| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 13 | | adverbTagCount | 1 | | adverbTags | | 0 | "she said quietly [quietly]" |
| | dialogueSentences | 48 | | tagDensity | 0.271 | | leniency | 0.542 | | rawRatio | 0.077 | | effectiveRatio | 0.042 | |
| 92.34% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1305 | | totalAiIsmAdverbs | 2 | | 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) | |
| 80.84% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1305 | | totalAiIsms | 5 | | found | | | highlights | | 0 | "silence" | | 1 | "etched" | | 2 | "intensity" | | 3 | "pulsed" | | 4 | "flickered" |
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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 | 88 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 1 | | narrationSentences | 88 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 123 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 35 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1305 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 14 | | unquotedAttributions | 0 | | matches | (empty) | |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 36 | | wordCount | 679 | | uniqueNames | 5 | | maxNameDensity | 2.36 | | worstName | "Quinn" | | maxWindowNameDensity | 5 | | worstWindowName | "Quinn" | | discoveredNames | | Tube | 1 | | Camden | 1 | | Quinn | 16 | | Park | 9 | | Eva | 9 |
| | persons | | 0 | "Camden" | | 1 | "Quinn" | | 2 | "Park" | | 3 | "Eva" |
| | places | (empty) | | globalScore | 0.322 | | windowScore | 0 | |
| 43.62% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 47 | | glossingSentenceCount | 2 | | matches | | 0 | "not quite touching the victim's shoe" | | 1 | "quite place" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.766 | | wordCount | 1305 | | matches | | 0 | "not north but deeper into the tunnel's darkness" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 123 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 61 | | mean | 21.39 | | std | 15.33 | | cv | 0.717 | | sampleLengths | | 0 | 14 | | 1 | 49 | | 2 | 7 | | 3 | 17 | | 4 | 48 | | 5 | 19 | | 6 | 6 | | 7 | 8 | | 8 | 37 | | 9 | 41 | | 10 | 12 | | 11 | 42 | | 12 | 15 | | 13 | 28 | | 14 | 37 | | 15 | 2 | | 16 | 35 | | 17 | 6 | | 18 | 30 | | 19 | 29 | | 20 | 41 | | 21 | 11 | | 22 | 2 | | 23 | 42 | | 24 | 3 | | 25 | 32 | | 26 | 7 | | 27 | 4 | | 28 | 29 | | 29 | 20 | | 30 | 7 | | 31 | 22 | | 32 | 15 | | 33 | 19 | | 34 | 43 | | 35 | 14 | | 36 | 25 | | 37 | 2 | | 38 | 69 | | 39 | 11 | | 40 | 13 | | 41 | 17 | | 42 | 17 | | 43 | 37 | | 44 | 5 | | 45 | 27 | | 46 | 4 | | 47 | 43 | | 48 | 11 | | 49 | 3 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 88 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 124 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 123 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 680 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 25 | | adverbRatio | 0.03676470588235294 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.007352941176470588 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 123 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 123 | | mean | 10.61 | | std | 8.39 | | cv | 0.791 | | sampleLengths | | 0 | 14 | | 1 | 8 | | 2 | 24 | | 3 | 17 | | 4 | 7 | | 5 | 8 | | 6 | 1 | | 7 | 1 | | 8 | 7 | | 9 | 24 | | 10 | 24 | | 11 | 2 | | 12 | 17 | | 13 | 6 | | 14 | 2 | | 15 | 6 | | 16 | 21 | | 17 | 11 | | 18 | 3 | | 19 | 2 | | 20 | 19 | | 21 | 22 | | 22 | 5 | | 23 | 7 | | 24 | 34 | | 25 | 8 | | 26 | 15 | | 27 | 2 | | 28 | 12 | | 29 | 14 | | 30 | 4 | | 31 | 18 | | 32 | 15 | | 33 | 2 | | 34 | 18 | | 35 | 17 | | 36 | 2 | | 37 | 4 | | 38 | 16 | | 39 | 8 | | 40 | 2 | | 41 | 2 | | 42 | 2 | | 43 | 4 | | 44 | 25 | | 45 | 4 | | 46 | 18 | | 47 | 3 | | 48 | 1 | | 49 | 15 |
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| 72.09% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 3 | | diversityRatio | 0.44715447154471544 | | totalSentences | 123 | | uniqueOpeners | 55 | |
| 93.90% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 71 | | matches | | 0 | "Somewhere above, Camden hummed with" | | 1 | "Still believed the job was" |
| | ratio | 0.028 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 16 | | totalSentences | 71 | | matches | | 0 | "Her colleague stepped into the" | | 1 | "Her worn leather watch caught" | | 2 | "She withdrew a pen from" | | 3 | "She pointed to the victim's" | | 4 | "She picked it up with" | | 5 | "Its casing bore a green" | | 6 | "He led her toward the" | | 7 | "They meant nothing to her," | | 8 | "She shouldn't have been able" | | 9 | "Her green eyes fixed on" | | 10 | "She'd noticed the fingertips." | | 11 | "She resisted the urge to" | | 12 | "she said quietly" | | 13 | "She disappeared into the tunnel's" | | 14 | "She pulled it from her" | | 15 | "It pointed directly at the" |
| | ratio | 0.225 | |
| 30.42% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 61 | | totalSentences | 71 | | matches | | 0 | "The body hung from the" | | 1 | "Quinn crouched beneath it, notebook" | | 2 | "The abandoned Tube station stretched" | | 3 | "Her colleague stepped into the" | | 4 | "Park consulted his own notes" | | 5 | "Her worn leather watch caught" | | 6 | "She withdrew a pen from" | | 7 | "She pointed to the victim's" | | 8 | "Park flipped back a page." | | 9 | "Quinn walked a slow circle" | | 10 | "Something glinted on the platform" | | 11 | "She picked it up with" | | 12 | "A small brass compass." | | 13 | "Its casing bore a green" | | 14 | "The needle spun lazily, then" | | 15 | "Quinn pocketed it before Park" | | 16 | "He led her toward the" | | 17 | "Someone had scratched symbols into" | | 18 | "Quinn studied the symbols." | | 19 | "They meant nothing to her," |
| | ratio | 0.859 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 71 | | matches | (empty) | | ratio | 0 | |
| 87.91% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 26 | | technicalSentenceCount | 2 | | matches | | 0 | "The abandoned Tube station stretched in both directions, its curved walls lined with old advertising posters for products that hadn't existed since the seventie…" | | 1 | "Her green eyes fixed on Quinn with an intensity that bordered on uncomfortable." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 13 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 2 | | fancyCount | 1 | | fancyTags | | 0 | "Eva continued (continue)" |
| | dialogueSentences | 48 | | tagDensity | 0.042 | | leniency | 0.083 | | rawRatio | 0.5 | | effectiveRatio | 0.042 | |