| 75.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 12 | | adverbTagCount | 3 | | adverbTags | | 0 | "she said finally [finally]" | | 1 | "he said quietly [quietly]" | | 2 | "she said firmly [firmly]" |
| | dialogueSentences | 48 | | tagDensity | 0.25 | | leniency | 0.5 | | rawRatio | 0.25 | | effectiveRatio | 0.125 | |
| 80.42% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1277 | | totalAiIsmAdverbs | 5 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | adverb | "reluctantly" | | count | 1 |
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| | highlights | | 0 | "softly" | | 1 | "lazily" | | 2 | "carefully" | | 3 | "slightly" | | 4 | "reluctantly" |
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| 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) | |
| 37.35% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1277 | | totalAiIsms | 16 | | found | | | highlights | | 0 | "scanned" | | 1 | "flicker" | | 2 | "tinged" | | 3 | "pristine" | | 4 | "glinting" | | 5 | "etched" | | 6 | "intricate" | | 7 | "racing" | | 8 | "glint" | | 9 | "palpable" | | 10 | "scanning" | | 11 | "gloom" | | 12 | "firmly" |
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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 | 1 | | narrationSentences | 76 | | matches | | |
| 48.87% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 4 | | narrationSentences | 76 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 112 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 30 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1266 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 17 | | unquotedAttributions | 0 | | matches | (empty) | |
| 66.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 22 | | wordCount | 880 | | uniqueNames | 8 | | maxNameDensity | 1.59 | | worstName | "Evans" | | maxWindowNameDensity | 3 | | worstWindowName | "Evans" | | discoveredNames | | Harlow | 1 | | Quinn | 1 | | Camden | 1 | | Veil | 1 | | Market | 1 | | Detective | 2 | | Sergeant | 1 | | Evans | 14 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Sergeant" | | 3 | "Evans" |
| | places | (empty) | | globalScore | 0.705 | | windowScore | 0.667 | |
| 0.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 65 | | glossingSentenceCount | 5 | | matches | | 0 | "seemed obvious at first glance—a single gunshot wound to the chest" | | 1 | "looked like makeshift stalls" | | 2 | "seemed almost deliberate" | | 3 | "looked like ash" | | 4 | "silver that seemed to glint in the dim light" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1266 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 112 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 56 | | mean | 22.61 | | std | 18.22 | | cv | 0.806 | | sampleLengths | | 0 | 85 | | 1 | 67 | | 2 | 72 | | 3 | 4 | | 4 | 31 | | 5 | 38 | | 6 | 28 | | 7 | 48 | | 8 | 3 | | 9 | 2 | | 10 | 25 | | 11 | 12 | | 12 | 13 | | 13 | 55 | | 14 | 8 | | 15 | 15 | | 16 | 11 | | 17 | 40 | | 18 | 11 | | 19 | 6 | | 20 | 56 | | 21 | 2 | | 22 | 26 | | 23 | 18 | | 24 | 10 | | 25 | 30 | | 26 | 8 | | 27 | 37 | | 28 | 28 | | 29 | 19 | | 30 | 13 | | 31 | 20 | | 32 | 3 | | 33 | 8 | | 34 | 31 | | 35 | 4 | | 36 | 8 | | 37 | 30 | | 38 | 14 | | 39 | 24 | | 40 | 24 | | 41 | 8 | | 42 | 19 | | 43 | 44 | | 44 | 24 | | 45 | 7 | | 46 | 34 | | 47 | 3 | | 48 | 18 | | 49 | 15 |
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| 77.56% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 6 | | totalSentences | 76 | | matches | | 0 | "were polished" | | 1 | "been frozen" | | 2 | "was littered" | | 3 | "been made" | | 4 | "were jagged" | | 5 | "were discolored" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 164 | | matches | | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 7 | | semicolonCount | 0 | | flaggedSentences | 7 | | totalSentences | 112 | | ratio | 0.063 | | matches | | 0 | "This wasn’t her jurisdiction, but the call had come in late last night—a detective she knew vaguely, asking for her expertise." | | 1 | "The cause of death seemed obvious at first glance—a single gunshot wound to the chest." | | 2 | "She reached out, touching the fabric of his sleeve—cold and stiff, almost like it had been frozen." | | 3 | "The platform was littered with trash—empty bottles, torn newspapers, and the remnants of what looked like makeshift stalls." | | 4 | "The pristine suit, the coldness of the skin, the protective sigils, the compass—it all pointed to something beyond a simple murder." | | 5 | "But there was something else—a faint shimmer in the air, like heat rising from asphalt." | | 6 | "Whatever was on the other side, it held the answers they were looking for—and she wasn’t about to stop until she found them." |
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| 98.82% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 774 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 32 | | adverbRatio | 0.041343669250646 | | lyAdverbCount | 11 | | lyAdverbRatio | 0.014211886304909561 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 112 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 112 | | mean | 11.3 | | std | 6.52 | | cv | 0.577 | | sampleLengths | | 0 | 25 | | 1 | 21 | | 2 | 10 | | 3 | 29 | | 4 | 3 | | 5 | 10 | | 6 | 23 | | 7 | 21 | | 8 | 4 | | 9 | 6 | | 10 | 13 | | 11 | 25 | | 12 | 11 | | 13 | 15 | | 14 | 8 | | 15 | 4 | | 16 | 15 | | 17 | 16 | | 18 | 8 | | 19 | 30 | | 20 | 9 | | 21 | 19 | | 22 | 11 | | 23 | 12 | | 24 | 8 | | 25 | 17 | | 26 | 3 | | 27 | 2 | | 28 | 25 | | 29 | 2 | | 30 | 10 | | 31 | 8 | | 32 | 5 | | 33 | 13 | | 34 | 18 | | 35 | 8 | | 36 | 16 | | 37 | 8 | | 38 | 7 | | 39 | 8 | | 40 | 11 | | 41 | 9 | | 42 | 10 | | 43 | 7 | | 44 | 14 | | 45 | 11 | | 46 | 6 | | 47 | 12 | | 48 | 13 | | 49 | 8 |
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| 58.63% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 1 | | diversityRatio | 0.35714285714285715 | | totalSentences | 112 | | uniqueOpeners | 40 | |
| 45.66% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 73 | | matches | | | ratio | 0.014 | |
| 33.70% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 34 | | totalSentences | 73 | | matches | | 0 | "Her sharp jaw tightened as" | | 1 | "She’d heard whispers of it" | | 2 | "She approached the body, her" | | 3 | "His face was pale, almost" | | 4 | "She turned to see Detective" | | 5 | "He was younger than her," | | 6 | "she said, nodding toward the" | | 7 | "She didn’t respond, crouching down" | | 8 | "His shoes were polished to" | | 9 | "She reached out, touching the" | | 10 | "She stood, brushing her hands" | | 11 | "Her gaze shifted to the" | | 12 | "she asked, pointing to the" | | 13 | "She moved closer, running her" | | 14 | "She’d seen them before, in" | | 15 | "Her eyes caught on something" | | 16 | "She knelt down again, picking" | | 17 | "she said, turning it over" | | 18 | "She glanced back at the" | | 19 | "she said finally" |
| | ratio | 0.466 | |
| 7.95% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 66 | | totalSentences | 73 | | matches | | 0 | "Detective Harlow Quinn stepped into" | | 1 | "The air smelled damp, thick" | | 2 | "Her sharp jaw tightened as" | | 3 | "The Veil Market." | | 4 | "She’d heard whispers of it" | | 5 | "This wasn’t her jurisdiction, but" | | 6 | "She approached the body, her" | | 7 | "The victim was a man" | | 8 | "His face was pale, almost" | | 9 | "The cause of death seemed" | | 10 | "She turned to see Detective" | | 11 | "He was younger than her," | | 12 | "she said, nodding toward the" | | 13 | "Evans shrugged, shoving his hands" | | 14 | "She didn’t respond, crouching down" | | 15 | "The man’s suit was pristine," | | 16 | "His shoes were polished to" | | 17 | "She reached out, touching the" | | 18 | "She stood, brushing her hands" | | 19 | "Her gaze shifted to the" |
| | ratio | 0.904 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 73 | | matches | (empty) | | ratio | 0 | |
| 90.59% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 41 | | technicalSentenceCount | 3 | | matches | | 0 | "He was younger than her, mid-thirties, with a perpetually rumpled look that belied his sharp mind." | | 1 | "The nails were discolored, almost blackened, with faint traces of something that looked like ash." | | 2 | "The man’s eyes were wide open, the irises an unnatural shade of silver that seemed to glint in the dim light." |
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| 83.33% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 12 | | uselessAdditionCount | 1 | | matches | | 0 | "she said, her voice low" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 11 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 48 | | tagDensity | 0.229 | | leniency | 0.458 | | rawRatio | 0.091 | | effectiveRatio | 0.042 | |