| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 5 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 16 | | tagDensity | 0.313 | | leniency | 0.625 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 384 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 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) | |
| 34.90% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 384 | | totalAiIsms | 5 | | found | | | highlights | | 0 | "echoed" | | 1 | "scanning" | | 2 | "etched" | | 3 | "glinting" | | 4 | "racing" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 1 |
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| | highlights | | |
| 88.77% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 1 | | narrationSentences | 23 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 23 | | filterMatches | (empty) | | 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 | 29 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 383 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 1 | | unquotedAttributions | 0 | | matches | (empty) | |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 20 | | wordCount | 217 | | uniqueNames | 6 | | maxNameDensity | 3.69 | | worstName | "Quinn" | | maxWindowNameDensity | 4 | | worstWindowName | "Quinn" | | discoveredNames | | Harlow | 2 | | Quinn | 8 | | Tube | 1 | | Kowalski | 1 | | Eva | 6 | | Detective | 2 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Kowalski" | | 3 | "Eva" |
| | places | (empty) | | globalScore | 0 | | windowScore | 0.333 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 13 | | 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 | 383 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 34 | | matches | (empty) | |
| 71.11% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 14 | | mean | 27.36 | | std | 10.91 | | cv | 0.399 | | sampleLengths | | 0 | 42 | | 1 | 7 | | 2 | 16 | | 3 | 38 | | 4 | 22 | | 5 | 30 | | 6 | 27 | | 7 | 23 | | 8 | 16 | | 9 | 25 | | 10 | 31 | | 11 | 38 | | 12 | 20 | | 13 | 48 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 23 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 39 | | matches | (empty) | |
| 58.82% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 1 | | semicolonCount | 0 | | flaggedSentences | 1 | | totalSentences | 34 | | ratio | 0.029 | | matches | | 0 | "Quinn's sharp gaze took in the details—the small brass compass nearby, its needle twitching, the worn leather satchel spilled open, books strewn about." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 218 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 4 | | adverbRatio | 0.01834862385321101 | | lyAdverbCount | 1 | | lyAdverbRatio | 0.0045871559633027525 | |
| 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 | 11.26 | | std | 6.3 | | cv | 0.56 | | sampleLengths | | 0 | 12 | | 1 | 23 | | 2 | 7 | | 3 | 7 | | 4 | 12 | | 5 | 4 | | 6 | 15 | | 7 | 23 | | 8 | 12 | | 9 | 10 | | 10 | 18 | | 11 | 8 | | 12 | 4 | | 13 | 5 | | 14 | 22 | | 15 | 12 | | 16 | 5 | | 17 | 6 | | 18 | 3 | | 19 | 13 | | 20 | 5 | | 21 | 10 | | 22 | 10 | | 23 | 4 | | 24 | 13 | | 25 | 14 | | 26 | 8 | | 27 | 16 | | 28 | 14 | | 29 | 4 | | 30 | 16 | | 31 | 29 | | 32 | 13 | | 33 | 6 |
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| 73.53% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 0 | | diversityRatio | 0.4411764705882353 | | totalSentences | 34 | | uniqueOpeners | 15 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 22 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 3 | | totalSentences | 22 | | matches | | 0 | "She stood, surveying the area." | | 1 | "She turned to Eva." | | 2 | "She glanced at Eva" |
| | ratio | 0.136 | |
| 73.64% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 17 | | totalSentences | 22 | | matches | | 0 | "The underground market was abuzz" | | 1 | "Detective Harlow Quinn's leather shoes" | | 2 | "A constable stopped her at" | | 3 | "Quinn flashed her badge" | | 4 | "The constable led her to" | | 5 | "Quinn's sharp gaze took in" | | 6 | "Eva Kowalski emerged from the" | | 7 | "Quinn knelt beside the corpse," | | 8 | "A young man, his eyes" | | 9 | "Eva tugged at her hair." | | 10 | "Quinn inspected the compass, its" | | 11 | "She stood, surveying the area." | | 12 | "The constable shuffled." | | 13 | "She turned to Eva." | | 14 | "She glanced at Eva" | | 15 | "Eva hesitated, then sighed." | | 16 | "Something had gone terribly wrong" |
| | ratio | 0.773 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 22 | | matches | (empty) | | ratio | 0 | |
| 53.57% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 8 | | technicalSentenceCount | 1 | | matches | | 0 | "But Detective Harlow Quinn was already striding away, her military precision cutting through the chaos of the market, her mind racing to uncover the truth hidde…" |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 5 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 87.50% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 1 | | fancyCount | 1 | | fancyTags | | 0 | "At Eva's nod she continued (continue)" |
| | dialogueSentences | 16 | | tagDensity | 0.063 | | leniency | 0.125 | | rawRatio | 1 | | effectiveRatio | 0.125 | |