| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 6 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 12 | | tagDensity | 0.5 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 560 | | 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) | |
| 73.21% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 560 | | totalAiIsms | 3 | | found | | | highlights | | 0 | "streaming" | | 1 | "footsteps" | | 2 | "echoed" |
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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 | 37 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 37 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 43 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 32 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 563 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 2 | | unquotedAttributions | 0 | | matches | (empty) | |
| 28.32% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 27 | | wordCount | 452 | | uniqueNames | 14 | | maxNameDensity | 2.43 | | worstName | "Quinn" | | maxWindowNameDensity | 3 | | worstWindowName | "Quinn" | | discoveredNames | | Detective | 1 | | Quinn | 11 | | Camden | 1 | | High | 1 | | Street | 1 | | Raven | 1 | | Nest | 1 | | Morris | 2 | | Veil | 1 | | Market | 1 | | Saint | 1 | | Christopher | 1 | | Herrera | 1 | | Tomás | 3 |
| | persons | | 0 | "Detective" | | 1 | "Quinn" | | 2 | "Raven" | | 3 | "Morris" | | 4 | "Saint" | | 5 | "Christopher" | | 6 | "Herrera" | | 7 | "Tomás" |
| | places | | 0 | "Camden" | | 1 | "High" | | 2 | "Street" |
| | globalScore | 0.283 | | windowScore | 0.667 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 33 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 22.38% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 1.776 | | wordCount | 563 | | matches | | 0 | "not just her suspect, but other shapes moving in" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 43 | | matches | (empty) | |
| 77.92% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 17 | | mean | 33.12 | | std | 14 | | cv | 0.423 | | sampleLengths | | 0 | 44 | | 1 | 53 | | 2 | 21 | | 3 | 45 | | 4 | 53 | | 5 | 42 | | 6 | 42 | | 7 | 39 | | 8 | 27 | | 9 | 16 | | 10 | 9 | | 11 | 26 | | 12 | 18 | | 13 | 38 | | 14 | 33 | | 15 | 10 | | 16 | 47 |
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| 86.30% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 37 | | matches | | 0 | "been closed" | | 1 | "were bought" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 67 | | matches | | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 6 | | semicolonCount | 0 | | flaggedSentences | 6 | | totalSentences | 43 | | ratio | 0.14 | | matches | | 0 | "They'd made eye contact across the bar - Quinn sitting at her usual spot watching Silas' clientele, the suspect emerging from that damned hidden back room she could never find a way into." | | 1 | "Three years of dead ends since Morris disappeared, and now finally a lead - she wasn't about to lose it." | | 2 | "The underground station had been closed for decades - officially." | | 3 | "The air grew thick, carrying the musty scent of abandonment mixed with something else - incense maybe, or herbs." | | 4 | "The beam of her torch caught glimpses of movement in the darkness ahead - not just her suspect, but other shapes moving in and out of old maintenance doorways." | | 5 | "Quinn's torch beam caught glimpses of impossible shadows on the walls - things with too many limbs, shapes that shouldn't exist." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 149 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 1 | | adverbRatio | 0.006711409395973154 | | lyAdverbCount | 0 | | lyAdverbRatio | 0 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 43 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 43 | | mean | 13.09 | | std | 6.45 | | cv | 0.492 | | sampleLengths | | 0 | 18 | | 1 | 11 | | 2 | 15 | | 3 | 3 | | 4 | 17 | | 5 | 33 | | 6 | 21 | | 7 | 10 | | 8 | 15 | | 9 | 20 | | 10 | 8 | | 11 | 16 | | 12 | 12 | | 13 | 17 | | 14 | 7 | | 15 | 10 | | 16 | 11 | | 17 | 3 | | 18 | 11 | | 19 | 14 | | 20 | 9 | | 21 | 19 | | 22 | 10 | | 23 | 29 | | 24 | 8 | | 25 | 19 | | 26 | 10 | | 27 | 6 | | 28 | 9 | | 29 | 13 | | 30 | 13 | | 31 | 7 | | 32 | 11 | | 33 | 14 | | 34 | 24 | | 35 | 12 | | 36 | 21 | | 37 | 5 | | 38 | 5 | | 39 | 6 | | 40 | 9 | | 41 | 13 | | 42 | 19 |
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| 90.70% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 1 | | diversityRatio | 0.5581395348837209 | | totalSentences | 43 | | uniqueOpeners | 24 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 36 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 6 | | totalSentences | 36 | | matches | | 0 | "Her boots splashed through puddles," | | 1 | "She'd been chasing the suspect" | | 2 | "They'd made eye contact across" | | 3 | "Her voice cut through the" | | 4 | "Her hand went to her" | | 5 | "His warm brown eyes fixed" |
| | ratio | 0.167 | |
| 43.33% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 30 | | totalSentences | 36 | | matches | | 0 | "Rain drummed against Detective Quinn's" | | 1 | "Her boots splashed through puddles," | | 2 | "Quinn's lungs burned." | | 3 | "She'd been chasing the suspect" | | 4 | "They'd made eye contact across" | | 5 | "Her voice cut through the" | | 6 | "The suspect's shoulder clipped a" | | 7 | "Quinn vaulted over the fallen" | | 8 | "The alley opened onto a" | | 9 | "Rusty chains hung broken from" | | 10 | "Quinn pulled up short at" | | 11 | "The stairwell gaped like a" | | 12 | "Her hand went to her" | | 13 | "The underground station had been" | | 14 | "The Veil Market." | | 15 | "A place where things that" | | 16 | "Quinn drew her torch and" | | 17 | "Each step groaned under her" | | 18 | "The air grew thick, carrying" | | 19 | "The beam of her torch" |
| | ratio | 0.833 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 36 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 20 | | technicalSentenceCount | 1 | | matches | | 0 | "Quinn's torch beam caught glimpses of impossible shadows on the walls - things with too many limbs, shapes that shouldn't exist." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 6 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 1 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 12 | | tagDensity | 0.083 | | leniency | 0.167 | | rawRatio | 0 | | effectiveRatio | 0 | |