| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 11 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 32 | | tagDensity | 0.344 | | leniency | 0.688 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 769 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 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) | |
| 80.49% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 769 | | totalAiIsms | 3 | | found | | | highlights | | |
| 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 | 41 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 41 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 62 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 35 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 769 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 8 | | unquotedAttributions | 0 | | matches | (empty) | |
| 90.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 12 | | wordCount | 500 | | uniqueNames | 3 | | maxNameDensity | 1.2 | | worstName | "Ashdown" | | maxWindowNameDensity | 2 | | worstWindowName | "Quinn" | | discoveredNames | | | persons | | | places | (empty) | | globalScore | 0.9 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 29 | | 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 | 769 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 62 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 34 | | mean | 22.62 | | std | 20.62 | | cv | 0.912 | | sampleLengths | | 0 | 22 | | 1 | 16 | | 2 | 9 | | 3 | 72 | | 4 | 28 | | 5 | 2 | | 6 | 45 | | 7 | 14 | | 8 | 5 | | 9 | 43 | | 10 | 7 | | 11 | 12 | | 12 | 31 | | 13 | 11 | | 14 | 43 | | 15 | 51 | | 16 | 6 | | 17 | 11 | | 18 | 6 | | 19 | 12 | | 20 | 61 | | 21 | 6 | | 22 | 5 | | 23 | 30 | | 24 | 4 | | 25 | 2 | | 26 | 70 | | 27 | 6 | | 28 | 9 | | 29 | 43 | | 30 | 4 | | 31 | 49 | | 32 | 4 | | 33 | 30 |
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| 88.15% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 41 | | matches | | 0 | "been hauled" | | 1 | "was yellowed" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 77 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 62 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 500 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 12 | | adverbRatio | 0.024 | | lyAdverbCount | 3 | | lyAdverbRatio | 0.006 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 62 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 62 | | mean | 12.4 | | std | 8.39 | | cv | 0.677 | | sampleLengths | | 0 | 22 | | 1 | 11 | | 2 | 5 | | 3 | 9 | | 4 | 10 | | 5 | 23 | | 6 | 13 | | 7 | 26 | | 8 | 25 | | 9 | 3 | | 10 | 2 | | 11 | 24 | | 12 | 21 | | 13 | 6 | | 14 | 8 | | 15 | 5 | | 16 | 7 | | 17 | 12 | | 18 | 9 | | 19 | 15 | | 20 | 7 | | 21 | 12 | | 22 | 17 | | 23 | 14 | | 24 | 5 | | 25 | 6 | | 26 | 15 | | 27 | 22 | | 28 | 6 | | 29 | 7 | | 30 | 28 | | 31 | 16 | | 32 | 6 | | 33 | 11 | | 34 | 6 | | 35 | 9 | | 36 | 3 | | 37 | 28 | | 38 | 20 | | 39 | 13 | | 40 | 6 | | 41 | 5 | | 42 | 30 | | 43 | 4 | | 44 | 2 | | 45 | 3 | | 46 | 10 | | 47 | 35 | | 48 | 22 | | 49 | 6 |
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| 98.39% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 1 | | diversityRatio | 0.6129032258064516 | | totalSentences | 62 | | uniqueOpeners | 38 | |
| 95.24% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 35 | | matches | | 0 | "Then they stopped dead at" |
| | ratio | 0.029 | |
| 82.86% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 12 | | totalSentences | 35 | | matches | | 0 | "He picked his way down," | | 1 | "She ignored him and studied" | | 2 | "His skin had gone the" | | 3 | "She pointed with a pen" | | 4 | "She followed the prints with" | | 5 | "He said nothing." | | 6 | "It was yellowed and carved," | | 7 | "Her stomach tightened, a reflex" | | 8 | "She didn't answer." | | 9 | "She picked up the compass" | | 10 | "She stood, knees popping, and" | | 11 | "She set her palm flat" |
| | ratio | 0.343 | |
| 31.43% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 30 | | totalSentences | 35 | | matches | | 0 | "Quinn said, before the constable's" | | 1 | "The young officer froze with" | | 2 | "Quinn crouched on the cracked" | | 3 | "The air tasted of wet" | | 4 | "Camden's market noise came through" | | 5 | "Ashdown appeared at the top" | | 6 | "He picked his way down," | | 7 | "She ignored him and studied" | | 8 | "His skin had gone the" | | 9 | "Dark stains spread across the" | | 10 | "She pointed with a pen" | | 11 | "Ashdown sighed through his nose." | | 12 | "Quinn tilted her head at" | | 13 | "She followed the prints with" | | 14 | "Each one was sharp at" | | 15 | "Ashdown had the grace to" | | 16 | "He said nothing." | | 17 | "Quinn reached into her coat" | | 18 | "It was yellowed and carved," | | 19 | "Her stomach tightened, a reflex" |
| | ratio | 0.857 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 35 | | matches | (empty) | | ratio | 0 | |
| 35.71% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 20 | | technicalSentenceCount | 3 | | matches | | 0 | "Hanging lamps swung from their cables, throwing the shadows around in loose circles." | | 1 | "Two parallel grooves ran from the mouth of the tunnel to the body, deep, as though something heavy had been hauled along." | | 2 | "Behind them, the drag marks on the tiles began to shift, the grime sliding inward as though something beneath the platform had taken a breath." |
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| 79.55% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 11 | | uselessAdditionCount | 1 | | matches | | 0 | "She stood, knees popping, and walked toward the wall" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 6 | | fancyCount | 1 | | fancyTags | | 0 | "Quinn repeated (repeat)" |
| | dialogueSentences | 32 | | tagDensity | 0.188 | | leniency | 0.375 | | rawRatio | 0.167 | | effectiveRatio | 0.063 | |