| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 17 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 33 | | tagDensity | 0.515 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 88.14% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 843 | | 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) | |
| 34.76% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 843 | | totalAiIsms | 11 | | found | | | highlights | | 0 | "pulse" | | 1 | "silk" | | 2 | "whisper" | | 3 | "pulsed" | | 4 | "warmth" | | 5 | "shimmered" | | 6 | "flickered" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 82 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 82 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 98 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 31 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 837 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 12 | | unquotedAttributions | 0 | | matches | (empty) | |
| 34.62% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 42 | | wordCount | 650 | | uniqueNames | 12 | | maxNameDensity | 2.31 | | worstName | "Rory" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Rory" | | discoveredNames | | Richmond | 1 | | Park | 1 | | Heartstone | 3 | | London | 1 | | Isolde | 1 | | Rory | 15 | | Nyx | 6 | | Veil | 2 | | Eva | 6 | | Cardiff | 1 | | Fae | 2 | | Silas | 3 |
| | persons | | 0 | "Heartstone" | | 1 | "Isolde" | | 2 | "Rory" | | 3 | "Nyx" | | 4 | "Veil" | | 5 | "Eva" | | 6 | "Silas" |
| | places | | 0 | "Richmond" | | 1 | "Park" | | 2 | "London" | | 3 | "Cardiff" |
| | globalScore | 0.346 | | windowScore | 0.5 | |
| 87.50% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 40 | | glossingSentenceCount | 1 | | matches | | 0 | "felt like silk wrapped around granite" |
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| 80.53% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 1.195 | | wordCount | 837 | | matches | | 0 | "not a door, but a tear in the fabric, silver" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 98 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 41 | | mean | 20.41 | | std | 14.67 | | cv | 0.719 | | sampleLengths | | 0 | 52 | | 1 | 55 | | 2 | 23 | | 3 | 10 | | 4 | 12 | | 5 | 58 | | 6 | 24 | | 7 | 18 | | 8 | 10 | | 9 | 20 | | 10 | 6 | | 11 | 29 | | 12 | 10 | | 13 | 15 | | 14 | 28 | | 15 | 42 | | 16 | 10 | | 17 | 19 | | 18 | 10 | | 19 | 3 | | 20 | 39 | | 21 | 3 | | 22 | 26 | | 23 | 4 | | 24 | 52 | | 25 | 13 | | 26 | 14 | | 27 | 13 | | 28 | 27 | | 29 | 4 | | 30 | 24 | | 31 | 13 | | 32 | 15 | | 33 | 32 | | 34 | 1 | | 35 | 30 | | 36 | 19 | | 37 | 8 | | 38 | 16 | | 39 | 22 | | 40 | 8 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 82 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 119 | | matches | (empty) | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 6 | | semicolonCount | 0 | | flaggedSentences | 6 | | totalSentences | 98 | | ratio | 0.061 | | matches | | 0 | "Flowers bloomed in impossible spirals—violet, gold, ink-blue—under a moon that was not London's moon." | | 1 | "The air changed pressure, a shimmer she could not see but her skin recognized—a faint distortion, like heat rising from summer asphalt, visible only to those who knew to look." | | 2 | "The wildflowers released scents that changed with each breath—first honey, then iron, then something that reminded Rory of her mother's kitchen in Cardiff, long gone." | | 3 | "A sound came—not wind, not water." | | 4 | "In the center, a portal shimmered—not a door, but a tear in the fabric, silver and faint like a scar in the air." | | 5 | "The shimmer distorted her reflection—bright blue eyes stretched long, black hair floating like ink in water." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 661 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 23 | | adverbRatio | 0.03479576399394856 | | lyAdverbCount | 7 | | lyAdverbRatio | 0.01059001512859304 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 98 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 98 | | mean | 8.54 | | std | 6.15 | | cv | 0.72 | | sampleLengths | | 0 | 19 | | 1 | 12 | | 2 | 9 | | 3 | 3 | | 4 | 9 | | 5 | 17 | | 6 | 24 | | 7 | 14 | | 8 | 4 | | 9 | 19 | | 10 | 5 | | 11 | 5 | | 12 | 5 | | 13 | 7 | | 14 | 5 | | 15 | 19 | | 16 | 14 | | 17 | 20 | | 18 | 9 | | 19 | 15 | | 20 | 18 | | 21 | 9 | | 22 | 1 | | 23 | 13 | | 24 | 2 | | 25 | 5 | | 26 | 6 | | 27 | 9 | | 28 | 12 | | 29 | 8 | | 30 | 10 | | 31 | 2 | | 32 | 10 | | 33 | 3 | | 34 | 15 | | 35 | 13 | | 36 | 4 | | 37 | 30 | | 38 | 2 | | 39 | 6 | | 40 | 5 | | 41 | 5 | | 42 | 7 | | 43 | 12 | | 44 | 4 | | 45 | 6 | | 46 | 3 | | 47 | 3 | | 48 | 11 | | 49 | 25 |
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| 66.33% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 5 | | diversityRatio | 0.42857142857142855 | | totalSentences | 98 | | uniqueOpeners | 42 | |
| 55.56% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 60 | | matches | | | ratio | 0.017 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 13 | | totalSentences | 60 | | matches | | 0 | "Her shoulder-length black hair clung" | | 1 | "She touched the crescent scar" | | 2 | "Her breath formed no mist." | | 3 | "Her bright blue eyes widened." | | 4 | "Their violet eyes glowed softly," | | 5 | "They spoke like a whisper" | | 6 | "They walked deeper." | | 7 | "They rounded a bend and" | | 8 | "Her breath fogged despite the" | | 9 | "Their shadow form flickered, dense" | | 10 | "She moved to the portal's" | | 11 | "They had felt it." | | 12 | "She pressed her palm to" |
| | ratio | 0.217 | |
| 43.33% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 50 | | totalSentences | 60 | | matches | | 0 | "Rory ducked beneath the twisted" | | 1 | "The old oaks marked the" | | 2 | "Her shoulder-length black hair clung" | | 3 | "She touched the crescent scar" | | 4 | "The Heartstone warmed against her" | | 5 | "Eva moved beside her." | | 6 | "Silas followed, boots crunching softly" | | 7 | "Her breath formed no mist." | | 8 | "A clearing spread before them." | | 9 | "Flowers bloomed in impossible spirals—violet," | | 10 | "Rory drew the moonsilver blade" | | 11 | "The leaf-shaped dagger stayed cold" | | 12 | "Silas asked, gesturing to a" | | 13 | "Rory stepped closer to the" | | 14 | "The pool reflected no stars," | | 15 | "Her bright blue eyes widened." | | 16 | "Nyx stepped forward from the" | | 17 | "Their violet eyes glowed softly," | | 18 | "They spoke like a whisper" | | 19 | "The Heartstone pulsed faster, crimson" |
| | ratio | 0.833 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 60 | | matches | (empty) | | ratio | 0 | |
| 0.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 24 | | technicalSentenceCount | 5 | | matches | | 0 | "Rory ducked beneath the twisted arch of standing stones and stepped onto ground that yielded like moss over stone." | | 1 | "Her shoulder-length black hair clung to damp air that smelled of crushed thyme and something sweeter, older." | | 2 | "Silas followed, boots crunching softly on paths that bloomed with wildflowers despite the winter biting at the park beyond." | | 3 | "Ancient oaks formed a cathedral ceiling woven with vines that glowed faintly amber, borrowing color from some distant sky." | | 4 | "Flowers bloomed in impossible spirals—violet, gold, ink-blue—under a moon that was not London's moon." |
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| 95.59% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 17 | | uselessAdditionCount | 1 | | matches | | 0 | "Rory said, her voice low" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 14 | | fancyCount | 1 | | fancyTags | | 0 | "Eva whispered (whisper)" |
| | dialogueSentences | 33 | | tagDensity | 0.424 | | leniency | 0.848 | | rawRatio | 0.071 | | effectiveRatio | 0.061 | |