| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 19 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 38 | | tagDensity | 0.5 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 92.30% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1299 | | totalAiIsmAdverbs | 2 | | found | | | highlights | | |
| 100.00% | AI-ism character names | Target: 0 AI-default names (16 tracked, −20% each) | | codexExemptions | | | found | (empty) | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 46.11% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1299 | | totalAiIsms | 14 | | found | | | highlights | | 0 | "weight" | | 1 | "silence" | | 2 | "scanning" | | 3 | "gloom" | | 4 | "whisper" | | 5 | "traced" | | 6 | "flicker" | | 7 | "navigate" |
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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 | 107 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 107 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 126 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 35 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 1 | | markdownWords | 4 | | totalWords | 1299 | | ratio | 0.003 | | matches | | 0 | "Aurora Carter. 25. Drunk." |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 24 | | unquotedAttributions | 0 | | matches | (empty) | |
| 66.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 32 | | wordCount | 975 | | uniqueNames | 8 | | maxNameDensity | 1.23 | | worstName | "Silas" | | maxWindowNameDensity | 3 | | worstWindowName | "Silas" | | discoveredNames | | London | 3 | | Thames | 1 | | Silas | 12 | | Blackwood | 1 | | Aurora | 9 | | Carter | 2 | | Wales | 1 | | Rory | 3 |
| | persons | | 0 | "Silas" | | 1 | "Blackwood" | | 2 | "Aurora" | | 3 | "Carter" | | 4 | "Rory" |
| | places | | 0 | "London" | | 1 | "Thames" | | 2 | "Wales" |
| | globalScore | 0.885 | | windowScore | 0.667 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 61 | | 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 | 1299 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 126 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 33 | | mean | 39.36 | | std | 30 | | cv | 0.762 | | sampleLengths | | 0 | 101 | | 1 | 102 | | 2 | 95 | | 3 | 53 | | 4 | 11 | | 5 | 16 | | 6 | 80 | | 7 | 51 | | 8 | 56 | | 9 | 12 | | 10 | 13 | | 11 | 88 | | 12 | 22 | | 13 | 48 | | 14 | 9 | | 15 | 50 | | 16 | 24 | | 17 | 11 | | 18 | 31 | | 19 | 29 | | 20 | 28 | | 21 | 32 | | 22 | 13 | | 23 | 27 | | 24 | 69 | | 25 | 6 | | 26 | 24 | | 27 | 1 | | 28 | 89 | | 29 | 49 | | 30 | 12 | | 31 | 11 | | 32 | 36 |
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| 95.43% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 107 | | matches | | 0 | "were lined" | | 1 | "was supposed" | | 2 | "were gone" |
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| 14.81% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 5 | | totalVerbs | 180 | | matches | | 0 | "wasn't looking" | | 1 | "was looking" | | 2 | "wasn't offering" | | 3 | "was offering" | | 4 | "were standing" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 1 | | flaggedSentences | 1 | | totalSentences | 126 | | ratio | 0.008 | | matches | | 0 | "The bell above the entrance meant something different than it did ten years ago; now, it dipped with the ache of a broken promise." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 980 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 23 | | adverbRatio | 0.02346938775510204 | | lyAdverbCount | 3 | | lyAdverbRatio | 0.003061224489795918 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 126 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 126 | | mean | 10.31 | | std | 7.14 | | cv | 0.693 | | sampleLengths | | 0 | 26 | | 1 | 19 | | 2 | 27 | | 3 | 5 | | 4 | 24 | | 5 | 14 | | 6 | 33 | | 7 | 12 | | 8 | 17 | | 9 | 20 | | 10 | 6 | | 11 | 17 | | 12 | 13 | | 13 | 18 | | 14 | 19 | | 15 | 4 | | 16 | 24 | | 17 | 4 | | 18 | 4 | | 19 | 15 | | 20 | 10 | | 21 | 6 | | 22 | 14 | | 23 | 3 | | 24 | 8 | | 25 | 4 | | 26 | 6 | | 27 | 6 | | 28 | 7 | | 29 | 6 | | 30 | 24 | | 31 | 23 | | 32 | 20 | | 33 | 4 | | 34 | 4 | | 35 | 34 | | 36 | 9 | | 37 | 4 | | 38 | 15 | | 39 | 14 | | 40 | 23 | | 41 | 4 | | 42 | 8 | | 43 | 5 | | 44 | 8 | | 45 | 5 | | 46 | 1 | | 47 | 4 | | 48 | 3 | | 49 | 15 |
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| 31.60% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 23 | | diversityRatio | 0.248 | | totalSentences | 125 | | uniqueOpeners | 31 | |
| 39.22% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 85 | | matches | | 0 | "Bright blue eyes scanning the" |
| | ratio | 0.012 | |
| 3.53% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 46 | | totalSentences | 85 | | matches | | 0 | "She pushed through the door." | | 1 | "She moved toward the counter," | | 2 | "She kept her head down," | | 3 | "She had changed the way" | | 4 | "It was there, stepping from" | | 5 | "He looked out of place" | | 6 | "He was fifty-eight, or older," | | 7 | "She knew his body." | | 8 | "She knew the rhythm of" | | 9 | "His hazel eyes widened, the" | | 10 | "He wasn't looking at the" | | 11 | "He was looking at Aurora" | | 12 | "His voice had aged easier" | | 13 | "She didn't move" | | 14 | "She held her bag too" | | 15 | "He stepped around the bar," | | 16 | "He stopped close, far enough" | | 17 | "She shifted her weight." | | 18 | "His hand slid out of" | | 19 | "It caught the flicker of" |
| | ratio | 0.541 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 81 | | totalSentences | 85 | | matches | | 0 | "The green neon sign above" | | 1 | "Aurora paused on the sidewalk," | | 2 | "The weight of it felt" | | 3 | "She pushed through the door." | | 4 | "The bell above the entrance" | | 5 | "Silence filled the space, the" | | 6 | "The walls were lined with" | | 7 | "She moved toward the counter," | | 8 | "She kept her head down," | | 9 | "She had changed the way" | | 10 | "It was there, stepping from" | | 11 | "He looked out of place" | | 12 | "He was fifty-eight, or older," | | 13 | "Hair like burnt sugar, grey-streaked" | | 14 | "She knew his body." | | 15 | "She knew the rhythm of" | | 16 | "Silas Blackwood turned slowly." | | 17 | "The movement was deliberate." | | 18 | "His hazel eyes widened, the" | | 19 | "He wasn't looking at the" |
| | ratio | 0.953 | |
| 58.82% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 85 | | matches | | | ratio | 0.012 | |
| 87.91% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 39 | | technicalSentenceCount | 3 | | matches | | 0 | "The green neon sign above the door buzzed with a low, insectoid hum, a sound that had been part of the London nightscape for twenty years." | | 1 | "The weight of it felt heavy, but heavier was the cold knot in her chest that hadn't loosened in a millennium of cold drinks and warm drinks." | | 2 | "He stepped around the bar, his left leg dragging slightly behind, the limp only noticeable to someone who knew the engineering of his hips." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 19 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 18 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 38 | | tagDensity | 0.474 | | leniency | 0.947 | | rawRatio | 0 | | effectiveRatio | 0 | |