| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | |
| 86.49% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1110 | | totalAiIsmAdverbs | 3 | | 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) | |
| 5.41% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1110 | | totalAiIsms | 21 | | found | | | highlights | | 0 | "maw" | | 1 | "silence" | | 2 | "loomed" | | 3 | "gloom" | | 4 | "beacon" | | 5 | "oppressive" | | 6 | "pulsed" | | 7 | "resonated" | | 8 | "scanned" | | 9 | "flicker" | | 10 | "weight" | | 11 | "stomach" | | 12 | "perfect" | | 13 | "searing" |
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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 | 1 | | narrationSentences | 112 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 2 | | narrationSentences | 112 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 112 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 26 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 4 | | markdownWords | 45 | | totalWords | 1106 | | ratio | 0.041 | | matches | | 0 | "They are not like us, Eva had said, her voice a memory. They don't see the world the same way. Their rules are not our rules." | | 1 | "Little bird. Little Laila. You have brought us a key." | | 2 | "Give it to us," | | 3 | "Let us open the door." |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 1 | | unquotedAttributions | 1 | | matches | | 0 | "Cool-headed, she told herself." |
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| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 15 | | wordCount | 1106 | | uniqueNames | 9 | | maxNameDensity | 0.36 | | worstName | "Rory" | | maxWindowNameDensity | 1 | | worstWindowName | "Laila" | | discoveredNames | | Richmond | 1 | | Park | 1 | | London | 1 | | Carter | 1 | | Eva | 2 | | Grove | 2 | | Isolde | 1 | | Laila | 2 | | Rory | 4 |
| | persons | | 0 | "Carter" | | 1 | "Eva" | | 2 | "Isolde" | | 3 | "Laila" | | 4 | "Rory" |
| | places | | 0 | "Richmond" | | 1 | "Park" | | 2 | "London" |
| | globalScore | 1 | | windowScore | 1 | |
| 55.06% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 79 | | glossingSentenceCount | 3 | | matches | | 0 | "felt like a pressure against her eardru" | | 1 | "felt like a mouth waiting to close" | | 2 | "silhouette that seemed to absorb the faint light around it" |
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| 19.17% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 2 | | per1kWords | 1.808 | | wordCount | 1106 | | matches | | 0 | "not teeth, but a row of bristle-like filaments, twitching" | | 1 | "not at her face, but at her chest" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 112 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 31 | | mean | 35.68 | | std | 25.27 | | cv | 0.708 | | sampleLengths | | 0 | 74 | | 1 | 56 | | 2 | 38 | | 3 | 99 | | 4 | 22 | | 5 | 58 | | 6 | 5 | | 7 | 61 | | 8 | 24 | | 9 | 5 | | 10 | 46 | | 11 | 49 | | 12 | 2 | | 13 | 61 | | 14 | 2 | | 15 | 50 | | 16 | 2 | | 17 | 48 | | 18 | 62 | | 19 | 13 | | 20 | 53 | | 21 | 26 | | 22 | 7 | | 23 | 55 | | 24 | 69 | | 25 | 22 | | 26 | 10 | | 27 | 24 | | 28 | 35 | | 29 | 10 | | 30 | 18 |
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| 95.86% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 112 | | matches | | 0 | "was gone" | | 1 | "being drawn" | | 2 | "was, caught" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 159 | | matches | | 0 | "were drinking" | | 1 | "was screaming" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 112 | | ratio | 0 | | matches | (empty) | |
| 97.16% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1110 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 48 | | adverbRatio | 0.043243243243243246 | | lyAdverbCount | 12 | | lyAdverbRatio | 0.010810810810810811 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 112 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 112 | | mean | 9.88 | | std | 6.07 | | cv | 0.615 | | sampleLengths | | 0 | 13 | | 1 | 11 | | 2 | 19 | | 3 | 7 | | 4 | 24 | | 5 | 10 | | 6 | 14 | | 7 | 6 | | 8 | 14 | | 9 | 12 | | 10 | 4 | | 11 | 12 | | 12 | 9 | | 13 | 13 | | 14 | 17 | | 15 | 14 | | 16 | 8 | | 17 | 19 | | 18 | 17 | | 19 | 24 | | 20 | 12 | | 21 | 6 | | 22 | 4 | | 23 | 17 | | 24 | 1 | | 25 | 7 | | 26 | 8 | | 27 | 17 | | 28 | 8 | | 29 | 5 | | 30 | 13 | | 31 | 14 | | 32 | 14 | | 33 | 11 | | 34 | 1 | | 35 | 8 | | 36 | 9 | | 37 | 4 | | 38 | 4 | | 39 | 3 | | 40 | 4 | | 41 | 5 | | 42 | 15 | | 43 | 18 | | 44 | 13 | | 45 | 11 | | 46 | 3 | | 47 | 17 | | 48 | 11 | | 49 | 7 |
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| 38.10% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 14 | | diversityRatio | 0.30357142857142855 | | totalSentences | 112 | | uniqueOpeners | 34 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 4 | | totalSentences | 102 | | matches | | 0 | "Even the animals were quiet" | | 1 | "Just the flowers and the" | | 2 | "Just the dark, impassive faces" | | 3 | "Maybe it wasn't as late" |
| | ratio | 0.039 | |
| 47.45% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 44 | | totalSentences | 102 | | matches | | 0 | "She wasn't here for a" | | 1 | "Her phone’s flashlight cut a" | | 2 | "She knew the way." | | 3 | "She’d only been here once," | | 4 | "They didn't look carved so" | | 5 | "It wasn't just a guide" | | 6 | "It was a beacon." | | 7 | "She pulled the chain from" | | 8 | "It cast a red shimmer" | | 9 | "It wasn't a snap of" | | 10 | "It was a single, clear" | | 11 | "Her heart hammered a little" | | 12 | "It’s just the wind." | | 13 | "They make strange noises." | | 14 | "She took a slow breath," | | 15 | "It was too sweet, thick" | | 16 | "She scanned the clearing again," | | 17 | "It was a shadow that" | | 18 | "She froze, the beam of" | | 19 | "Her knuckles were white around" |
| | ratio | 0.431 | |
| 48.24% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 84 | | totalSentences | 102 | | matches | | 0 | "The gate to Richmond Park" | | 1 | "Aurora Carter slipped through it," | | 2 | "The city’s hum, a constant" | | 3 | "She wasn't here for a" | | 4 | "The pendant resting against her" | | 5 | "Her phone’s flashlight cut a" | | 6 | "The beam caught the reflective" | | 7 | "The air grew still, the" | | 8 | "A silence so complete it" | | 9 | "She knew the way." | | 10 | "She’d only been here once," | | 11 | "The Grove had felt magical" | | 12 | "The ancient oak standing stones" | | 13 | "They didn't look carved so" | | 14 | "The air changed, growing thick" | | 15 | "The wildflowers Isolde had spoken" | | 16 | "Petals the colour of bone" | | 17 | "The pendant grew warmer, a" | | 18 | "It wasn't just a guide" | | 19 | "It was a beacon." |
| | ratio | 0.824 | |
| 49.02% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 102 | | matches | | 0 | "Now, in the moonless dark," |
| | ratio | 0.01 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 54 | | technicalSentenceCount | 3 | | matches | | 0 | "It was a shadow that moved against other shadows, detaching and then melting back into the darkness." | | 1 | "A thin, perfect slit that opened too wide, revealing not teeth, but a row of bristle-like filaments, twitching." | | 2 | "The creature’s head tilted, a gesture of curiosity that was infinitely more terrifying than any snarl." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 0 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |