| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 2 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 3 | | tagDensity | 0.667 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 759 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 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 | 759 | | totalAiIsms | 18 | | found | | | highlights | | 0 | "pulse" | | 1 | "whisper" | | 2 | "echoed" | | 3 | "silence" | | 4 | "flicker" | | 5 | "chill" | | 6 | "pulsed" | | 7 | "trembled" | | 8 | "traced" | | 9 | "shattered" | | 10 | "glinting" | | 11 | "warmth" | | 12 | "mosaic" | | 13 | "vibrated" | | 14 | "loomed" | | 15 | "flickered" | | 16 | "chilled" |
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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 | 68 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 2 | | narrationSentences | 68 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 69 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 25 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 3 | | markdownWords | 8 | | totalWords | 748 | | ratio | 0.011 | | matches | | 0 | "Fae-touched ground" | | 1 | "Why did they erase her?" | | 2 | "Stay." |
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| 62.50% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 4 | | unquotedAttributions | 1 | | matches | | 0 | "*Fae-touched ground*, they called it." |
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| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 10 | | wordCount | 738 | | uniqueNames | 4 | | maxNameDensity | 0.68 | | worstName | "Aurora" | | maxWindowNameDensity | 1 | | worstWindowName | "Aurora" | | discoveredNames | | Heartstone | 1 | | Pendant | 1 | | Fae | 3 | | Aurora | 5 |
| | persons | | 0 | "Pendant" | | 1 | "Fae" | | 2 | "Aurora" |
| | places | (empty) | | globalScore | 1 | | windowScore | 1 | |
| 53.85% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 52 | | glossingSentenceCount | 2 | | matches | | 0 | "as if expecting her" | | 1 | "felt like a blade poised at her throat" |
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| 66.31% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 1.337 | | wordCount | 748 | | matches | | 0 | "not with moss but something darker" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 69 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 17 | | mean | 44 | | std | 24.12 | | cv | 0.548 | | sampleLengths | | 0 | 72 | | 1 | 80 | | 2 | 35 | | 3 | 62 | | 4 | 70 | | 5 | 67 | | 6 | 11 | | 7 | 53 | | 8 | 51 | | 9 | 58 | | 10 | 18 | | 11 | 49 | | 12 | 46 | | 13 | 2 | | 14 | 52 | | 15 | 5 | | 16 | 17 |
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| 84.62% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 4 | | totalSentences | 68 | | matches | | 0 | "were overturned" | | 1 | "were lined" | | 2 | "was scratched" | | 3 | "was gone" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 131 | | matches | | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 11 | | semicolonCount | 0 | | flaggedSentences | 10 | | totalSentences | 69 | | ratio | 0.145 | | matches | | 0 | "The air smelled of damp earth and something sharper—metallic, almost like blood." | | 1 | "A draft swept past her, carrying the whisper of voices—low, guttural, speaking in a language she didn’t recognize but somehow understood." | | 2 | "The chapel echoed with a laugh—not hers, not anyone’s she knew." | | 3 | "Then—a flicker." | | 4 | "She remembered the stories—how the Fae demanded offerings, how they traded beauty for decay." | | 5 | "She’d come here to find answers—her mother’s disappearance, the whispers in her dreams—but the truth felt like a blade poised at her throat." | | 6 | "A figure materialized at the edge of her vision—a silhouette with too many limbs, its head tilting in a way that defied anatomy." | | 7 | "Somewhere in the distance, a bell tolled—a deep, resonant sound that vibrated in her molars." | | 8 | "Her reflection stared back, but the eyes were wrong—pupils dilated, irises swirling with black." | | 9 | "In the darkness, she heard the laughter again—closer now, a swarm of tiny, cruel voices." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 751 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 22 | | adverbRatio | 0.02929427430093209 | | lyAdverbCount | 1 | | lyAdverbRatio | 0.0013315579227696406 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 69 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 69 | | mean | 10.84 | | std | 6.36 | | cv | 0.587 | | sampleLengths | | 0 | 25 | | 1 | 16 | | 2 | 19 | | 3 | 12 | | 4 | 13 | | 5 | 19 | | 6 | 21 | | 7 | 3 | | 8 | 17 | | 9 | 5 | | 10 | 2 | | 11 | 8 | | 12 | 8 | | 13 | 11 | | 14 | 8 | | 15 | 9 | | 16 | 20 | | 17 | 21 | | 18 | 12 | | 19 | 5 | | 20 | 10 | | 21 | 1 | | 22 | 6 | | 23 | 2 | | 24 | 16 | | 25 | 17 | | 26 | 11 | | 27 | 1 | | 28 | 1 | | 29 | 13 | | 30 | 12 | | 31 | 11 | | 32 | 14 | | 33 | 12 | | 34 | 5 | | 35 | 6 | | 36 | 5 | | 37 | 6 | | 38 | 10 | | 39 | 13 | | 40 | 7 | | 41 | 17 | | 42 | 3 | | 43 | 23 | | 44 | 13 | | 45 | 10 | | 46 | 1 | | 47 | 1 | | 48 | 23 | | 49 | 2 |
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| 49.28% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 6 | | diversityRatio | 0.34782608695652173 | | totalSentences | 69 | | uniqueOpeners | 24 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 59 | | matches | | 0 | "Just the silence, thick and" | | 1 | "Somewhere in the distance, a" | | 2 | "Somewhere, a door creaked open." |
| | ratio | 0.051 | |
| 97.97% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 18 | | totalSentences | 59 | | matches | | 0 | "She clutched the Heartstone Pendant" | | 1 | "Her breath hitched." | | 2 | "She’d read about these places" | | 3 | "Her childhood friend’s voice, but" | | 4 | "It slithered through the rafters," | | 5 | "She stepped forward, the pendant" | | 6 | "It writhed, then split into" | | 7 | "They circled her, slow and" | | 8 | "She yanked her leg back," | | 9 | "She remembered the stories—how the" | | 10 | "Her fingers trembled as she" | | 11 | "She backed toward the entrance," | | 12 | "Her throat tightened." | | 13 | "She’d come here to find" | | 14 | "Its surface was slick, not" | | 15 | "it hissed, its voice a" | | 16 | "Her breath came in shallow" | | 17 | "Her reflection stared back, but" |
| | ratio | 0.305 | |
| 53.22% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 48 | | totalSentences | 59 | | matches | | 0 | "Aurora’s boots sank into the" | | 1 | "The moon hung low, a" | | 2 | "She clutched the Heartstone Pendant" | | 3 | "The air smelled of damp" | | 4 | "The door creaked open before" | | 5 | "A draft swept past her," | | 6 | "Her breath hitched." | | 7 | "She’d read about these places" | | 8 | "The name slipped out, raw" | | 9 | "Her childhood friend’s voice, but" | | 10 | "The chapel echoed with a" | | 11 | "It slithered through the rafters," | | 12 | "She stepped forward, the pendant" | | 13 | "The walls were lined with" | | 14 | "The face was scratched out," | | 15 | "A floorboard groaned behind her." | | 16 | "Aurora spun, hand flying to" | | 17 | "A shadow detaching itself from" | | 18 | "It writhed, then split into" | | 19 | "They circled her, slow and" |
| | ratio | 0.814 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 59 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 39 | | technicalSentenceCount | 2 | | matches | | 0 | "Inside, the pews were overturned, their wooden frames splintered as though something had tried to claw their way out." | | 1 | "A figure materialized at the edge of her vision—a silhouette with too many limbs, its head tilting in a way that defied anatomy." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 2 | | uselessAdditionCount | 1 | | matches | | 0 | "it hissed, its voice a chorus of overlapping tones" |
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| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 1 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 3 | | tagDensity | 0.333 | | leniency | 0.667 | | rawRatio | 1 | | effectiveRatio | 0.667 | |