100.0000% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 464 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 13 | | adverbRatio | 0.028017241379310345 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.010775862068965518 | |
| 100.0000% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 47 | | echoCount | 0 | | echoWords | (empty) | |
| 100.0000% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 47 | | mean | 12.98 | | std | 5.77 | | cv | 0.445 | | sampleLengths | | 0 | 26 | | 1 | 15 | | 2 | 14 | | 3 | 22 | | 4 | 14 | | 5 | 20 | | 6 | 15 | | 7 | 4 | | 8 | 9 | | 9 | 7 | | 10 | 17 | | 11 | 14 | | 12 | 13 | | 13 | 15 | | 14 | 3 | | 15 | 5 | | 16 | 10 | | 17 | 8 | | 18 | 17 | | 19 | 11 | | 20 | 10 | | 21 | 15 | | 22 | 15 | | 23 | 22 | | 24 | 12 | | 25 | 12 | | 26 | 14 | | 27 | 19 | | 28 | 16 | | 29 | 16 | | 30 | 9 | | 31 | 4 | | 32 | 14 | | 33 | 5 | | 34 | 15 | | 35 | 17 | | 36 | 13 | | 37 | 10 | | 38 | 10 | | 39 | 11 | | 40 | 13 | | 41 | 13 | | 42 | 13 | | 43 | 7 | | 44 | 5 | | 45 | 8 | | 46 | 33 |
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| 75.8865% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 1 | | diversityRatio | 0.46808510638297873 | | totalSentences | 47 | | uniqueOpeners | 22 | |
| 50.0000% | Dialogue tag variety (said vs. fancy) | Target: ≤30% fancy dialogue tags | | totalTags | 6 | | fancyCount | 3 | | fancyTags | | 0 | "he said, his voice warm with genuine affection (say, warm)" | | 1 | "Rory replied, mustering a smile (reply, muster)" | | 2 | "Silas said gently, as if reading her thoughts (say gently, read)" |
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