| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 9 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 47 | | tagDensity | 0.191 | | leniency | 0.383 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 85.61% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1737 | | totalAiIsmAdverbs | 5 | | found | | | highlights | | 0 | "very" | | 1 | "sharply" | | 2 | "slowly" | | 3 | "quickly" |
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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) | |
| 48.19% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1737 | | totalAiIsms | 18 | | found | | | highlights | | 0 | "flickered" | | 1 | "echo" | | 2 | "maw" | | 3 | "footsteps" | | 4 | "flicker" | | 5 | "wavering" | | 6 | "scanning" | | 7 | "glinting" | | 8 | "flicked" | | 9 | "shimmered" | | 10 | "pulsed" | | 11 | "beacon" | | 12 | "racing" | | 13 | "whisper" |
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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 | 152 | | matches | (empty) | |
| 95.86% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 3 | | narrationSentences | 152 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 189 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 26 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1728 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 5 | | unquotedAttributions | 0 | | matches | (empty) | |
| 50.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 47 | | wordCount | 1458 | | uniqueNames | 10 | | maxNameDensity | 1.58 | | worstName | "Harlow" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Harlow" | | discoveredNames | | Harlow | 23 | | Quinn | 1 | | Veil | 1 | | Market | 1 | | Tomás | 14 | | Herrera | 1 | | Saint | 1 | | Christopher | 1 | | Raven | 2 | | Nest | 2 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Tomás" | | 3 | "Herrera" | | 4 | "Saint" | | 5 | "Christopher" | | 6 | "Raven" | | 7 | "Nest" |
| | places | | | globalScore | 0.711 | | windowScore | 0.5 | |
| 54.76% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 105 | | glossingSentenceCount | 4 | | matches | | 0 | "blade that seemed to drink in the light" | | 1 | "looked like preserved eyes in jars" | | 2 | "looked like they were made of bone" | | 3 | "as if expecting it to open at any moment" |
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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 | 1728 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 189 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 71 | | mean | 24.34 | | std | 18.29 | | cv | 0.752 | | sampleLengths | | 0 | 56 | | 1 | 57 | | 2 | 3 | | 3 | 50 | | 4 | 59 | | 5 | 53 | | 6 | 69 | | 7 | 51 | | 8 | 80 | | 9 | 23 | | 10 | 42 | | 11 | 8 | | 12 | 19 | | 13 | 8 | | 14 | 28 | | 15 | 14 | | 16 | 11 | | 17 | 46 | | 18 | 72 | | 19 | 3 | | 20 | 23 | | 21 | 16 | | 22 | 21 | | 23 | 2 | | 24 | 23 | | 25 | 43 | | 26 | 36 | | 27 | 35 | | 28 | 5 | | 29 | 7 | | 30 | 7 | | 31 | 13 | | 32 | 23 | | 33 | 22 | | 34 | 34 | | 35 | 14 | | 36 | 11 | | 37 | 20 | | 38 | 30 | | 39 | 15 | | 40 | 11 | | 41 | 39 | | 42 | 14 | | 43 | 53 | | 44 | 22 | | 45 | 31 | | 46 | 44 | | 47 | 8 | | 48 | 17 | | 49 | 3 |
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| 96.03% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 4 | | totalSentences | 152 | | matches | | 0 | "were made" | | 1 | "was gone" | | 2 | "being demanded" | | 3 | "was gone" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 247 | | matches | | 0 | "were pressing" | | 1 | "was already weaving" |
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| 21.92% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 9 | | semicolonCount | 0 | | flaggedSentences | 8 | | totalSentences | 189 | | ratio | 0.042 | | matches | | 0 | "Not into thin air—into the ground." | | 1 | "She’d heard whispers of it—an underground bazaar that moved with the full moon, a place where the city’s underbelly traded in things best left unseen." | | 2 | "The alley opened into a circular chamber, the walls lined with doors—dozens of them, each one a different style, a different age." | | 3 | "But this—this was different." | | 4 | "But the rational part of her—the part that had kept her alive this long—knew Tomás was right." | | 5 | "Harlow did feel it—the wrongness of that chamber, the way the air had pressed against her skin like a living thing." | | 6 | "But the door—the door was a line she wasn’t sure she could uncross." | | 7 | "But she knew one thing for certain—this wasn’t over." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1469 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 47 | | adverbRatio | 0.031994554118447927 | | lyAdverbCount | 8 | | lyAdverbRatio | 0.005445881552076242 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 189 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 189 | | mean | 9.14 | | std | 5.59 | | cv | 0.611 | | sampleLengths | | 0 | 21 | | 1 | 15 | | 2 | 20 | | 3 | 3 | | 4 | 2 | | 5 | 9 | | 6 | 16 | | 7 | 19 | | 8 | 8 | | 9 | 3 | | 10 | 6 | | 11 | 11 | | 12 | 9 | | 13 | 12 | | 14 | 12 | | 15 | 3 | | 16 | 25 | | 17 | 20 | | 18 | 11 | | 19 | 4 | | 20 | 13 | | 21 | 17 | | 22 | 10 | | 23 | 9 | | 24 | 13 | | 25 | 11 | | 26 | 3 | | 27 | 25 | | 28 | 17 | | 29 | 20 | | 30 | 18 | | 31 | 4 | | 32 | 9 | | 33 | 17 | | 34 | 9 | | 35 | 17 | | 36 | 20 | | 37 | 8 | | 38 | 9 | | 39 | 16 | | 40 | 7 | | 41 | 13 | | 42 | 2 | | 43 | 16 | | 44 | 11 | | 45 | 5 | | 46 | 3 | | 47 | 11 | | 48 | 8 | | 49 | 8 |
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| 38.89% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 21 | | diversityRatio | 0.2275132275132275 | | totalSentences | 189 | | uniqueOpeners | 43 | |
| 69.93% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 143 | | matches | | 0 | "Then he vanished." | | 1 | "Then he was gone, the" | | 2 | "Then he was gone, swallowed" |
| | ratio | 0.021 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 39 | | totalSentences | 143 | | matches | | 0 | "She’d lost count of the" | | 1 | "She could almost reach out" | | 2 | "She didn’t hesitate." | | 3 | "She wasn’t about to let" | | 4 | "She’d heard whispers of it—an" | | 5 | "She’d have to find another" | | 6 | "They knew better than to" | | 7 | "She lost sight of him" | | 8 | "His olive skin was slick" | | 9 | "His warm brown eyes flicked" | | 10 | "She didn’t wait for him" | | 11 | "It was black, the surface" | | 12 | "His voice was smooth, unhurried." | | 13 | "It grated against her nerves." | | 14 | "He chuckled, low and dry." | | 15 | "He gestured to the doors" | | 16 | "He reached into his coat." | | 17 | "He tossed the token into" | | 18 | "It spun, catching the light," | | 19 | "It was something else." |
| | ratio | 0.273 | |
| 15.94% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 127 | | totalSentences | 143 | | matches | | 0 | "The pavement spat rainwater into" | | 1 | "The suspect’s silhouette flickered under" | | 2 | "She’d lost count of the" | | 3 | "A left turn." | | 4 | "The streets narrowed, the buildings" | | 5 | "The suspect’s foot caught on" | | 6 | "Harlow closed the gap, her" | | 7 | "She could almost reach out" | | 8 | "A manhole cover clanged open," | | 9 | "Harlow skidded to a halt," | | 10 | "The hole yawned, a black" | | 11 | "A ladder descended into the" | | 12 | "She didn’t hesitate." | | 13 | "The rungs were cold, slick" | | 14 | "The scent of damp earth" | | 15 | "The manhole cover groaned shut" | | 16 | "A flicker of movement." | | 17 | "The suspect’s torch bobbed ahead," | | 18 | "The tunnel sloped downward, the" | | 19 | "Harlow’s fingers brushed the wall," |
| | ratio | 0.888 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 143 | | matches | (empty) | | ratio | 0 | |
| 68.23% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 67 | | technicalSentenceCount | 7 | | matches | | 0 | "Harlow closed the gap, her boots splashing through puddles that reflected the neon glow of a nearby pub sign." | | 1 | "The tunnel sloped downward, the air growing thicker, heavier, as if the city itself were pressing in." | | 2 | "She’d heard whispers of it—an underground bazaar that moved with the full moon, a place where the city’s underbelly traded in things best left unseen." | | 3 | "The suspect was already weaving through the crowd, his coat blending into the sea of dark clothing." | | 4 | "The air smelled of damp and something older, something that made the hairs on her arms stand up." | | 5 | "But the rational part of her—the part that had kept her alive this long—knew Tomás was right." | | 6 | "Harlow stood there, the rain soaking through her coat, her mind racing." |
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| 69.44% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 9 | | uselessAdditionCount | 1 | | matches | | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 3 | | fancyCount | 2 | | fancyTags | | 0 | "Harlow barked (bark)" | | 1 | "His voice (his voice)" |
| | dialogueSentences | 47 | | tagDensity | 0.064 | | leniency | 0.128 | | rawRatio | 0.667 | | effectiveRatio | 0.085 | |