| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 13 | | adverbTagCount | 2 | | adverbTags | | 0 | "he said finally [finally]" | | 1 | "He leaned back [back]" |
| | dialogueSentences | 73 | | tagDensity | 0.178 | | leniency | 0.356 | | rawRatio | 0.154 | | effectiveRatio | 0.055 | |
| 87.60% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1613 | | totalAiIsmAdverbs | 4 | | found | | | highlights | | 0 | "carefully" | | 1 | "slowly" | | 2 | "slightly" |
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| 100.00% | AI-ism character names | Target: 0 AI-default names (16 tracked, −20% each) | | codexExemptions | | | found | (empty) | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 69.00% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1613 | | totalAiIsms | 10 | | found | | | highlights | | 0 | "tracing" | | 1 | "weight" | | 2 | "warmth" | | 3 | "charged" | | 4 | "pulsed" | | 5 | "unreadable" | | 6 | "eyebrow" | | 7 | "flickered" |
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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 | 140 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 2 | | narrationSentences | 140 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 197 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 37 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 12 | | markdownWords | 23 | | totalWords | 1606 | | ratio | 0.014 | | matches | | 0 | "thud" | | 1 | "Si" | | 2 | "I don’t get paid enough for this" | | 3 | "don’t" | | 4 | "Encouraged" | | 5 | "Private" | | 6 | "had" | | 7 | "my" | | 8 | "Uncle Si" | | 9 | "you" | | 10 | "Of course." | | 11 | "I need a gun." |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 16 | | unquotedAttributions | 0 | | matches | (empty) | |
| 66.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 63 | | wordCount | 1277 | | uniqueNames | 19 | | maxNameDensity | 1.57 | | worstName | "Rory" | | maxWindowNameDensity | 3 | | worstWindowName | "Rory" | | discoveredNames | | Rory | 20 | | Rorschach | 1 | | Blackwood | 2 | | Silas | 16 | | Old | 1 | | Raven | 1 | | Nest | 1 | | Laila | 1 | | Cardiff | 2 | | London | 2 | | Evan | 1 | | Embassy | 2 | | Russian | 1 | | Kensington | 1 | | Palace | 1 | | Gardens | 1 | | Eva | 3 | | Didn | 3 | | Like | 3 |
| | persons | | 0 | "Rory" | | 1 | "Blackwood" | | 2 | "Silas" | | 3 | "Raven" | | 4 | "Nest" | | 5 | "Laila" | | 6 | "Evan" | | 7 | "Eva" | | 8 | "Like" |
| | places | | 0 | "Cardiff" | | 1 | "London" | | 2 | "Kensington" | | 3 | "Palace" | | 4 | "Gardens" |
| | globalScore | 0.717 | | windowScore | 0.667 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 83 | | glossingSentenceCount | 1 | | matches | | 0 | "quite anger, wasn’t quite nostalgia" | | 1 | "quite nostalgia" |
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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 | 1606 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 197 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 84 | | mean | 19.12 | | std | 16.71 | | cv | 0.874 | | sampleLengths | | 0 | 69 | | 1 | 7 | | 2 | 66 | | 3 | 73 | | 4 | 15 | | 5 | 20 | | 6 | 27 | | 7 | 44 | | 8 | 34 | | 9 | 46 | | 10 | 59 | | 11 | 7 | | 12 | 4 | | 13 | 1 | | 14 | 1 | | 15 | 25 | | 16 | 31 | | 17 | 24 | | 18 | 1 | | 19 | 5 | | 20 | 51 | | 21 | 6 | | 22 | 17 | | 23 | 3 | | 24 | 17 | | 25 | 24 | | 26 | 19 | | 27 | 11 | | 28 | 3 | | 29 | 31 | | 30 | 11 | | 31 | 52 | | 32 | 4 | | 33 | 3 | | 34 | 1 | | 35 | 10 | | 36 | 10 | | 37 | 4 | | 38 | 2 | | 39 | 27 | | 40 | 2 | | 41 | 3 | | 42 | 21 | | 43 | 21 | | 44 | 9 | | 45 | 5 | | 46 | 7 | | 47 | 9 | | 48 | 17 | | 49 | 35 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 140 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 3 | | totalVerbs | 236 | | matches | | 0 | "were pretending" | | 1 | "was choosing" | | 2 | "wasn’t leaving" |
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| 70.34% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 6 | | semicolonCount | 0 | | flaggedSentences | 5 | | totalSentences | 197 | | ratio | 0.025 | | matches | | 0 | "Just watched the whiskey bleed into the grain, her thumb tracing the crescent scar on her wrist—old habit, older than the drink she’d just sacrificed." | | 1 | "It was the eyes—hazel, same as always, but heavier now, like they’d seen too much and decided to keep it all." | | 2 | "The bartender—some kid with a nose ring and a look that said *I don’t get paid enough for this*—slid her a fresh glass without a word." | | 3 | "The Raven’s Nest hummed around them—low murmurs, the clink of glasses, the occasional burst of laughter from the corner where a group of suits were pretending to be interesting." | | 4 | "The London air hit her like a slap—cold, damp, smelling of rain and exhaust." |
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| 92.68% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1282 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 62 | | adverbRatio | 0.0483619344773791 | | lyAdverbCount | 10 | | lyAdverbRatio | 0.0078003120124804995 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 197 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 197 | | mean | 8.15 | | std | 6.61 | | cv | 0.811 | | sampleLengths | | 0 | 15 | | 1 | 24 | | 2 | 3 | | 3 | 2 | | 4 | 25 | | 5 | 7 | | 6 | 19 | | 7 | 26 | | 8 | 2 | | 9 | 19 | | 10 | 3 | | 11 | 24 | | 12 | 21 | | 13 | 16 | | 14 | 3 | | 15 | 6 | | 16 | 15 | | 17 | 12 | | 18 | 2 | | 19 | 6 | | 20 | 8 | | 21 | 14 | | 22 | 5 | | 23 | 9 | | 24 | 26 | | 25 | 4 | | 26 | 5 | | 27 | 17 | | 28 | 8 | | 29 | 9 | | 30 | 2 | | 31 | 13 | | 32 | 9 | | 33 | 16 | | 34 | 6 | | 35 | 5 | | 36 | 29 | | 37 | 15 | | 38 | 10 | | 39 | 7 | | 40 | 4 | | 41 | 1 | | 42 | 1 | | 43 | 14 | | 44 | 9 | | 45 | 2 | | 46 | 4 | | 47 | 9 | | 48 | 1 | | 49 | 6 |
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| 52.96% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 9 | | diversityRatio | 0.34517766497461927 | | totalSentences | 197 | | uniqueOpeners | 68 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 9 | | totalSentences | 125 | | matches | | 0 | "Just watched the whiskey bleed" | | 1 | "Of course she had." | | 2 | "Just sat there, solid as" | | 3 | "*Of course.* The Russian Embassy" | | 4 | "Instead, she picked up her" | | 5 | "Then, slowly, he wiped his" | | 6 | "Then he was gone." | | 7 | "Somewhere, a dog barked." | | 8 | "Then she deleted the message" |
| | ratio | 0.072 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 37 | | totalSentences | 125 | | matches | | 0 | "It hit the bar with" | | 1 | "She didn’t flinch." | | 2 | "He looked different." | | 3 | "It was the eyes—hazel, same" | | 4 | "He said her name like" | | 5 | "she corrected, though she hadn’t" | | 6 | "He took a sip, watching" | | 7 | "She reached for a napkin," | | 8 | "He gestured to the stool" | | 9 | "She pulled out the stool," | | 10 | "he said finally" | | 11 | "He tapped his left knee" | | 12 | "He nodded toward the back," | | 13 | "She *had* known, once." | | 14 | "She took a sip, let" | | 15 | "She matched his stare" | | 16 | "He chuckled, low and rough." | | 17 | "He leaned in, just enough" | | 18 | "She downed the rest of" | | 19 | "It came out bitter, cracked." |
| | ratio | 0.296 | |
| 68.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 98 | | totalSentences | 125 | | matches | | 0 | "The glass slipped through Rory’s" | | 1 | "It hit the bar with" | | 2 | "She didn’t flinch." | | 3 | "The voice came from her" | | 4 | "Rory turned, and there he" | | 5 | "He looked different." | | 6 | "It was the eyes—hazel, same" | | 7 | "The limp was new too," | | 8 | "A souvenir, probably." | | 9 | "Men like Silas didn’t collect" | | 10 | "He said her name like" | | 11 | "she corrected, though she hadn’t" | | 12 | "A ghost of a smile" | | 13 | "He took a sip, watching" | | 14 | "She reached for a napkin," | | 15 | "The bartender—some kid with a" | | 16 | "Rory nodded her thanks." | | 17 | "Silas exhaled through his nose," | | 18 | "He gestured to the stool" | | 19 | "The smart move would’ve been" |
| | ratio | 0.784 | |
| 80.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 125 | | matches | | 0 | "Before the bruises that didn’t" | | 1 | "Before she’d learned the difference" |
| | ratio | 0.016 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 46 | | technicalSentenceCount | 2 | | matches | | 0 | "The bartender—some kid with a nose ring and a look that said *I don’t get paid enough for this*—slid her a fresh glass without a word." | | 1 | "The kind that meant he was choosing his words carefully, the way you’d defuse a bomb." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 13 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 5 | | fancyCount | 2 | | fancyTags | | 0 | "she corrected (correct)" | | 1 | "he murmured (murmur)" |
| | dialogueSentences | 73 | | tagDensity | 0.068 | | leniency | 0.137 | | rawRatio | 0.4 | | effectiveRatio | 0.055 | |