| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 6 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 65 | | tagDensity | 0.092 | | leniency | 0.185 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 70.47% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1016 | | totalAiIsmAdverbs | 6 | | found | | | highlights | | 0 | "slightly" | | 1 | "slowly" | | 2 | "really" | | 3 | "sharply" |
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| 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) | |
| 60.63% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1016 | | totalAiIsms | 8 | | found | | | highlights | | 0 | "flickered" | | 1 | "stomach" | | 2 | "trembled" | | 3 | "whisper" | | 4 | "pounding" | | 5 | "eyebrow" |
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| 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 | 90 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 90 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 149 | | 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 | 2 | | markdownWords | 15 | | totalWords | 1008 | | ratio | 0.015 | | matches | | 0 | "Evan" | | 1 | "I’m sorry. I don’t know what I was thinking. I’ll fix this. I promise." |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 11 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 6 | | wordCount | 679 | | uniqueNames | 5 | | maxNameDensity | 0.29 | | worstName | "Rory" | | maxWindowNameDensity | 1 | | worstWindowName | "Rory" | | discoveredNames | | Raven | 1 | | Nest | 1 | | Rory | 2 | | Silas | 1 | | Evan | 1 |
| | persons | | 0 | "Raven" | | 1 | "Nest" | | 2 | "Rory" | | 3 | "Silas" | | 4 | "Evan" |
| | places | (empty) | | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 44 | | 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 | 1008 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 149 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 75 | | mean | 13.44 | | std | 15.67 | | cv | 1.166 | | sampleLengths | | 0 | 110 | | 1 | 61 | | 2 | 10 | | 3 | 1 | | 4 | 48 | | 5 | 10 | | 6 | 9 | | 7 | 8 | | 8 | 2 | | 9 | 3 | | 10 | 15 | | 11 | 9 | | 12 | 2 | | 13 | 43 | | 14 | 15 | | 15 | 7 | | 16 | 16 | | 17 | 1 | | 18 | 7 | | 19 | 27 | | 20 | 4 | | 21 | 9 | | 22 | 11 | | 23 | 31 | | 24 | 7 | | 25 | 1 | | 26 | 9 | | 27 | 25 | | 28 | 6 | | 29 | 25 | | 30 | 28 | | 31 | 14 | | 32 | 8 | | 33 | 3 | | 34 | 6 | | 35 | 17 | | 36 | 9 | | 37 | 2 | | 38 | 5 | | 39 | 23 | | 40 | 5 | | 41 | 22 | | 42 | 7 | | 43 | 15 | | 44 | 7 | | 45 | 28 | | 46 | 9 | | 47 | 6 | | 48 | 10 | | 49 | 9 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 90 | | matches | (empty) | |
| 0.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 6 | | totalVerbs | 149 | | matches | | 0 | "was waiting" | | 1 | "were shaking" | | 2 | "was trying" | | 3 | "was thinking" | | 4 | "was pounding" | | 5 | "was walking" |
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| 8.63% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 8 | | semicolonCount | 0 | | flaggedSentences | 7 | | totalSentences | 149 | | ratio | 0.047 | | matches | | 0 | "The air inside was thick with the scent of aged whiskey and something sharper—gun oil, maybe, or the faint metallic tang of old secrets." | | 1 | "His back was to her, but she knew that posture—broad shoulders, the way he held himself like he was waiting for something to break." | | 2 | "She’d seen it before—men who drank to forget, who drowned themselves in bottles because the world had given them too many reasons to hate it." | | 3 | "From something worse—recognition." | | 4 | "“No.” He took a step closer, the scent of whiskey and something else—cigarette smoke, maybe—filling her nose." | | 5 | "She recognised the stationery—Evan’s." | | 6 | "She didn’t know what she was walking into, but she knew one thing—she was in too deep already." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 687 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 24 | | adverbRatio | 0.034934497816593885 | | lyAdverbCount | 6 | | lyAdverbRatio | 0.008733624454148471 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 149 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 149 | | mean | 6.77 | | std | 5.57 | | cv | 0.823 | | sampleLengths | | 0 | 24 | | 1 | 24 | | 2 | 13 | | 3 | 5 | | 4 | 20 | | 5 | 24 | | 6 | 2 | | 7 | 6 | | 8 | 24 | | 9 | 14 | | 10 | 11 | | 11 | 3 | | 12 | 1 | | 13 | 10 | | 14 | 1 | | 15 | 12 | | 16 | 12 | | 17 | 12 | | 18 | 5 | | 19 | 7 | | 20 | 10 | | 21 | 6 | | 22 | 3 | | 23 | 3 | | 24 | 5 | | 25 | 2 | | 26 | 2 | | 27 | 1 | | 28 | 11 | | 29 | 4 | | 30 | 2 | | 31 | 7 | | 32 | 2 | | 33 | 6 | | 34 | 5 | | 35 | 25 | | 36 | 5 | | 37 | 2 | | 38 | 15 | | 39 | 5 | | 40 | 2 | | 41 | 5 | | 42 | 11 | | 43 | 1 | | 44 | 2 | | 45 | 5 | | 46 | 12 | | 47 | 7 | | 48 | 3 | | 49 | 5 |
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| 43.96% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 9 | | diversityRatio | 0.2953020134228188 | | totalSentences | 149 | | uniqueOpeners | 44 | |
| 43.86% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 76 | | matches | | 0 | "Just watched her, like he" |
| | ratio | 0.013 | |
| 0.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 62 | | totalSentences | 76 | | matches | | 0 | "She’d come in early, before" | | 1 | "His back was to her," | | 2 | "She hadn’t seen him in" | | 3 | "His jaw was sharper now," | | 4 | "He looked older." | | 5 | "she muttered, stepping back before" | | 6 | "His voice was rough, like" | | 7 | "She turned, pressing herself against" | | 8 | "He stood, slow and deliberate," | | 9 | "she said, voice tight" | | 10 | "He laughed, low and without" | | 11 | "She didn’t move." | | 12 | "He studied her for a" | | 13 | "She knew what that meant." | | 14 | "She’d seen it before—men who" | | 15 | "she asked, voice steady despite" | | 16 | "He tilted his head, considering." | | 17 | "She exhaled through her nose." | | 18 | "His name on her lips" | | 19 | "He flinched too, but not" |
| | ratio | 0.816 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 70 | | totalSentences | 76 | | matches | | 0 | "The green neon sign of" | | 1 | "The air inside was thick" | | 2 | "She’d come in early, before" | | 3 | "A figure sat in the" | | 4 | "His back was to her," | | 5 | "She hadn’t seen him in" | | 6 | "His jaw was sharper now," | | 7 | "He looked older." | | 8 | "she muttered, stepping back before" | | 9 | "His voice was rough, like" | | 10 | "She turned, pressing herself against" | | 11 | "He stood, slow and deliberate," | | 12 | "The old knee, she remembered." | | 13 | "The one that had ruined" | | 14 | "she said, voice tight" | | 15 | "He laughed, low and without" | | 16 | "She didn’t move." | | 17 | "He studied her for a" | | 18 | "The words hung between them," | | 19 | "She knew what that meant." |
| | ratio | 0.921 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 76 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 23 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 41.67% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 6 | | uselessAdditionCount | 1 | | matches | | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 4 | | fancyCount | 2 | | fancyTags | | 0 | "she muttered (mutter)" | | 1 | "she repeated (repeat)" |
| | dialogueSentences | 65 | | tagDensity | 0.062 | | leniency | 0.123 | | rawRatio | 0.5 | | effectiveRatio | 0.062 | |