| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 2 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 4 | | tagDensity | 0.5 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 47.74% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 861 | | totalAiIsmAdverbs | 9 | | found | | | highlights | | 0 | "slowly" | | 1 | "tightly" | | 2 | "quickly" | | 3 | "slightly" | | 4 | "very" | | 5 | "suddenly" | | 6 | "softly" |
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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) | |
| 0.00% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 861 | | totalAiIsms | 26 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | | | 13 | | | 14 | | | 15 | | | 16 | | | 17 | | | 18 | |
| | highlights | | 0 | "gloom" | | 1 | "reminder" | | 2 | "chill" | | 3 | "footsteps" | | 4 | "oppressive" | | 5 | "silence" | | 6 | "pounding" | | 7 | "flicker" | | 8 | "scanning" | | 9 | "racing" | | 10 | "pulsed" | | 11 | "could feel" | | 12 | "quickened" | | 13 | "looming" | | 14 | "loomed" | | 15 | "glinting" | | 16 | "warmth" | | 17 | "unravel" | | 18 | "sentinels" |
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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 | 48 | | matches | (empty) | |
| 0.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 8 | | narrationSentences | 48 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 50 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 31 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 861 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 4 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 3 | | wordCount | 850 | | uniqueNames | 3 | | maxNameDensity | 0.12 | | worstName | "Fae" | | maxWindowNameDensity | 0 | | worstWindowName | (null) | | discoveredNames | | | persons | | | places | | | globalScore | 1 | | windowScore | 1 | |
| 0.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 48 | | glossingSentenceCount | 3 | | matches | | 0 | "seemed wrong their petals twisted and mutated into shapes that defied nature" | | 1 | "wrongness that seemed to seep into the very air around her" | | 2 | "branches that seemed to reach for her" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 861 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 50 | | matches | (empty) | |
| 37.19% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 18 | | mean | 47.83 | | std | 13.4 | | cv | 0.28 | | sampleLengths | | 0 | 68 | | 1 | 52 | | 2 | 45 | | 3 | 50 | | 4 | 42 | | 5 | 57 | | 6 | 11 | | 7 | 51 | | 8 | 60 | | 9 | 46 | | 10 | 57 | | 11 | 45 | | 12 | 19 | | 13 | 58 | | 14 | 46 | | 15 | 49 | | 16 | 59 | | 17 | 46 |
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| 97.95% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 48 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 147 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 50 | | ratio | 0 | | matches | (empty) | |
| 88.68% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 850 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 45 | | adverbRatio | 0.052941176470588235 | | lyAdverbCount | 17 | | lyAdverbRatio | 0.02 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 50 | | echoCount | 0 | | echoWords | (empty) | |
| 86.27% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 50 | | mean | 17.22 | | std | 6.3 | | cv | 0.366 | | sampleLengths | | 0 | 24 | | 1 | 25 | | 2 | 19 | | 3 | 17 | | 4 | 14 | | 5 | 21 | | 6 | 26 | | 7 | 19 | | 8 | 17 | | 9 | 19 | | 10 | 14 | | 11 | 15 | | 12 | 27 | | 13 | 22 | | 14 | 20 | | 15 | 15 | | 16 | 9 | | 17 | 2 | | 18 | 15 | | 19 | 14 | | 20 | 22 | | 21 | 18 | | 22 | 24 | | 23 | 18 | | 24 | 16 | | 25 | 13 | | 26 | 10 | | 27 | 7 | | 28 | 11 | | 29 | 9 | | 30 | 22 | | 31 | 15 | | 32 | 10 | | 33 | 12 | | 34 | 23 | | 35 | 15 | | 36 | 4 | | 37 | 11 | | 38 | 16 | | 39 | 31 | | 40 | 22 | | 41 | 13 | | 42 | 11 | | 43 | 28 | | 44 | 21 | | 45 | 16 | | 46 | 15 | | 47 | 28 | | 48 | 24 | | 49 | 22 |
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| 59.33% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 2 | | diversityRatio | 0.38 | | totalSentences | 50 | | uniqueOpeners | 19 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 48 | | matches | | 0 | "Instead, they seemed wrong, their" | | 1 | "Slowly, she forced herself to" |
| | ratio | 0.042 | |
| 86.67% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 16 | | totalSentences | 48 | | matches | | 0 | "She glanced down at the" | | 1 | "She had come here for" | | 2 | "She strained her ears, trying" | | 3 | "She couldn't tell how long" | | 4 | "She whipped her head around," | | 5 | "she called out, her voice" | | 6 | "She quickened her pace, desperate" | | 7 | "She staggered back, her breath" | | 8 | "She squeezed her eyes shut," | | 9 | "She turned to run, but" | | 10 | "she whispered, her voice barely" | | 11 | "It didn't answer, only reached" | | 12 | "She stumbled back, her feet" | | 13 | "She ran until her lungs" | | 14 | "She collapsed to her knees," | | 15 | "She had come here for" |
| | ratio | 0.333 | |
| 85.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 36 | | totalSentences | 48 | | matches | | 0 | "Rory stood at the edge" | | 1 | "The thick canopy of leaves" | | 2 | "She glanced down at the" | | 3 | "The wildflowers blooming around her" | | 4 | "A chill ran through her" | | 5 | "She had come here for" | | 6 | "A rustling in the bushes" | | 7 | "She strained her ears, trying" | | 8 | "Time seemed to stretch and" | | 9 | "She couldn't tell how long" | | 10 | "A flicker of movement caught" | | 11 | "She whipped her head around," | | 12 | "Another flicker, this time on" | | 13 | "she called out, her voice" | | 14 | "The pendant pulsed against her" | | 15 | "Something was wrong, she could" | | 16 | "She quickened her pace, desperate" | | 17 | "The path ahead of her" | | 18 | "A hand brushed against her" | | 19 | "She staggered back, her breath" |
| | ratio | 0.75 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 48 | | matches | (empty) | | ratio | 0 | |
| 29.22% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 44 | | technicalSentenceCount | 7 | | matches | | 0 | "Rory stood at the edge of the Fae Grove, her hand resting on one of the ancient oak standing stones that marked its boundary." | | 1 | "She had come here for answers, drawn by the pendant's insistent pull and the cryptic words of the mysterious benefactor who had given it to her." | | 2 | "A rustling in the bushes to her left made her freeze, her heart pounding in her chest." | | 3 | "The trees around her were no longer oak, but twisted, black things with sharp, jagged branches that seemed to reach for her." | | 4 | "The wildflowers were gone, replaced by a thick, slimy moss that squelched beneath her feet." | | 5 | "She turned to run, but the thing was in front of her now, its form shifting and changing like smoke in the wind." | | 6 | "She collapsed to her knees, gasping for breath, her whole body trembling with exhaustion and fear." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 2 | | uselessAdditionCount | 2 | | matches | | 0 | "she called out, her voice trembling slightly" | | 1 | "she whispered, her voice barely audible over the pounding of her heart" |
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| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 2 | | fancyCount | 2 | | fancyTags | | 0 | "she called out (call out)" | | 1 | "she whispered (whisper)" |
| | dialogueSentences | 4 | | tagDensity | 0.5 | | leniency | 1 | | rawRatio | 1 | | effectiveRatio | 1 | |