| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 3 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 5 | | tagDensity | 0.6 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 87.18% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1170 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | 0 | "quickly" | | 1 | "slowly" | | 2 | "slightly" |
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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) | |
| 31.62% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1170 | | totalAiIsms | 16 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | word | "down her spine" | | count | 1 |
| | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | |
| | highlights | | 0 | "sentinels" | | 1 | "pulsed" | | 2 | "rhythmic" | | 3 | "silence" | | 4 | "down her spine" | | 5 | "analyzed" | | 6 | "scanning" | | 7 | "whisper" | | 8 | "chilling" | | 9 | "intensity" | | 10 | "shattered" | | 11 | "chill" | | 12 | "weight" |
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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 | 107 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 1 | | narrationSentences | 107 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 109 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 27 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 1 | | markdownWords | 3 | | totalWords | 1169 | | ratio | 0.003 | | matches | | |
| 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 | 17 | | wordCount | 1154 | | uniqueNames | 8 | | maxNameDensity | 0.69 | | worstName | "Aurora" | | maxWindowNameDensity | 1 | | worstWindowName | "Aurora" | | discoveredNames | | Aurora | 8 | | London | 2 | | Heartstone | 1 | | Pendant | 1 | | Richmond | 1 | | Park | 1 | | November | 2 | | Hel | 1 |
| | persons | | | places | | 0 | "London" | | 1 | "Richmond" | | 2 | "Park" |
| | globalScore | 1 | | windowScore | 1 | |
| 83.33% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 75 | | glossingSentenceCount | 2 | | matches | | 0 | "bluebells that seemed to turn their heads as she passed" | | 1 | "sounded like dry leaves skittering over pa" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.855 | | wordCount | 1169 | | matches | | 0 | "not a sudden shift, but a subtle thickening, like wading into water" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 109 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 25 | | mean | 46.76 | | std | 29.24 | | cv | 0.625 | | sampleLengths | | 0 | 77 | | 1 | 75 | | 2 | 99 | | 3 | 77 | | 4 | 64 | | 5 | 14 | | 6 | 34 | | 7 | 88 | | 8 | 10 | | 9 | 67 | | 10 | 3 | | 11 | 62 | | 12 | 2 | | 13 | 29 | | 14 | 54 | | 15 | 49 | | 16 | 19 | | 17 | 70 | | 18 | 39 | | 19 | 3 | | 20 | 53 | | 21 | 47 | | 22 | 39 | | 23 | 87 | | 24 | 8 |
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| 88.87% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 5 | | totalSentences | 107 | | matches | | 0 | "been removed" | | 1 | "were gone" | | 2 | "were gone" | | 3 | "was replaced" | | 4 | "was broken" |
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| 62.54% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 4 | | totalVerbs | 194 | | matches | | 0 | "was catching" | | 1 | "was reacting" | | 2 | "were spinning" | | 3 | "was watching" |
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| 90.43% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 1 | | semicolonCount | 1 | | flaggedSentences | 2 | | totalSentences | 109 | | ratio | 0.018 | | matches | | 0 | "It was not the peaceful quiet of a park at night; it was a held breath." | | 1 | "She saw movement at the edge of her vision—a tall, slender shape standing just beyond the light of the pendant." |
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| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1157 | | adjectiveStacks | 1 | | stackExamples | | 0 | "small crescent-shaped scar" |
| | adverbCount | 37 | | adverbRatio | 0.03197925669835782 | | lyAdverbCount | 12 | | lyAdverbRatio | 0.010371650821089023 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 109 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 109 | | mean | 10.72 | | std | 6.41 | | cv | 0.597 | | sampleLengths | | 0 | 11 | | 1 | 21 | | 2 | 19 | | 3 | 26 | | 4 | 17 | | 5 | 13 | | 6 | 18 | | 7 | 3 | | 8 | 16 | | 9 | 8 | | 10 | 5 | | 11 | 25 | | 12 | 16 | | 13 | 16 | | 14 | 17 | | 15 | 20 | | 16 | 8 | | 17 | 21 | | 18 | 16 | | 19 | 5 | | 20 | 14 | | 21 | 5 | | 22 | 8 | | 23 | 7 | | 24 | 4 | | 25 | 4 | | 26 | 9 | | 27 | 18 | | 28 | 22 | | 29 | 4 | | 30 | 10 | | 31 | 2 | | 32 | 8 | | 33 | 24 | | 34 | 6 | | 35 | 10 | | 36 | 5 | | 37 | 18 | | 38 | 8 | | 39 | 27 | | 40 | 14 | | 41 | 5 | | 42 | 5 | | 43 | 14 | | 44 | 1 | | 45 | 1 | | 46 | 4 | | 47 | 2 | | 48 | 8 | | 49 | 9 |
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| 42.66% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 8 | | diversityRatio | 0.27522935779816515 | | totalSentences | 109 | | uniqueOpeners | 30 | |
| 99.01% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 101 | | matches | | 0 | "Just the sound of her" | | 1 | "Only the wind, which didn't" | | 2 | "Then, the wind picked up," |
| | ratio | 0.03 | |
| 33.86% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 47 | | totalSentences | 101 | | matches | | 0 | "It was not a sudden" | | 1 | "She paused, her boots sinking" | | 2 | "It pulsed, a rhythmic thrum" | | 3 | "She glanced down." | | 4 | "It was the only light" | | 5 | "She had come for answers." | | 6 | "It was not the peaceful" | | 7 | "They should have been dead," | | 8 | "She blinked, shaking her head." | | 9 | "She needed to stay focused." | | 10 | "She pulled her phone from" | | 11 | "She tapped the side, but" | | 12 | "It had been a childhood" | | 13 | "she called out" | | 14 | "Her voice sounded flat, absorbed" | | 15 | "It moved against the grain" | | 16 | "It was reacting to something." | | 17 | "She walked in a straight" | | 18 | "She stopped and spun around." | | 19 | "Her heart hammered against her" |
| | ratio | 0.465 | |
| 14.46% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 90 | | totalSentences | 101 | | matches | | 0 | "The air changed the moment" | | 1 | "It was not a sudden" | | 2 | "She paused, her boots sinking" | | 3 | "Aurora adjusted the collar of" | | 4 | "The Heartstone Pendant rested against" | | 5 | "It pulsed, a rhythmic thrum" | | 6 | "She glanced down." | | 7 | "The deep crimson gemstone glowed" | | 8 | "It was the only light" | | 9 | "She had come for answers." | | 10 | "The pendant had led her" | | 11 | "It was not the peaceful" | | 12 | "Wildflowers bloomed in the grass" | | 13 | "They should have been dead," | | 14 | "Aurora stared at a cluster" | | 15 | "She blinked, shaking her head." | | 16 | "The strain of the last" | | 17 | "She needed to stay focused." | | 18 | "Panic was a luxury she" | | 19 | "She pulled her phone from" |
| | ratio | 0.891 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 101 | | matches | (empty) | | ratio | 0 | |
| 61.99% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 53 | | technicalSentenceCount | 6 | | matches | | 0 | "It was not a sudden shift, but a subtle thickening, like wading into water that had grown too cold too quickly." | | 1 | "She paused, her boots sinking into soil that felt unnervingly soft, devoid of the usual grit of London earth." | | 2 | "Just the sound of her own breathing and the crunch of leaves that were too vibrant, too green for November." | | 3 | "It had no face, only a smooth surface where features should be, and it was watching her with an intensity that felt physical." | | 4 | "It was voices, hundreds of them, whispering in a language that hurt her teeth." | | 5 | "She dropped to her knees, rolling to the side as the air where she had been standing shattered." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 3 | | uselessAdditionCount | 1 | | matches | | 0 | "she said, her voice stronger than she felt" |
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| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 2 | | fancyCount | 1 | | fancyTags | | 0 | "she whispered (whisper)" |
| | dialogueSentences | 5 | | tagDensity | 0.4 | | leniency | 0.8 | | rawRatio | 0.5 | | effectiveRatio | 0.4 | |