| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 14 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 28 | | tagDensity | 0.5 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 91.80% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1220 | | 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) | |
| 50.82% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1220 | | totalAiIsms | 12 | | found | | | highlights | | 0 | "charged" | | 1 | "flickered" | | 2 | "loomed" | | 3 | "pulsed" | | 4 | "silence" | | 5 | "whisper" | | 6 | "perfect" | | 7 | "lurching" | | 8 | "echoed" |
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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 | 127 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 127 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 141 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 34 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 5 | | markdownWords | 13 | | totalWords | 1210 | | ratio | 0.011 | | matches | | 0 | "Maybe the \"delivery\" is a trap," | | 1 | "every" | | 2 | "Cold enough for fog." | | 3 | "portal." | | 4 | "Drive." |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 13 | | unquotedAttributions | 0 | | matches | (empty) | |
| 50.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 33 | | wordCount | 1069 | | uniqueNames | 12 | | maxNameDensity | 1.31 | | worstName | "Aurora" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Aurora" | | discoveredNames | | Richmond | 1 | | Park | 1 | | Carter | 1 | | Yu-Fei | 1 | | Heartstone | 2 | | Pendant | 1 | | Evan | 2 | | Silas | 5 | | Googled | 1 | | Aurora | 14 | | Fae | 1 | | Grove | 3 |
| | persons | | 0 | "Carter" | | 1 | "Yu-Fei" | | 2 | "Pendant" | | 3 | "Evan" | | 4 | "Silas" | | 5 | "Aurora" |
| | places | | 0 | "Richmond" | | 1 | "Park" | | 2 | "Fae" | | 3 | "Grove" |
| | globalScore | 0.845 | | windowScore | 0.5 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 83 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1210 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 141 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 40 | | mean | 30.25 | | std | 25.05 | | cv | 0.828 | | sampleLengths | | 0 | 95 | | 1 | 91 | | 2 | 94 | | 3 | 8 | | 4 | 64 | | 5 | 56 | | 6 | 6 | | 7 | 23 | | 8 | 39 | | 9 | 25 | | 10 | 34 | | 11 | 41 | | 12 | 37 | | 13 | 2 | | 14 | 65 | | 15 | 27 | | 16 | 44 | | 17 | 13 | | 18 | 42 | | 19 | 17 | | 20 | 33 | | 21 | 31 | | 22 | 6 | | 23 | 14 | | 24 | 37 | | 25 | 28 | | 26 | 8 | | 27 | 18 | | 28 | 3 | | 29 | 6 | | 30 | 42 | | 31 | 5 | | 32 | 38 | | 33 | 4 | | 34 | 2 | | 35 | 3 | | 36 | 35 | | 37 | 9 | | 38 | 51 | | 39 | 14 |
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| 85.92% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 7 | | totalSentences | 127 | | matches | | 0 | "been crossed" | | 1 | "been carved" | | 2 | "was gone" | | 3 | "was gone" | | 4 | "was gone" | | 5 | "were made" | | 6 | "been chewed" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 188 | | matches | | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 10 | | semicolonCount | 0 | | flaggedSentences | 8 | | totalSentences | 141 | | ratio | 0.057 | | matches | | 0 | "The air smelled of wet earth and something sharper—like the tang of burnt sugar." | | 1 | "That wasn’t his name on the envelope—never would be—but she’d take whatever help came her way." | | 2 | "Her phone flickered in her pocket—4:43 a.m." | | 3 | "The runic symbols were on *every* stone, now—roots curling up her ankles like serpents." | | 4 | "\"Does it matter?\" A woman stepped into the light—tall and draped in a moss-green cloak." | | 5 | "Aurora’s phone flickered—6:17 a.m." | | 6 | "A shape loomed in it—a horse with too many legs, its eyes burning the same crimson as the Heartstone." | | 7 | "Its hands—were they hands?—were pale and webbed between the fingers." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1083 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 33 | | adverbRatio | 0.030470914127423823 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.0046168051708217915 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 141 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 141 | | mean | 8.58 | | std | 5.28 | | cv | 0.615 | | sampleLengths | | 0 | 17 | | 1 | 16 | | 2 | 14 | | 3 | 31 | | 4 | 17 | | 5 | 11 | | 6 | 16 | | 7 | 13 | | 8 | 10 | | 9 | 8 | | 10 | 17 | | 11 | 16 | | 12 | 4 | | 13 | 19 | | 14 | 8 | | 15 | 17 | | 16 | 12 | | 17 | 16 | | 18 | 7 | | 19 | 6 | | 20 | 5 | | 21 | 8 | | 22 | 2 | | 23 | 5 | | 24 | 4 | | 25 | 13 | | 26 | 14 | | 27 | 5 | | 28 | 14 | | 29 | 7 | | 30 | 7 | | 31 | 8 | | 32 | 8 | | 33 | 4 | | 34 | 11 | | 35 | 10 | | 36 | 8 | | 37 | 6 | | 38 | 6 | | 39 | 3 | | 40 | 11 | | 41 | 3 | | 42 | 15 | | 43 | 11 | | 44 | 13 | | 45 | 2 | | 46 | 20 | | 47 | 3 | | 48 | 18 | | 49 | 16 |
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| 41.49% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 12 | | diversityRatio | 0.2907801418439716 | | totalSentences | 141 | | uniqueOpeners | 41 | |
| 29.24% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 114 | | matches | | 0 | "*Maybe the is a trap,*" |
| | ratio | 0.009 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 32 | | totalSentences | 114 | | matches | | 0 | "She’d followed the GPS coordinates" | | 1 | "She tugged the strap of" | | 2 | "It wasn’t there on any" | | 3 | "Her phone flickered in her" | | 4 | "She’d crossed the oaks at" | | 5 | "Her breath fogged the air." | | 6 | "She stepped over it and" | | 7 | "Her boots sank into the" | | 8 | "She pulled out the pendant," | | 9 | "Her hair was black as" | | 10 | "It didn’t whisper." | | 11 | "It just burned." | | 12 | "She backed away until she" | | 13 | "She yanked free the chain," | | 14 | "She wrenched free, stumbled sideways," | | 15 | "Her reflection in a dewdrop:" | | 16 | "She wiped the leaf, looked" | | 17 | "She hadn’t seen the sunrise." | | 18 | "She skidded to a halt." | | 19 | "His bar was five miles" |
| | ratio | 0.281 | |
| 21.40% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 100 | | totalSentences | 114 | | matches | | 0 | "The moon hung low over" | | 1 | "Aurora Carter stepped between two" | | 2 | "The air smelled of wet" | | 3 | "She’d followed the GPS coordinates" | | 4 | "The courier company name had" | | 5 | "She tugged the strap of" | | 6 | "The silver chain of the" | | 7 | "A minute ago, the stone" | | 8 | "That wasn’t his name on" | | 9 | "The clearing opened ahead." | | 10 | "A path of moss snaked" | | 11 | "It wasn’t there on any" | | 12 | "Her phone flickered in her" | | 13 | "She’d crossed the oaks at" | | 14 | "That math didn’t add up." | | 15 | "a voice said" | | 16 | "The path was gone." | | 17 | "The oaks now loomed directly" | | 18 | "The runic symbols were on" | | 19 | "Her breath fogged the air." |
| | ratio | 0.877 | |
| 87.72% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 114 | | matches | | 0 | "Now it was hot enough" | | 1 | "Now it wanted the rest." |
| | ratio | 0.018 | |
| 91.84% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 42 | | technicalSentenceCount | 3 | | matches | | 0 | "The moon hung low over Richmond Park, a swollen silver disc that cast more shadow than light." | | 1 | "Her boots sank into the moss as if it were quicksand." | | 2 | "The woman’s face was dissolving, her features melting into bark, hair into ivy." |
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| 89.29% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 14 | | uselessAdditionCount | 1 | | matches | | 0 | "he said, but his knuckles whitened on the steering wheel" |
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| 78.57% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 8 | | fancyCount | 2 | | fancyTags | | 0 | "Silas muttered (mutter)" | | 1 | "it hissed (hiss)" |
| | dialogueSentences | 28 | | tagDensity | 0.286 | | leniency | 0.571 | | rawRatio | 0.25 | | effectiveRatio | 0.143 | |