| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 19 | | adverbTagCount | 1 | | adverbTags | | 0 | "Eva said grimly [grimly]" |
| | dialogueSentences | 37 | | tagDensity | 0.514 | | leniency | 1 | | rawRatio | 0.053 | | effectiveRatio | 0.053 | |
| 87.48% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1198 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | 0 | "completely" | | 1 | "carefully" |
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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) | |
| 29.05% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1198 | | totalAiIsms | 17 | | found | | | highlights | | 0 | "weight" | | 1 | "furrowed" | | 2 | "perfect" | | 3 | "familiar" | | 4 | "echoed" | | 5 | "stomach" | | 6 | "etched" | | 7 | "navigate" | | 8 | "raced" | | 9 | "constructed" | | 10 | "dance" | | 11 | "chill" | | 12 | "unspoken" | | 13 | "measured" | | 14 | "cataloged" |
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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 | 74 | | matches | | |
| 84.94% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 2 | | narrationSentences | 74 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 92 | | 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 | 1190 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 20 | | unquotedAttributions | 0 | | matches | (empty) | |
| 27.34% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 41 | | wordCount | 856 | | uniqueNames | 5 | | maxNameDensity | 2.45 | | worstName | "Quinn" | | maxWindowNameDensity | 4 | | worstWindowName | "Quinn" | | discoveredNames | | Tube | 1 | | Quinn | 21 | | Davies | 2 | | Eva | 16 | | Kowalski | 1 |
| | persons | | 0 | "Quinn" | | 1 | "Davies" | | 2 | "Eva" | | 3 | "Kowalski" |
| | places | (empty) | | globalScore | 0.273 | | windowScore | 0.333 | |
| 18.42% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 57 | | glossingSentenceCount | 3 | | matches | | 0 | "looked like he belonged in secondary scho" | | 1 | "discoloration that seemed to emanate from beneath the nails" | | 2 | "as if responding to their conversation" |
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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 | 1190 | | matches | (empty) | |
| 94.20% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 2 | | totalSentences | 92 | | matches | | 0 | "keep that detail" | | 1 | "whispered that Eva" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 41 | | mean | 29.02 | | std | 16.27 | | cv | 0.56 | | sampleLengths | | 0 | 58 | | 1 | 10 | | 2 | 29 | | 3 | 44 | | 4 | 67 | | 5 | 8 | | 6 | 17 | | 7 | 47 | | 8 | 16 | | 9 | 42 | | 10 | 22 | | 11 | 30 | | 12 | 13 | | 13 | 28 | | 14 | 36 | | 15 | 36 | | 16 | 25 | | 17 | 20 | | 18 | 39 | | 19 | 9 | | 20 | 49 | | 21 | 6 | | 22 | 27 | | 23 | 20 | | 24 | 45 | | 25 | 29 | | 26 | 13 | | 27 | 51 | | 28 | 37 | | 29 | 20 | | 30 | 23 | | 31 | 7 | | 32 | 29 | | 33 | 53 | | 34 | 25 | | 35 | 15 | | 36 | 26 | | 37 | 28 | | 38 | 69 | | 39 | 13 | | 40 | 9 |
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| 91.04% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 74 | | matches | | 0 | "been collected" | | 1 | "been decommissioned" | | 2 | "been bleached" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 162 | | matches | | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 6 | | semicolonCount | 0 | | flaggedSentences | 6 | | totalSentences | 92 | | ratio | 0.065 | | matches | | 0 | "The forensic team had already marked the scene—numbered cones dotting the grimy tiles where evidence had been collected." | | 1 | "Her worn leather watch caught the dim light—ten minutes past midnight." | | 2 | "But it was the eyes that made Quinn pause—completely white, as if the irises had been bleached of all color." | | 3 | "Eva shrugged, tucking a stray curl behind her left ear—a nervous habit Quinn had noticed during their previous encounters." | | 4 | "There, barely visible in the grime, was a pattern of scratches—five parallel lines, repeated at intervals." | | 5 | "Quinn held up the small brass object—a compass, its casing tarnished with verdigris, protective sigils etched into its face." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 863 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 28 | | adverbRatio | 0.03244495944380069 | | lyAdverbCount | 11 | | lyAdverbRatio | 0.012746234067207415 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 92 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 92 | | mean | 12.93 | | std | 5.96 | | cv | 0.461 | | sampleLengths | | 0 | 21 | | 1 | 19 | | 2 | 18 | | 3 | 10 | | 4 | 16 | | 5 | 13 | | 6 | 15 | | 7 | 11 | | 8 | 14 | | 9 | 4 | | 10 | 11 | | 11 | 18 | | 12 | 18 | | 13 | 20 | | 14 | 8 | | 15 | 4 | | 16 | 13 | | 17 | 17 | | 18 | 2 | | 19 | 2 | | 20 | 7 | | 21 | 19 | | 22 | 9 | | 23 | 7 | | 24 | 14 | | 25 | 20 | | 26 | 8 | | 27 | 15 | | 28 | 7 | | 29 | 19 | | 30 | 11 | | 31 | 5 | | 32 | 8 | | 33 | 11 | | 34 | 17 | | 35 | 17 | | 36 | 12 | | 37 | 7 | | 38 | 14 | | 39 | 22 | | 40 | 21 | | 41 | 4 | | 42 | 7 | | 43 | 13 | | 44 | 19 | | 45 | 17 | | 46 | 1 | | 47 | 2 | | 48 | 9 | | 49 | 15 |
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| 72.10% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 2 | | diversityRatio | 0.44565217391304346 | | totalSentences | 92 | | uniqueOpeners | 41 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 66 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 16 | | totalSentences | 66 | | matches | | 0 | "she asked, pulling on latex" | | 1 | "Her worn leather watch caught" | | 2 | "They found the body thirty" | | 3 | "His skin had taken on" | | 4 | "she asked, kneeling beside the" | | 5 | "She snapped on a flashlight" | | 6 | "She straightened, recognizing the red" | | 7 | "She'd hoped to avoid this" | | 8 | "She'd been trying to keep" | | 9 | "She moved to the tunnel" | | 10 | "She pulled a small evidence" | | 11 | "She'd always assumed it was" | | 12 | "she asked, watching the needle" | | 13 | "She pulled out her radio." | | 14 | "She lowered her voice" | | 15 | "She slipped it into an" |
| | ratio | 0.242 | |
| 35.76% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 56 | | totalSentences | 66 | | matches | | 0 | "The air in the abandoned" | | 1 | "Harlow Quinn stepped over the" | | 2 | "The forensic team had already" | | 3 | "she asked, pulling on latex" | | 4 | "PC Davies, a young officer" | | 5 | "Quinn's brow furrowed as she" | | 6 | "Her worn leather watch caught" | | 7 | "The station had been decommissioned" | | 8 | "They found the body thirty" | | 9 | "The victim was male, mid-thirties," | | 10 | "His skin had taken on" | | 11 | "she asked, kneeling beside the" | | 12 | "Quinn pulled out a small" | | 13 | "She snapped on a flashlight" | | 14 | "A familiar voice echoed down" | | 15 | "She straightened, recognizing the red" | | 16 | "The occult researcher carried her" | | 17 | "Quinn kept her voice neutral," | | 18 | "She'd hoped to avoid this" | | 19 | "Eva shrugged, tucking a stray" |
| | ratio | 0.848 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 66 | | matches | (empty) | | ratio | 0 | |
| 90.59% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 41 | | technicalSentenceCount | 3 | | matches | | 0 | "Quinn watched as Eva examined the corpse's hands, noting the peculiar gray discoloration that seemed to emanate from beneath the nails." | | 1 | "But now, standing in this abandoned station with three bodies and a pattern that refused to make sense, Quinn felt the first real crack in her carefully constru…" | | 2 | "The compass needle twitched in Quinn's hand, spinning faster now, as if responding to their conversation." |
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| 19.74% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 19 | | uselessAdditionCount | 4 | | matches | | 0 | "Quinn kept, though her jaw tightened" | | 1 | "Quinn said, though her stomach tightened at the confirmation" | | 2 | "Quinn corrected, though her voice lacked its usual certainty" | | 3 | "Quinn said, her voice hardening with purpose" |
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| 95.95% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 12 | | fancyCount | 2 | | fancyTags | | 0 | "Eva breathed (breathe)" | | 1 | "Quinn corrected (correct)" |
| | dialogueSentences | 37 | | tagDensity | 0.324 | | leniency | 0.649 | | rawRatio | 0.167 | | effectiveRatio | 0.108 | |