| 97.44% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 12 | | adverbTagCount | 2 | | adverbTags | | 0 | "Eva hesitated then [then]" | | 1 | "Quinn said slowly [slowly]" |
| | dialogueSentences | 39 | | tagDensity | 0.308 | | leniency | 0.615 | | rawRatio | 0.167 | | effectiveRatio | 0.103 | |
| 64.57% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 988 | | totalAiIsmAdverbs | 7 | | found | | | highlights | | 0 | "sharply" | | 1 | "nervously" | | 2 | "slightly" | | 3 | "warily" | | 4 | "slowly" |
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| 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) | |
| 24.09% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 988 | | totalAiIsms | 15 | | found | | | highlights | | 0 | "flickered" | | 1 | "echoing" | | 2 | "scanning" | | 3 | "shattered" | | 4 | "measured" | | 5 | "furrowed" | | 6 | "racing" | | 7 | "whisper" | | 8 | "etched" | | 9 | "intricate" | | 10 | "unwavering" | | 11 | "jaw clenched" | | 12 | "echoed" | | 13 | "raced" |
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| 66.67% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 2 | | maxInWindow | 2 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 1 |
| | 1 | | label | "jaw/fists clenched" | | count | 1 |
|
| | highlights | | 0 | "eyes narrowed" | | 1 | "jaw clenched" |
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| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 64 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 64 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 87 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 25 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 983 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 8 | | unquotedAttributions | 0 | | matches | (empty) | |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 41 | | wordCount | 663 | | uniqueNames | 5 | | maxNameDensity | 3.17 | | worstName | "Quinn" | | maxWindowNameDensity | 5 | | worstWindowName | "Quinn" | | discoveredNames | | Tube | 1 | | Harlow | 1 | | Quinn | 21 | | Eva | 17 | | Kowalski | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Eva" | | 3 | "Kowalski" |
| | places | (empty) | | globalScore | 0 | | windowScore | 0 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 53 | | glossingSentenceCount | 1 | | matches | | 0 | "seemed stronger now, lingering at the back of her throat" |
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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 | 983 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 87 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 30 | | mean | 32.77 | | std | 17.58 | | cv | 0.536 | | sampleLengths | | 0 | 71 | | 1 | 79 | | 2 | 57 | | 3 | 23 | | 4 | 38 | | 5 | 49 | | 6 | 31 | | 7 | 12 | | 8 | 24 | | 9 | 5 | | 10 | 26 | | 11 | 22 | | 12 | 20 | | 13 | 30 | | 14 | 26 | | 15 | 21 | | 16 | 28 | | 17 | 24 | | 18 | 45 | | 19 | 47 | | 20 | 8 | | 21 | 42 | | 22 | 16 | | 23 | 21 | | 24 | 56 | | 25 | 14 | | 26 | 40 | | 27 | 51 | | 28 | 31 | | 29 | 26 |
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| 88.82% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 64 | | matches | | 0 | "been forgotten" | | 1 | "was clipped" | | 2 | "were blackened" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 128 | | matches | | |
| 44.33% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 4 | | semicolonCount | 0 | | flaggedSentences | 3 | | totalSentences | 87 | | ratio | 0.034 | | matches | | 0 | "A faint whiff of something acrid—ozone, maybe—lingered in the air." | | 1 | "She glanced around, taking in the scattered remnants of what could have been market stalls—broken crates, discarded trinkets, a shattered lantern." | | 2 | "She hadn’t paid attention to the pattern before, but now it was unmistakable—a series of irregular cracks radiating outward, forming imperfect circles." |
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| 96.22% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 668 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 29 | | adverbRatio | 0.04341317365269461 | | lyAdverbCount | 14 | | lyAdverbRatio | 0.020958083832335328 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 87 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 87 | | mean | 11.3 | | std | 6.01 | | cv | 0.532 | | sampleLengths | | 0 | 24 | | 1 | 18 | | 2 | 15 | | 3 | 14 | | 4 | 18 | | 5 | 12 | | 6 | 14 | | 7 | 11 | | 8 | 14 | | 9 | 10 | | 10 | 11 | | 11 | 20 | | 12 | 15 | | 13 | 11 | | 14 | 11 | | 15 | 9 | | 16 | 3 | | 17 | 14 | | 18 | 24 | | 19 | 3 | | 20 | 21 | | 21 | 7 | | 22 | 3 | | 23 | 1 | | 24 | 11 | | 25 | 3 | | 26 | 21 | | 27 | 10 | | 28 | 11 | | 29 | 1 | | 30 | 11 | | 31 | 13 | | 32 | 3 | | 33 | 2 | | 34 | 9 | | 35 | 17 | | 36 | 9 | | 37 | 13 | | 38 | 12 | | 39 | 8 | | 40 | 9 | | 41 | 15 | | 42 | 2 | | 43 | 4 | | 44 | 12 | | 45 | 14 | | 46 | 7 | | 47 | 14 | | 48 | 8 | | 49 | 20 |
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| 65.52% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 3 | | diversityRatio | 0.41379310344827586 | | totalSentences | 87 | | uniqueOpeners | 36 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 60 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 15 | | totalSentences | 60 | | matches | | 0 | "Her sharp jaw was set," | | 1 | "She crouched, peeling back the" | | 2 | "Her tone was clipped, skeptical" | | 3 | "She glanced around, taking in" | | 4 | "She hadn’t paid them much" | | 5 | "she muttered, more to herself" | | 6 | "His fingertips were blackened, as" | | 7 | "She gestured to the scene" | | 8 | "She pointed to the ground" | | 9 | "She hadn’t paid attention to" | | 10 | "She held it out to" | | 11 | "She hated this." | | 12 | "She stared at the broken" | | 13 | "Her mind raced, piecing together" | | 14 | "She turned back to Eva," |
| | ratio | 0.25 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 56 | | totalSentences | 60 | | matches | | 0 | "The dim glow of emergency" | | 1 | "The air smelled damp, earthy," | | 2 | "Detective Harlow Quinn strode down" | | 3 | "Her sharp jaw was set," | | 4 | "A body lay sprawled on" | | 5 | "Quinn noted the unnatural angle" | | 6 | "She crouched, peeling back the" | | 7 | "The man’s suit was expensive" | | 8 | "A faint whiff of something" | | 9 | "The voice came from behind" | | 10 | "Quinn rose and turned to" | | 11 | "The young woman adjusted her" | | 12 | "Quinn’s gaze lingered on Eva’s" | | 13 | "Her tone was clipped, skeptical" | | 14 | "Eva tucked a strand of" | | 15 | "Quinn’s brow furrowed." | | 16 | "She glanced around, taking in" | | 17 | "She hadn’t paid them much" | | 18 | "she muttered, more to herself" | | 19 | "Eva hesitated, then opened her" |
| | ratio | 0.933 | |
| 83.33% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 60 | | matches | | | ratio | 0.017 | |
| 63.49% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 27 | | technicalSentenceCount | 3 | | matches | | 0 | "The dim glow of emergency lights flickered against the moss-covered walls of the abandoned Tube station, casting long shadows that danced like restless spirits." | | 1 | "The air smelled damp, earthy, and faintly metallic, as though the station had been forgotten by time itself." | | 2 | "His fingertips were blackened, as though burned, but the skin was cold to the touch." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 12 | | uselessAdditionCount | 5 | | matches | | 0 | "she muttered, more to herself than Eva" | | 1 | "Eva flipped, her fingers trembling slightly" | | 2 | "Eva knelt, her voice dropping to a whisper" | | 3 | "Quinn said, though her voice lacked conviction" | | 4 | "Quinn said slowly, her voice tight" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 3 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 39 | | tagDensity | 0.077 | | leniency | 0.154 | | rawRatio | 0.333 | | effectiveRatio | 0.051 | |