| 66.67% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 15 | | adverbTagCount | 2 | | adverbTags | | 0 | "Evan glanced around [around]" | | 1 | "Rory said softly [softly]" |
| | dialogueSentences | 27 | | tagDensity | 0.556 | | leniency | 1 | | rawRatio | 0.133 | | effectiveRatio | 0.133 | |
| 84.03% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 626 | | 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) | |
| 52.08% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 626 | | totalAiIsms | 6 | | found | | | highlights | | 0 | "whisper" | | 1 | "could feel" | | 2 | "warmth" | | 3 | "echo" | | 4 | "silence" |
| |
| 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 | 52 | | matches | (empty) | |
| 87.91% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 1 | | narrationSentences | 52 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 64 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 32 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 1 | | markdownWords | 1 | | totalWords | 624 | | ratio | 0.002 | | matches | | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 6 | | unquotedAttributions | 0 | | matches | (empty) | |
| 55.06% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 30 | | wordCount | 474 | | uniqueNames | 10 | | maxNameDensity | 1.9 | | worstName | "Rory" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Evan" | | discoveredNames | | Raven | 2 | | Nest | 1 | | Evan | 8 | | Rory | 9 | | Silas | 5 | | Could | 1 | | Despite | 1 | | Reasons | 1 | | Reassuring | 1 | | End | 1 |
| | persons | | 0 | "Evan" | | 1 | "Rory" | | 2 | "Silas" | | 3 | "Could" |
| | places | | | globalScore | 0.551 | | windowScore | 0.833 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 33 | | 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 | 624 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 64 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 26 | | mean | 24 | | std | 12.61 | | cv | 0.525 | | sampleLengths | | 0 | 49 | | 1 | 30 | | 2 | 2 | | 3 | 41 | | 4 | 28 | | 5 | 30 | | 6 | 38 | | 7 | 8 | | 8 | 10 | | 9 | 33 | | 10 | 28 | | 11 | 21 | | 12 | 21 | | 13 | 35 | | 14 | 18 | | 15 | 14 | | 16 | 35 | | 17 | 22 | | 18 | 22 | | 19 | 7 | | 20 | 39 | | 21 | 35 | | 22 | 1 | | 23 | 11 | | 24 | 32 | | 25 | 14 |
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| 91.77% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 52 | | matches | | 0 | "being brushed" | | 1 | "was crooked" |
| |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 86 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 64 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 184 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 3 | | adverbRatio | 0.016304347826086956 | | lyAdverbCount | 1 | | lyAdverbRatio | 0.005434782608695652 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 64 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 64 | | mean | 9.75 | | std | 6.96 | | cv | 0.714 | | sampleLengths | | 0 | 23 | | 1 | 9 | | 2 | 2 | | 3 | 15 | | 4 | 15 | | 5 | 15 | | 6 | 2 | | 7 | 21 | | 8 | 1 | | 9 | 5 | | 10 | 14 | | 11 | 23 | | 12 | 5 | | 13 | 7 | | 14 | 7 | | 15 | 16 | | 16 | 18 | | 17 | 20 | | 18 | 8 | | 19 | 10 | | 20 | 12 | | 21 | 15 | | 22 | 6 | | 23 | 23 | | 24 | 5 | | 25 | 15 | | 26 | 1 | | 27 | 5 | | 28 | 8 | | 29 | 9 | | 30 | 4 | | 31 | 32 | | 32 | 1 | | 33 | 1 | | 34 | 1 | | 35 | 14 | | 36 | 4 | | 37 | 5 | | 38 | 7 | | 39 | 2 | | 40 | 6 | | 41 | 7 | | 42 | 15 | | 43 | 7 | | 44 | 13 | | 45 | 7 | | 46 | 2 | | 47 | 15 | | 48 | 7 | | 49 | 7 |
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| 77.08% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 4 | | diversityRatio | 0.5 | | totalSentences | 64 | | uniqueOpeners | 32 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 41 | | matches | (empty) | | ratio | 0 | |
| 63.90% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 16 | | totalSentences | 41 | | matches | | 0 | "His brow creased, a shadow" | | 1 | "Her voice was quiet, like" | | 2 | "His eyes were too bright," | | 3 | "He paused, wetting his lips," | | 4 | "He had been wearing that" | | 5 | "His eyes were watchful now," | | 6 | "Her smile was crooked, cutting." | | 7 | "She paused, sipped" | | 8 | "He reddened, dropped his head" | | 9 | "She finished it in a" | | 10 | "He smiled, and it was" | | 11 | "He leaned in close, his" | | 12 | "She swallowed, not turning away." | | 13 | "he whispered, taking his coat" | | 14 | "His abrupt silence pulled her" | | 15 | "she said, shrugging a goodbye" |
| | ratio | 0.39 | |
| 45.37% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 34 | | totalSentences | 41 | | matches | | 0 | "Rory slid onto the last" | | 1 | "His brow creased, a shadow" | | 2 | "The door behind her swung" | | 3 | "Rory half-turned, still standing out" | | 4 | "Her voice was quiet, like" | | 5 | "There, not there, now here." | | 6 | "His eyes were too bright," | | 7 | "He paused, wetting his lips," | | 8 | "Rory could still remember the" | | 9 | "He had been wearing that" | | 10 | "Silas set her drinks down" | | 11 | "Rory picked up the whiskey," | | 12 | "Evan glanced around, absorbed the" | | 13 | "A seven year long explanation." | | 14 | "Evan lifted a shoulder in" | | 15 | "Rory felt her arm being" | | 16 | "His eyes were watchful now," | | 17 | "Her smile was crooked, cutting." | | 18 | "She paused, sipped" | | 19 | "Evan's laugh was hollow, an" |
| | ratio | 0.829 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 41 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 14 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 15 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 4 | | fancyCount | 1 | | fancyTags | | 0 | "he whispered (whisper)" |
| | dialogueSentences | 27 | | tagDensity | 0.148 | | leniency | 0.296 | | rawRatio | 0.25 | | effectiveRatio | 0.074 | |