| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 2 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 4 | | tagDensity | 0.5 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 51.46% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 309 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | |
| 80.00% | AI-ism character names | Target: 0 AI-default names (17 tracked, −20% each) | | codexExemptions | (empty) | | found | | |
| 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 | 309 | | totalAiIsms | 7 | | found | | | highlights | | 0 | "echoed" | | 1 | "flickered" | | 2 | "glint" | | 3 | "standard" | | 4 | "traced" | | 5 | "intricate" | | 6 | "etched" |
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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 | 32 | | matches | (empty) | |
| 98.21% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 32 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 34 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 27 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 305 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 2 | | unquotedAttributions | 0 | | matches | (empty) | |
| 76.74% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 7 | | wordCount | 273 | | uniqueNames | 4 | | maxNameDensity | 1.47 | | worstName | "Quinn" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Quinn" | | discoveredNames | | Tube | 1 | | Quinn | 4 | | Detective | 1 | | Rodriguez | 1 |
| | persons | | 0 | "Quinn" | | 1 | "Detective" | | 2 | "Rodriguez" |
| | places | (empty) | | globalScore | 0.767 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 19 | | 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 | 305 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 34 | | matches | (empty) | |
| 55.15% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 10 | | mean | 30.5 | | std | 10.46 | | cv | 0.343 | | sampleLengths | | 0 | 34 | | 1 | 44 | | 2 | 15 | | 3 | 16 | | 4 | 44 | | 5 | 37 | | 6 | 41 | | 7 | 22 | | 8 | 27 | | 9 | 25 |
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| 94.30% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 32 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 42 | | matches | (empty) | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 2 | | semicolonCount | 0 | | flaggedSentences | 2 | | totalSentences | 34 | | ratio | 0.059 | | matches | | 0 | "The victim—male, mid-thirties—showed no signs of traditional trauma." | | 1 | "Her fingers traced the outline of a strange marking partially hidden beneath the victim's collar—intricate symbols that looked more like an arcane script than anything medical." |
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| 86.55% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 277 | | adjectiveStacks | 1 | | stackExamples | | 0 | "usual musty underground smell," |
| | adverbCount | 13 | | adverbRatio | 0.04693140794223827 | | lyAdverbCount | 6 | | lyAdverbRatio | 0.021660649819494584 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 34 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 34 | | mean | 8.97 | | std | 6.05 | | cv | 0.674 | | sampleLengths | | 0 | 14 | | 1 | 20 | | 2 | 17 | | 3 | 3 | | 4 | 8 | | 5 | 2 | | 6 | 3 | | 7 | 11 | | 8 | 15 | | 9 | 4 | | 10 | 12 | | 11 | 4 | | 12 | 14 | | 13 | 26 | | 14 | 5 | | 15 | 9 | | 16 | 5 | | 17 | 2 | | 18 | 16 | | 19 | 16 | | 20 | 2 | | 21 | 7 | | 22 | 16 | | 23 | 13 | | 24 | 9 | | 25 | 7 | | 26 | 11 | | 27 | 9 | | 28 | 6 | | 29 | 2 | | 30 | 3 | | 31 | 2 | | 32 | 10 | | 33 | 2 |
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| 86.27% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 4 | | diversityRatio | 0.5882352941176471 | | totalSentences | 34 | | uniqueOpeners | 20 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 26 | | matches | | 0 | "Just a look of absolute" |
| | ratio | 0.038 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 7 | | totalSentences | 26 | | matches | | 0 | "she muttered, more to herself" | | 1 | "Her fingers traced the outline" | | 2 | "She pulled out an evidence" | | 3 | "Its face was etched with" | | 4 | "she said, her voice crisp" | | 5 | "Her instincts had solved cases" | | 6 | "Her mind was already connecting" |
| | ratio | 0.269 | |
| 75.38% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 20 | | totalSentences | 26 | | matches | | 0 | "The abandoned Tube station echoed" | | 1 | "Quinn knelt, her worn leather" | | 2 | "Something felt off." | | 3 | "The victim—male, mid-thirties-showed no signs" | | 4 | "she muttered, more to herself" | | 5 | "Detective Rodriguez shifted uncomfortably." | | 6 | "Quinn's sharp jaw tightened." | | 7 | "Her fingers traced the outline" | | 8 | "The station itself felt wrong." | | 9 | "A faint trace of ozone." | | 10 | "Something that reminded her of" | | 11 | "She pulled out an evidence" | | 12 | "Its face was etched with" | | 13 | "she said, her voice crisp" | | 14 | "The other detective looked skeptical" | | 15 | "Quinn knew she had a" | | 16 | "Her instincts had solved cases" | | 17 | "Her mind was already connecting" | | 18 | "The strange markings." | | 19 | "Something told her this was" |
| | ratio | 0.769 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 26 | | matches | (empty) | | ratio | 0 | |
| 0.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 12 | | technicalSentenceCount | 3 | | matches | | 0 | "The abandoned Tube station echoed with a hollow stillness that made Quinn's skin crawl." | | 1 | "Her fingers traced the outline of a strange marking partially hidden beneath the victim's collar—intricate symbols that looked more like an arcane script than a…" | | 2 | "Something that reminded her of the unexplained circumstances surrounding her former partner's death three years ago." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 2 | | uselessAdditionCount | 2 | | matches | | 0 | "she muttered, more to herself than to her partner" | | 1 | "she said, her voice crisp with military precision" |
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| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 2 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 4 | | tagDensity | 0.5 | | leniency | 1 | | rawRatio | 0.5 | | effectiveRatio | 0.5 | |