| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 29 | | adverbTagCount | 3 | | adverbTags | | 0 | "Lucien said finally [finally]" | | 1 | "Lucien seemed genuinely [genuinely]" | | 2 | "he said quietly [quietly]" |
| | dialogueSentences | 76 | | tagDensity | 0.382 | | leniency | 0.763 | | rawRatio | 0.103 | | effectiveRatio | 0.079 | |
| 77.31% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1102 | | totalAiIsmAdverbs | 5 | | found | | | highlights | | 0 | "completely" | | 1 | "precisely" | | 2 | "carefully" | | 3 | "very" | | 4 | "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) | |
| 36.48% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1102 | | totalAiIsms | 14 | | found | | | highlights | | 0 | "resolve" | | 1 | "encounter" | | 2 | "stark" | | 3 | "chaotic" | | 4 | "unreadable" | | 5 | "reminder" | | 6 | "intensity" | | 7 | "otherworldly" | | 8 | "familiar" | | 9 | "silence" | | 10 | "unspoken" | | 11 | "tension" | | 12 | "whisper" | | 13 | "racing" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "sent a shiver through" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 62 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 62 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 107 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 30 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1097 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 10 | | unquotedAttributions | 0 | | matches | (empty) | |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 38 | | wordCount | 544 | | uniqueNames | 4 | | maxNameDensity | 3.31 | | worstName | "Rory" | | maxWindowNameDensity | 5.5 | | worstWindowName | "Lucien" | | discoveredNames | | Rory | 18 | | Lucien | 18 | | Silence | 1 | | Eva | 1 |
| | persons | | 0 | "Rory" | | 1 | "Lucien" | | 2 | "Silence" | | 3 | "Eva" |
| | places | (empty) | | globalScore | 0 | | windowScore | 0 | |
| 95.65% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 46 | | glossingSentenceCount | 1 | | matches | | 0 | "seemed genuinely confused by the question" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1097 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 107 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 56 | | mean | 19.59 | | std | 11.05 | | cv | 0.564 | | sampleLengths | | 0 | 25 | | 1 | 1 | | 2 | 15 | | 3 | 23 | | 4 | 32 | | 5 | 10 | | 6 | 42 | | 7 | 20 | | 8 | 40 | | 9 | 6 | | 10 | 17 | | 11 | 25 | | 12 | 18 | | 13 | 17 | | 14 | 28 | | 15 | 22 | | 16 | 16 | | 17 | 17 | | 18 | 7 | | 19 | 4 | | 20 | 39 | | 21 | 4 | | 22 | 29 | | 23 | 13 | | 24 | 6 | | 25 | 31 | | 26 | 26 | | 27 | 27 | | 28 | 16 | | 29 | 11 | | 30 | 15 | | 31 | 40 | | 32 | 9 | | 33 | 31 | | 34 | 38 | | 35 | 3 | | 36 | 23 | | 37 | 29 | | 38 | 26 | | 39 | 11 | | 40 | 27 | | 41 | 14 | | 42 | 9 | | 43 | 33 | | 44 | 16 | | 45 | 24 | | 46 | 39 | | 47 | 13 | | 48 | 25 | | 49 | 23 |
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| 99.60% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 62 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 108 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 107 | | ratio | 0 | | matches | (empty) | |
| 67.06% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 547 | | adjectiveStacks | 1 | | stackExamples | | 0 | "small, leather-bound book." |
| | adverbCount | 32 | | adverbRatio | 0.05850091407678245 | | lyAdverbCount | 18 | | lyAdverbRatio | 0.03290676416819013 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 107 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 107 | | mean | 10.25 | | std | 6.13 | | cv | 0.597 | | sampleLengths | | 0 | 7 | | 1 | 6 | | 2 | 12 | | 3 | 1 | | 4 | 14 | | 5 | 1 | | 6 | 18 | | 7 | 5 | | 8 | 26 | | 9 | 6 | | 10 | 6 | | 11 | 4 | | 12 | 30 | | 13 | 12 | | 14 | 9 | | 15 | 11 | | 16 | 15 | | 17 | 9 | | 18 | 6 | | 19 | 10 | | 20 | 6 | | 21 | 12 | | 22 | 5 | | 23 | 18 | | 24 | 7 | | 25 | 9 | | 26 | 9 | | 27 | 8 | | 28 | 9 | | 29 | 16 | | 30 | 12 | | 31 | 15 | | 32 | 7 | | 33 | 16 | | 34 | 12 | | 35 | 5 | | 36 | 7 | | 37 | 4 | | 38 | 21 | | 39 | 4 | | 40 | 14 | | 41 | 4 | | 42 | 10 | | 43 | 14 | | 44 | 5 | | 45 | 9 | | 46 | 4 | | 47 | 6 | | 48 | 13 | | 49 | 18 |
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| 92.52% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 1 | | diversityRatio | 0.5607476635514018 | | totalSentences | 107 | | uniqueOpeners | 60 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 60 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 12 | | totalSentences | 60 | | matches | | 0 | "He offered that infuriating half-smile" | | 1 | "She unlatched the chain and" | | 2 | "His amber eye caught the" | | 3 | "She hesitated a moment too" | | 4 | "She gathered the scattered papers," | | 5 | "He took a step closer," | | 6 | "she finally answered" | | 7 | "She pulled away, putting the" | | 8 | "His amber eye held hers," | | 9 | "She opened it carefully." | | 10 | "She stepped back, her heart" | | 11 | "he said quietly" |
| | ratio | 0.2 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 57 | | totalSentences | 60 | | matches | | 0 | "The lock clicked open one" | | 1 | "Rory peered through the security" | | 2 | "He offered that infuriating half-smile" | | 3 | "She unlatched the chain and" | | 4 | "His amber eye caught the" | | 5 | "Rory's fingers tightened on the" | | 6 | "Lucien adjusted his cufflink, the" | | 7 | "She hesitated a moment too" | | 8 | "Lucien swept past her, his" | | 9 | "Books teetered in precarious towers" | | 10 | "Scrolls lay half-unfurled across the" | | 11 | "Rory closed the door, engaging" | | 12 | "Lucien ran a gloved finger" | | 13 | "Rory crossed her arms, leaning" | | 14 | "Lucien turned, his expression unreadable" | | 15 | "A tabby cat wound its" | | 16 | "The cat responded by jumping" | | 17 | "Rory sighed, moving to right" | | 18 | "Lucien watched her with an" | | 19 | "She gathered the scattered papers," |
| | ratio | 0.95 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 60 | | matches | (empty) | | ratio | 0 | |
| 71.43% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 10 | | technicalSentenceCount | 1 | | matches | | 0 | "The pages were filled with symbols she recognized from Eva's research, but arranged in patterns that made her head ache." |
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| 90.52% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 29 | | uselessAdditionCount | 2 | | matches | | 0 | "Lucien turned, his expression unreadable" | | 1 | "She gathered, her movements precise" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 2 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 76 | | tagDensity | 0.026 | | leniency | 0.053 | | rawRatio | 0 | | effectiveRatio | 0 | |