| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 15 | | adverbTagCount | 1 | | adverbTags | | 0 | "She wondered aloud [aloud]" |
| | dialogueSentences | 32 | | tagDensity | 0.469 | | leniency | 0.938 | | rawRatio | 0.067 | | effectiveRatio | 0.063 | |
| 75.06% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1203 | | totalAiIsmAdverbs | 6 | | found | | | highlights | | 0 | "suddenly" | | 1 | "really" | | 2 | "very" |
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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) | |
| 29.34% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1203 | | totalAiIsms | 17 | | found | | | highlights | | 0 | "pumping" | | 1 | "pounding" | | 2 | "searing" | | 3 | "raced" | | 4 | "footsteps" | | 5 | "beacon" | | 6 | "dancing" | | 7 | "stomach" | | 8 | "familiar" | | 9 | "could feel" | | 10 | "warmth" | | 11 | "weight" | | 12 | "furrowed" | | 13 | "steeled" |
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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 | "flicker of emotion" | | count | 1 |
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| | highlights | | 0 | "eyes widened" | | 1 | "a flash of fear" |
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| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 82 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 82 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 97 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 35 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1206 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 13 | | unquotedAttributions | 0 | | matches | (empty) | |
| 16.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 51 | | wordCount | 901 | | uniqueNames | 10 | | maxNameDensity | 2.55 | | worstName | "Tomás" | | maxWindowNameDensity | 4.5 | | worstWindowName | "Tomás" | | discoveredNames | | Harlow | 5 | | Tomás | 23 | | Detective | 4 | | Quinn | 9 | | Veil | 2 | | Market | 2 | | Raven | 2 | | Nest | 2 | | Theondon | 1 | | Carrie | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Tomás" | | 2 | "Detective" | | 3 | "Quinn" | | 4 | "Raven" | | 5 | "Nest" | | 6 | "Carrie" |
| | places | | | globalScore | 0.224 | | windowScore | 0.167 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 69 | | glossingSentenceCount | 1 | | matches | | 0 | "as if expecting a threat to jump out 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 | 1206 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 97 | | matches | (empty) | |
| 92.15% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 43 | | mean | 28.05 | | std | 13.25 | | cv | 0.473 | | sampleLengths | | 0 | 29 | | 1 | 37 | | 2 | 26 | | 3 | 16 | | 4 | 8 | | 5 | 35 | | 6 | 39 | | 7 | 19 | | 8 | 25 | | 9 | 15 | | 10 | 19 | | 11 | 39 | | 12 | 28 | | 13 | 19 | | 14 | 13 | | 15 | 21 | | 16 | 40 | | 17 | 23 | | 18 | 28 | | 19 | 46 | | 20 | 21 | | 21 | 9 | | 22 | 25 | | 23 | 18 | | 24 | 25 | | 25 | 9 | | 26 | 32 | | 27 | 62 | | 28 | 61 | | 29 | 37 | | 30 | 38 | | 31 | 28 | | 32 | 45 | | 33 | 23 | | 34 | 40 | | 35 | 20 | | 36 | 15 | | 37 | 27 | | 38 | 36 | | 39 | 18 | | 40 | 46 | | 41 | 2 | | 42 | 44 |
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| 88.15% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 4 | | totalSentences | 82 | | matches | | 0 | "was gone" | | 1 | "was dragged" | | 2 | "was deserted" | | 3 | "was lit" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 175 | | matches | | |
| 83.95% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 2 | | semicolonCount | 0 | | flaggedSentences | 2 | | totalSentences | 97 | | ratio | 0.021 | | matches | | 0 | "He knew these passageways like the back of his hand - he'd seen it all." | | 1 | "Tomás pressed on, ducking and weaving through the throng of creatures on all sides - fantastical beings who would have once stayed, rattled his stomach." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 592 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 15 | | adverbRatio | 0.02533783783783784 | | lyAdverbCount | 6 | | lyAdverbRatio | 0.010135135135135136 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 97 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 97 | | mean | 12.43 | | std | 7.08 | | cv | 0.57 | | sampleLengths | | 0 | 16 | | 1 | 13 | | 2 | 17 | | 3 | 7 | | 4 | 13 | | 5 | 26 | | 6 | 10 | | 7 | 6 | | 8 | 8 | | 9 | 7 | | 10 | 13 | | 11 | 15 | | 12 | 11 | | 13 | 14 | | 14 | 14 | | 15 | 4 | | 16 | 8 | | 17 | 7 | | 18 | 9 | | 19 | 16 | | 20 | 7 | | 21 | 8 | | 22 | 9 | | 23 | 10 | | 24 | 21 | | 25 | 15 | | 26 | 3 | | 27 | 16 | | 28 | 12 | | 29 | 19 | | 30 | 6 | | 31 | 7 | | 32 | 10 | | 33 | 11 | | 34 | 16 | | 35 | 24 | | 36 | 23 | | 37 | 19 | | 38 | 9 | | 39 | 17 | | 40 | 16 | | 41 | 13 | | 42 | 10 | | 43 | 11 | | 44 | 9 | | 45 | 25 | | 46 | 12 | | 47 | 6 | | 48 | 25 | | 49 | 9 |
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| 69.07% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 3 | | diversityRatio | 0.4329896907216495 | | totalSentences | 97 | | uniqueOpeners | 42 | |
| 86.58% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 77 | | matches | | 0 | "Blearily, she looked around." | | 1 | "Suddenly, a hand clamped over" |
| | ratio | 0.026 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 21 | | totalSentences | 77 | | matches | | 0 | "She didn't slow her pace," | | 1 | "She burst onto the next" | | 2 | "They'd reached a dead end," | | 3 | "she called over the pounding" | | 4 | "His gaze suddenly widened and" | | 5 | "She stumbled and fell to" | | 6 | "Her head cracked against the" | | 7 | "She reached up and felt" | | 8 | "She smelled alcohol, unmarrried chocolate," | | 9 | "He knew these passageways like" | | 10 | "He spun around to see" | | 11 | "He spun around, his heart" | | 12 | "She wondered aloud" | | 13 | "He'd never wanted to see" | | 14 | "She glanced around the market," | | 15 | "He could feel the warmth" | | 16 | "She took a step back," | | 17 | "We've got to shut it" | | 18 | "It's all tied up with" | | 19 | "I was thinking the same" |
| | ratio | 0.273 | |
| 24.94% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 67 | | totalSentences | 77 | | matches | | 0 | "The rain pounded on the" | | 1 | "She didn't slow her pace," | | 2 | "There, a flash of dark" | | 3 | "Harlow cursed under her breath," | | 4 | "She burst onto the next" | | 5 | "They'd reached a dead end," | | 6 | "Tomás's eyes darted left and" | | 7 | "Harlow closed in, perspiring, weapon" | | 8 | "she called over the pounding" | | 9 | "Tomás held up his hands," | | 10 | "His gaze suddenly widened and" | | 11 | "Harlow cursed and followed, looking" | | 12 | "She stumbled and fell to" | | 13 | "Her head cracked against the" | | 14 | "She reached up and felt" | | 15 | "The alley yawned before her," | | 16 | "Tomàs was gone, vanished into" | | 17 | "Harlow tried to stand, but" | | 18 | "She smelled alcohol, unmarrried chocolate," | | 19 | "a deep voice growled in" |
| | ratio | 0.87 | |
| 64.94% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 77 | | matches | | 0 | "Before she could protest, she" |
| | ratio | 0.013 | |
| 89.29% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 40 | | technicalSentenceCount | 3 | | matches | | 0 | "Tomás stumbled down the stairs, his hand gripping the banister for support, his leg aching from the long chase." | | 1 | "Tomás pressed on, ducking and weaving through the throng of creatures on all sides - fantastical beings who would have once stayed, rattled his stomach." | | 2 | "Quinn recoiled as if stung, twisting her arm from Tomás's grip." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 14 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 7 | | fancyCount | 6 | | fancyTags | | 0 | "a deep voice growled (growl)" | | 1 | "Tomás panted (pant)" | | 2 | "he spat (spit)" | | 3 | "the creature snarled (snarl)" | | 4 | "Tomás retorted (retort)" | | 5 | "Tomás protested (protest)" |
| | dialogueSentences | 32 | | tagDensity | 0.219 | | leniency | 0.438 | | rawRatio | 0.857 | | effectiveRatio | 0.375 | |