| 0.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 22 | | adverbTagCount | 5 | | adverbTags | | 0 | "she said softly [softly]" | | 1 | "Eva whirled around [around]" | | 2 | "Eva said quietly [quietly]" | | 3 | "she said softly [softly]" | | 4 | "Eva said firmly [firmly]" |
| | dialogueSentences | 46 | | tagDensity | 0.478 | | leniency | 0.957 | | rawRatio | 0.227 | | effectiveRatio | 0.217 | |
| 63.47% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1232 | | totalAiIsmAdverbs | 9 | | found | | | highlights | | 0 | "suddenly" | | 1 | "very" | | 2 | "softly" | | 3 | "slightly" | | 4 | "slowly" |
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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) | |
| 47.24% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1232 | | totalAiIsms | 13 | | found | | | highlights | | 0 | "echoed" | | 1 | "jaw clenched" | | 2 | "perfect" | | 3 | "shattered" | | 4 | "echo" | | 5 | "intensity" | | 6 | "silence" | | 7 | "pounding" | | 8 | "reminder" | | 9 | "unreadable" | | 10 | "firmly" | | 11 | "radiant" | | 12 | "searing" |
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| 33.33% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 3 | | maxInWindow | 3 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 1 |
| | 1 | | label | "jaw/fists clenched" | | count | 1 |
| | 2 | | label | "sent a shiver through" | | count | 1 |
|
| | highlights | | 0 | "eyes narrowed" | | 1 | "jaw clenched" | | 2 | "sent a jolt through" |
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| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 1 | | narrationSentences | 73 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 73 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 97 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 41 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1229 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 28 | | unquotedAttributions | 1 | | matches | | 0 | "Finally, she sighed, her shoulders slumping slightly." |
| |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 48 | | wordCount | 649 | | uniqueNames | 3 | | maxNameDensity | 4.01 | | worstName | "Eva" | | maxWindowNameDensity | 5.5 | | worstWindowName | "Eva" | | discoveredNames | | | persons | | 0 | "Aurora" | | 1 | "Ptolemy" | | 2 | "Eva" |
| | places | (empty) | | globalScore | 0 | | windowScore | 0 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 54 | | 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 | 1229 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 97 | | matches | | |
| 83.74% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 43 | | mean | 28.58 | | std | 12.66 | | cv | 0.443 | | sampleLengths | | 0 | 11 | | 1 | 29 | | 2 | 15 | | 3 | 27 | | 4 | 2 | | 5 | 23 | | 6 | 37 | | 7 | 20 | | 8 | 27 | | 9 | 43 | | 10 | 19 | | 11 | 30 | | 12 | 43 | | 13 | 18 | | 14 | 17 | | 15 | 20 | | 16 | 43 | | 17 | 17 | | 18 | 25 | | 19 | 28 | | 20 | 49 | | 21 | 8 | | 22 | 45 | | 23 | 50 | | 24 | 34 | | 25 | 26 | | 26 | 43 | | 27 | 27 | | 28 | 42 | | 29 | 27 | | 30 | 31 | | 31 | 36 | | 32 | 35 | | 33 | 29 | | 34 | 48 | | 35 | 14 | | 36 | 30 | | 37 | 3 | | 38 | 32 | | 39 | 29 | | 40 | 23 | | 41 | 17 | | 42 | 57 |
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| 95.65% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 73 | | matches | | 0 | "been scared" | | 1 | "was meant" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 129 | | matches | (empty) | |
| 54.49% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 3 | | semicolonCount | 0 | | flaggedSentences | 3 | | totalSentences | 97 | | ratio | 0.031 | | matches | | 0 | "She'd rehearsed this moment a hundred times on the way over—the perfect blend of apology and explanation." | | 1 | "\"You ran the moment things got hard. The moment you realized this\"—she gestured between them—\"wasn't some fairy tale romance.\"" | | 2 | "She'd been scared—of the intensity of her feelings, of the vulnerability of letting someone in." |
| |
| 91.46% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 623 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 31 | | adverbRatio | 0.04975922953451043 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.008025682182985553 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 97 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 97 | | mean | 12.67 | | std | 7.97 | | cv | 0.629 | | sampleLengths | | 0 | 11 | | 1 | 12 | | 2 | 17 | | 3 | 9 | | 4 | 6 | | 5 | 3 | | 6 | 17 | | 7 | 7 | | 8 | 2 | | 9 | 10 | | 10 | 13 | | 11 | 7 | | 12 | 10 | | 13 | 2 | | 14 | 18 | | 15 | 5 | | 16 | 15 | | 17 | 9 | | 18 | 18 | | 19 | 5 | | 20 | 18 | | 21 | 10 | | 22 | 10 | | 23 | 9 | | 24 | 10 | | 25 | 11 | | 26 | 19 | | 27 | 3 | | 28 | 7 | | 29 | 8 | | 30 | 3 | | 31 | 15 | | 32 | 7 | | 33 | 8 | | 34 | 10 | | 35 | 9 | | 36 | 8 | | 37 | 20 | | 38 | 10 | | 39 | 33 | | 40 | 10 | | 41 | 7 | | 42 | 6 | | 43 | 19 | | 44 | 8 | | 45 | 3 | | 46 | 4 | | 47 | 13 | | 48 | 8 | | 49 | 41 |
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| 43.99% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 9 | | diversityRatio | 0.31958762886597936 | | totalSentences | 97 | | uniqueOpeners | 31 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 4 | | totalSentences | 70 | | matches | | 0 | "Finally, she sighed, her shoulders" | | 1 | "Then, slowly, she brought Aurora's" | | 2 | "Then, with a shaky exhale," | | 3 | "Then, slowly, she nodded." |
| | ratio | 0.057 | |
| 82.86% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 24 | | totalSentences | 70 | | matches | | 0 | "She'd rehearsed this moment a" | | 1 | "She could still see the" | | 2 | "she said softly" | | 3 | "It was one of the" | | 4 | "she gestured between them—\"wasn't some" | | 5 | "She wanted to argue, to" | | 6 | "She had run." | | 7 | "She'd been scared—of the intensity" | | 8 | "she whispered, the words feeling" | | 9 | "She crossed her arms again," | | 10 | "she said, her voice tired" | | 11 | "She had to make Eva" | | 12 | "she began, her voice low" | | 13 | "She stepped closer to Eva," | | 14 | "She looked at Aurora with" | | 15 | "She reached out, tentatively taking" | | 16 | "she whispered, her voice thick" | | 17 | "she breathed, her voice shaky" | | 18 | "she said softly" | | 19 | "she said, her voice rough" |
| | ratio | 0.343 | |
| 45.71% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 58 | | totalSentences | 70 | | matches | | 0 | "The door flew open before" | | 1 | "Eva stood there, arms crossed," | | 2 | "Eva said, her voice dripping" | | 3 | "Aurora's jaw clenched." | | 4 | "She'd rehearsed this moment a" | | 5 | "Eva snapped, stepping aside to" | | 6 | "Aurora hesitated at the threshold," | | 7 | "The last time she'd been" | | 8 | "She could still see the" | | 9 | "she said softly" | | 10 | "Eva whirled around, her dark" | | 11 | "Aurora flinched as if struck." | | 12 | "Eva had always had a" | | 13 | "It was one of the" | | 14 | "Aurora said, her voice tight" | | 15 | "Eva stalked across the room," | | 16 | "she gestured between them—\"wasn't some" | | 17 | "Aurora's heart clenched." | | 18 | "She wanted to argue, to" | | 19 | "She had run." |
| | ratio | 0.829 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 70 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 29 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 22 | | uselessAdditionCount | 14 | | matches | | 0 | "Eva said, her voice dripping with sarcasm" | | 1 | "Eva whirled around, her dark eyes flashing" | | 2 | "Aurora said, her voice tight" | | 3 | "Eva stalked, her movements sharp and agitated" | | 4 | "she whispered, the words feeling inadequate" | | 5 | "she said, her voice tired" | | 6 | "she began, her voice low" | | 7 | "Aurora continued, her words coming faster now" | | 8 | "she whispered, her voice thick with emotion" | | 9 | "she breathed, her voice shaky" | | 10 | "Aurora said, her thumb brushing over Eva's cheek" | | 11 | "she said, her voice rough with emotion" | | 12 | "she said, her voice steady" | | 13 | "she whispered, her lips brushing against Aurora's" |
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| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 18 | | fancyCount | 8 | | fancyTags | | 0 | "Eva snapped (snap)" | | 1 | "she whispered (whisper)" | | 2 | "Aurora continued (continue)" | | 3 | "she whispered (whisper)" | | 4 | "she breathed (breathe)" | | 5 | "she whispered (whisper)" | | 6 | "Aurora breathed (breathe)" | | 7 | "she whispered (whisper)" |
| | dialogueSentences | 46 | | tagDensity | 0.391 | | leniency | 0.783 | | rawRatio | 0.444 | | effectiveRatio | 0.348 | |