| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 5 | | adverbTagCount | 1 | | adverbTags | | 0 | "she said finally [finally]" |
| | dialogueSentences | 47 | | tagDensity | 0.106 | | leniency | 0.213 | | rawRatio | 0.2 | | effectiveRatio | 0.043 | |
| 94.14% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 853 | | totalAiIsmAdverbs | 1 | | 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) | |
| 0.00% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 853 | | totalAiIsms | 19 | | found | | | highlights | | 0 | "weight" | | 1 | "silence" | | 2 | "charged" | | 3 | "electric" | | 4 | "pulse" | | 5 | "stomach" | | 6 | "flicked" | | 7 | "jaw clenched" | | 8 | "traced" | | 9 | "whisper" | | 10 | "unspoken" | | 11 | "reminder" |
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| 0.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 4 | | maxInWindow | 4 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 1 |
| | 1 | | label | "clenched jaw/fists" | | count | 2 |
| | 2 | | label | "jaw/fists clenched" | | count | 1 |
|
| | highlights | | 0 | "eyes narrowed" | | 1 | "clenched into fists" | | 2 | "jaw clenched" |
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| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 77 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 77 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 119 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 26 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 6 | | markdownWords | 6 | | totalWords | 848 | | ratio | 0.007 | | matches | | 0 | "care" | | 1 | "tried" | | 2 | "known" | | 3 | "known" | | 4 | "told" | | 5 | "known" |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 13 | | unquotedAttributions | 0 | | matches | (empty) | |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 59 | | wordCount | 628 | | uniqueNames | 3 | | maxNameDensity | 4.78 | | worstName | "Aurora" | | maxWindowNameDensity | 7.5 | | worstWindowName | "Eva" | | discoveredNames | | | persons | | | places | (empty) | | globalScore | 0 | | windowScore | 0 | |
| 82.43% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 37 | | glossingSentenceCount | 1 | | matches | | 0 | "smelled like the last time she’d been here" |
| |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 848 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 119 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 53 | | mean | 16 | | std | 12.32 | | cv | 0.77 | | sampleLengths | | 0 | 55 | | 1 | 37 | | 2 | 43 | | 3 | 24 | | 4 | 48 | | 5 | 33 | | 6 | 10 | | 7 | 8 | | 8 | 17 | | 9 | 6 | | 10 | 15 | | 11 | 7 | | 12 | 13 | | 13 | 28 | | 14 | 10 | | 15 | 6 | | 16 | 18 | | 17 | 27 | | 18 | 3 | | 19 | 8 | | 20 | 21 | | 21 | 7 | | 22 | 25 | | 23 | 9 | | 24 | 8 | | 25 | 11 | | 26 | 12 | | 27 | 11 | | 28 | 24 | | 29 | 5 | | 30 | 5 | | 31 | 22 | | 32 | 15 | | 33 | 5 | | 34 | 8 | | 35 | 10 | | 36 | 13 | | 37 | 11 | | 38 | 8 | | 39 | 8 | | 40 | 40 | | 41 | 10 | | 42 | 5 | | 43 | 7 | | 44 | 11 | | 45 | 9 | | 46 | 8 | | 47 | 11 | | 48 | 7 | | 49 | 42 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 77 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 113 | | matches | (empty) | |
| 94.84% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 3 | | semicolonCount | 0 | | flaggedSentences | 2 | | totalSentences | 119 | | ratio | 0.017 | | matches | | 0 | "She moved past her, the scar on her wrist—small, jagged—catching the dim light of the streetlamps outside." | | 1 | "The flat was a mess—papers scattered, a half-empty mug of tea forgotten on the table." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 632 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 24 | | adverbRatio | 0.0379746835443038 | | lyAdverbCount | 6 | | lyAdverbRatio | 0.00949367088607595 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 119 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 119 | | mean | 7.13 | | std | 5.47 | | cv | 0.768 | | sampleLengths | | 0 | 22 | | 1 | 24 | | 2 | 6 | | 3 | 3 | | 4 | 26 | | 5 | 11 | | 6 | 3 | | 7 | 17 | | 8 | 19 | | 9 | 4 | | 10 | 18 | | 11 | 5 | | 12 | 1 | | 13 | 15 | | 14 | 15 | | 15 | 18 | | 16 | 3 | | 17 | 22 | | 18 | 8 | | 19 | 5 | | 20 | 5 | | 21 | 3 | | 22 | 5 | | 23 | 9 | | 24 | 8 | | 25 | 5 | | 26 | 1 | | 27 | 4 | | 28 | 11 | | 29 | 4 | | 30 | 3 | | 31 | 4 | | 32 | 9 | | 33 | 7 | | 34 | 8 | | 35 | 8 | | 36 | 5 | | 37 | 3 | | 38 | 7 | | 39 | 4 | | 40 | 2 | | 41 | 10 | | 42 | 8 | | 43 | 3 | | 44 | 11 | | 45 | 13 | | 46 | 3 | | 47 | 6 | | 48 | 2 | | 49 | 16 |
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| 47.48% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 3 | | diversityRatio | 0.15966386554621848 | | totalSentences | 119 | | uniqueOpeners | 19 | |
| 43.86% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 76 | | matches | | 0 | "Then Eva’s fingers traced the" |
| | ratio | 0.013 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 9 | | totalSentences | 76 | | matches | | 0 | "She hadn’t come for a" | | 1 | "she said, voice tight" | | 2 | "She moved past her, the" | | 3 | "She didn’t remember that." | | 4 | "she ordered, voice low" | | 5 | "She stood in the middle" | | 6 | "she said, not a question" | | 7 | "she said finally, voice breaking" | | 8 | "She didn’t have to." |
| | ratio | 0.118 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 73 | | totalSentences | 76 | | matches | | 0 | "The front door of Eva’s" | | 1 | "Aurora Carter stepped inside, her" | | 2 | "She hadn’t come for a" | | 3 | "Eva was already on her" | | 4 | "she said, voice tight" | | 5 | "Aurora didn’t answer." | | 6 | "She moved past her, the" | | 7 | "The flat smelled like the" | | 8 | "She didn’t remember that." | | 9 | "Eva’s fingers brushed the edge" | | 10 | "she ordered, voice low" | | 11 | "Aurora hesitated, then dropped onto" | | 12 | "The flat was a mess—papers" | | 13 | "Ptolemy, the tabby cat, blinked" | | 14 | "Eva didn’t sit." | | 15 | "She stood in the middle" | | 16 | "she said, not a question" | | 17 | "Aurora exhaled, slow and steady." | | 18 | "Eva’s jaw tightened." | | 19 | "Aurora’s fingers tightened around the" |
| | ratio | 0.961 | |
| 65.79% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 76 | | matches | | | ratio | 0.013 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 23 | | technicalSentenceCount | 1 | | matches | | 0 | "Eva was already on her feet, her sharp green eyes darting between the doorframe and the chaos of bookshelves that stretched like spines across the walls." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 5 | | uselessAdditionCount | 3 | | matches | | 0 | "she said, voice tight," | | 1 | "she ordered, voice low" | | 2 | "she said finally, voice breaking" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 5 | | fancyCount | 2 | | fancyTags | | 0 | "she ordered (order)" | | 1 | "she whispered (whisper)" |
| | dialogueSentences | 47 | | tagDensity | 0.106 | | leniency | 0.213 | | rawRatio | 0.4 | | effectiveRatio | 0.085 | |