| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 2 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 5 | | tagDensity | 0.4 | | leniency | 0.8 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 87.26% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 785 | | 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) | |
| 0.00% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 785 | | totalAiIsms | 21 | | found | | | highlights | | 0 | "loomed" | | 1 | "sentinels" | | 2 | "pulsed" | | 3 | "warmth" | | 4 | "shimmered" | | 5 | "pulse" | | 6 | "silence" | | 7 | "whisper" | | 8 | "familiar" | | 9 | "weight" | | 10 | "flicker" | | 11 | "trembled" | | 12 | "wavered" | | 13 | "dancing" | | 14 | "stomach" | | 15 | "reminder" |
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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 | 101 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 101 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 104 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 25 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 6 | | markdownWords | 7 | | totalWords | 784 | | ratio | 0.009 | | matches | | 0 | "watching. Waiting." | | 1 | "hungry." | | 2 | "Movement." | | 3 | "Rory." | | 4 | "People." | | 5 | "Run." |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 2 | | unquotedAttributions | 0 | | matches | (empty) | |
| 77.92% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 21 | | wordCount | 763 | | uniqueNames | 7 | | maxNameDensity | 1.44 | | worstName | "Rory" | | maxWindowNameDensity | 2 | | worstWindowName | "Rory" | | discoveredNames | | Heartstone | 1 | | Grove | 5 | | November | 1 | | Rory | 11 | | Richmond | 1 | | Park | 1 | | London | 1 |
| | persons | | | places | | 0 | "Grove" | | 1 | "November" | | 2 | "Richmond" | | 3 | "Park" | | 4 | "London" |
| | globalScore | 0.779 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 58 | | 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 | 784 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 104 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 43 | | mean | 18.23 | | std | 13.97 | | cv | 0.766 | | sampleLengths | | 0 | 62 | | 1 | 47 | | 2 | 31 | | 3 | 16 | | 4 | 37 | | 5 | 3 | | 6 | 33 | | 7 | 1 | | 8 | 17 | | 9 | 32 | | 10 | 4 | | 11 | 32 | | 12 | 10 | | 13 | 30 | | 14 | 14 | | 15 | 28 | | 16 | 1 | | 17 | 25 | | 18 | 19 | | 19 | 15 | | 20 | 11 | | 21 | 1 | | 22 | 26 | | 23 | 1 | | 24 | 19 | | 25 | 10 | | 26 | 4 | | 27 | 29 | | 28 | 6 | | 29 | 4 | | 30 | 18 | | 31 | 1 | | 32 | 39 | | 33 | 27 | | 34 | 4 | | 35 | 31 | | 36 | 9 | | 37 | 29 | | 38 | 15 | | 39 | 14 | | 40 | 16 | | 41 | 7 | | 42 | 6 |
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| 98.32% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 101 | | matches | | |
| 93.33% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 125 | | matches | | 0 | "was holding" | | 1 | "was clear—*watching" |
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| 5.49% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 5 | | semicolonCount | 0 | | flaggedSentences | 5 | | totalSentences | 104 | | ratio | 0.048 | | matches | | 0 | "The air smelled of wet moss and something sweeter—wildflowers, though it was the wrong season for them." | | 1 | "The words were too soft to make out, but the intent was clear—*watching." | | 2 | "The beam cut through the dark, illuminating the gnarled roots, the wildflowers, the—" | | 3 | "The shadows stretched, twisting into shapes that almost looked like—" | | 4 | "Rory lunged for the gap between them, her fingers scraping against the bark as she hurled herself through—" |
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| 86.90% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 764 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 42 | | adverbRatio | 0.0549738219895288 | | lyAdverbCount | 8 | | lyAdverbRatio | 0.010471204188481676 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 104 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 104 | | mean | 7.54 | | std | 5.12 | | cv | 0.679 | | sampleLengths | | 0 | 14 | | 1 | 17 | | 2 | 17 | | 3 | 14 | | 4 | 4 | | 5 | 25 | | 6 | 18 | | 7 | 9 | | 8 | 5 | | 9 | 4 | | 10 | 13 | | 11 | 7 | | 12 | 9 | | 13 | 19 | | 14 | 4 | | 15 | 3 | | 16 | 2 | | 17 | 9 | | 18 | 3 | | 19 | 2 | | 20 | 14 | | 21 | 8 | | 22 | 9 | | 23 | 1 | | 24 | 2 | | 25 | 15 | | 26 | 7 | | 27 | 6 | | 28 | 5 | | 29 | 14 | | 30 | 4 | | 31 | 13 | | 32 | 5 | | 33 | 13 | | 34 | 1 | | 35 | 10 | | 36 | 9 | | 37 | 6 | | 38 | 15 | | 39 | 2 | | 40 | 10 | | 41 | 2 | | 42 | 15 | | 43 | 13 | | 44 | 1 | | 45 | 8 | | 46 | 5 | | 47 | 8 | | 48 | 1 | | 49 | 3 |
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| 45.83% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 9 | | diversityRatio | 0.3269230769230769 | | totalSentences | 104 | | uniqueOpeners | 34 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 13 | | totalSentences | 84 | | matches | | 0 | "Just the faint rustle of" | | 1 | "Just the trees, their bark" | | 2 | "Just the press of silence," | | 3 | "Maybe she’d imagined the pulsing." | | 4 | "Maybe the stress of the" | | 5 | "Then the whisper came." | | 6 | "Just the shadows, deeper than" | | 7 | "Just the trees." | | 8 | "Then the torch died." | | 9 | "Just the trees." | | 10 | "Just the flowers." | | 11 | "Just her, alone in the" | | 12 | "Just stared at the stars," |
| | ratio | 0.155 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 19 | | totalSentences | 84 | | matches | | 0 | "She adjusted the strap of" | | 1 | "She’d come for answers." | | 2 | "She moved deeper into the" | | 3 | "They shouldn’t be blooming." | | 4 | "Their petals shimmered faintly, as" | | 5 | "She stood slowly, her pulse" | | 6 | "She forced herself forward, her" | | 7 | "It slithered through the trees," | | 8 | "Her voice came out sharper" | | 9 | "She whirled, but there was" | | 10 | "She reached into her bag," | | 11 | "she muttered, though her hands" | | 12 | "She stumbled back, her boot" | | 13 | "Their limbs bending in ways" | | 14 | "She fumbled with the switch," | | 15 | "She bolted, her bag bouncing" | | 16 | "Her lungs burned, her boots" | | 17 | "She didn’t look back." | | 18 | "She didn’t move." |
| | ratio | 0.226 | |
| 100.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 56 | | totalSentences | 84 | | matches | | 0 | "The ancient oaks loomed like" | | 1 | "Rory stepped over the threshold" | | 2 | "The air smelled of wet" | | 3 | "She adjusted the strap of" | | 4 | "She’d come for answers." | | 5 | "The pendant had pulsed all" | | 6 | "The clearing stretched before her," | | 7 | "Rory exhaled, her fingers brushing" | | 8 | "She moved deeper into the" | | 9 | "They shouldn’t be blooming." | | 10 | "Their petals shimmered faintly, as" | | 11 | "A twig snapped." | | 12 | "The sound had come from" | | 13 | "She stood slowly, her pulse" | | 14 | "She forced herself forward, her" | | 15 | "The pendant was cold again," | | 16 | "It slithered through the trees," | | 17 | "Rory spun, her heart hammering." | | 18 | "The words were too soft" | | 19 | "Her voice came out sharper" |
| | ratio | 0.667 | |
| 59.52% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 84 | | matches | | | ratio | 0.012 | |
| 71.43% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 30 | | technicalSentenceCount | 3 | | matches | | 0 | "Their limbs bending in ways that made her stomach clench." | | 1 | "Behind her, the whispers rose into a chorus, a hissing, clicking sound that set her teeth on edge." | | 2 | "Rory rolled onto her back, her chest heaving, the torch beam trembling in her grip." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 2 | | uselessAdditionCount | 1 | | matches | | 0 | "she muttered, though her hands trembled" |
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| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 1 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 5 | | tagDensity | 0.2 | | leniency | 0.4 | | rawRatio | 1 | | effectiveRatio | 0.4 | |