| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 17 | | adverbTagCount | 2 | | adverbTags | | 0 | "He leaned back [back]" | | 1 | "he said again [again]" |
| | dialogueSentences | 57 | | tagDensity | 0.298 | | leniency | 0.596 | | rawRatio | 0.118 | | effectiveRatio | 0.07 | |
| 91.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1111 | | totalAiIsmAdverbs | 2 | | found | | | highlights | | |
| 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) | |
| 68.50% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1111 | | totalAiIsms | 7 | | found | | | highlights | | 0 | "silence" | | 1 | "unreadable" | | 2 | "weight" | | 3 | "familiar" | | 4 | "traced" | | 5 | "aftermath" |
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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 | 102 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 2 | | narrationSentences | 102 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 140 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 32 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 4 | | markdownWords | 33 | | totalWords | 1101 | | ratio | 0.03 | | matches | | 0 | "don’t stare at the girl who just dropped a drink at midnight" | | 1 | "Leg’s gone to hell. Won’t be fieldwork again." | | 2 | "You’re not cut out for this, Rory. Stick to what you know." | | 3 | "he" |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 14 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 28 | | wordCount | 889 | | uniqueNames | 12 | | maxNameDensity | 0.79 | | worstName | "Silas" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Nest" | | discoveredNames | | Rory | 2 | | Raven | 2 | | Nest | 5 | | Silas | 7 | | Prague | 1 | | Cardiff | 2 | | Evan | 2 | | Spymaster | 1 | | Didn | 1 | | Honest | 1 | | Final | 1 | | Wanted | 3 |
| | persons | | 0 | "Rory" | | 1 | "Raven" | | 2 | "Nest" | | 3 | "Silas" | | 4 | "Evan" |
| | places | | | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 60 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1101 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 140 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 62 | | mean | 17.76 | | std | 15.39 | | cv | 0.867 | | sampleLengths | | 0 | 65 | | 1 | 36 | | 2 | 3 | | 3 | 25 | | 4 | 27 | | 5 | 22 | | 6 | 38 | | 7 | 6 | | 8 | 24 | | 9 | 56 | | 10 | 10 | | 11 | 5 | | 12 | 7 | | 13 | 1 | | 14 | 1 | | 15 | 16 | | 16 | 25 | | 17 | 46 | | 18 | 7 | | 19 | 1 | | 20 | 1 | | 21 | 1 | | 22 | 2 | | 23 | 20 | | 24 | 6 | | 25 | 1 | | 26 | 11 | | 27 | 5 | | 28 | 22 | | 29 | 28 | | 30 | 12 | | 31 | 41 | | 32 | 24 | | 33 | 29 | | 34 | 3 | | 35 | 3 | | 36 | 9 | | 37 | 35 | | 38 | 6 | | 39 | 12 | | 40 | 16 | | 41 | 12 | | 42 | 44 | | 43 | 13 | | 44 | 10 | | 45 | 11 | | 46 | 38 | | 47 | 8 | | 48 | 1 | | 49 | 2 |
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| 98.38% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 102 | | matches | | 0 | "was gone" | | 1 | "been called" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 169 | | matches | (empty) | |
| 61.22% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 5 | | semicolonCount | 0 | | flaggedSentences | 4 | | totalSentences | 140 | | ratio | 0.029 | | matches | | 0 | "Every head turned—then quickly looked away." | | 1 | "She remembered the phone call—static, his voice tight with pain." | | 2 | "Wanted to tell him he didn’t know her anymore, that the girl he’d known—the one who’d sat at this very bar, listening to his stories like they were gospel—was gone." | | 3 | "She remembered the stories—how he’d been called the Spymaster, how he’d run agents in and out of places most people couldn’t find on a map." |
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| 98.95% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 898 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 37 | | adverbRatio | 0.04120267260579064 | | lyAdverbCount | 1 | | lyAdverbRatio | 0.0011135857461024498 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 140 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 140 | | mean | 7.86 | | std | 6.26 | | cv | 0.796 | | sampleLengths | | 0 | 11 | | 1 | 27 | | 2 | 6 | | 3 | 21 | | 4 | 6 | | 5 | 15 | | 6 | 15 | | 7 | 3 | | 8 | 11 | | 9 | 13 | | 10 | 1 | | 11 | 2 | | 12 | 14 | | 13 | 9 | | 14 | 2 | | 15 | 2 | | 16 | 15 | | 17 | 4 | | 18 | 1 | | 19 | 15 | | 20 | 9 | | 21 | 14 | | 22 | 6 | | 23 | 20 | | 24 | 4 | | 25 | 1 | | 26 | 8 | | 27 | 10 | | 28 | 4 | | 29 | 21 | | 30 | 7 | | 31 | 5 | | 32 | 5 | | 33 | 5 | | 34 | 5 | | 35 | 5 | | 36 | 2 | | 37 | 1 | | 38 | 1 | | 39 | 9 | | 40 | 7 | | 41 | 9 | | 42 | 13 | | 43 | 3 | | 44 | 5 | | 45 | 4 | | 46 | 9 | | 47 | 28 | | 48 | 7 | | 49 | 1 |
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| 67.62% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 2 | | diversityRatio | 0.4142857142857143 | | totalSentences | 140 | | uniqueOpeners | 58 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 4 | | totalSentences | 84 | | matches | | 0 | "Then Silas set his glass" | | 1 | "Then, because she owed him" | | 2 | "Instead, she said," | | 3 | "Instead, she reached for her" |
| | ratio | 0.048 | |
| 43.81% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 37 | | totalSentences | 84 | | matches | | 0 | "He just watched her, fingers" | | 1 | "She wiped her palm on" | | 2 | "She hadn’t felt it." | | 3 | "He reached under the bar," | | 4 | "She caught it one-handed, pressed" | | 5 | "He gestured to the shelves" | | 6 | "She remembered the phone call—static," | | 7 | "*You’re not cut out for" | | 8 | "She’d known what he meant." | | 9 | "She laughed, sharp and sudden." | | 10 | "He studied her, hazel eyes" | | 11 | "She set it on the" | | 12 | "He didn’t have to." | | 13 | "He’d taught her that, years" | | 14 | "His eyebrows lifted." | | 15 | "He leaned back, the stool" | | 16 | "She looked away, at the" | | 17 | "His voice was quiet" | | 18 | "She wanted to argue." | | 19 | "She set the glass down," |
| | ratio | 0.44 | |
| 85.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 63 | | totalSentences | 84 | | matches | | 0 | "The glass slipped from Rory’s" | | 1 | "Whisky sloshed across the bar," | | 2 | "Every head turned—then quickly looked" | | 3 | "The Nest had rules, and" | | 4 | "Silas didn’t move from his" | | 5 | "He just watched her, fingers" | | 6 | "The signet ring on his" | | 7 | "She wiped her palm on" | | 8 | "The crescent scar on her" | | 9 | "The kind that stretched too" | | 10 | "A thin line of red" | | 11 | "She hadn’t felt it." | | 12 | "He reached under the bar," | | 13 | "She caught it one-handed, pressed" | | 14 | "The fabric smelled of lemon" | | 15 | "He gestured to the shelves" | | 16 | "The word settled between them" | | 17 | "She remembered the phone call—static," | | 18 | "*Leg’s gone to hell." | | 19 | "*You’re not cut out for" |
| | ratio | 0.75 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 84 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 37 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 66.18% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 17 | | uselessAdditionCount | 2 | | matches | | 0 | "He leaned back, the stool creaking under his weight" | | 1 | "Silas asked, as if he’d read her mind" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 9 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 57 | | tagDensity | 0.158 | | leniency | 0.316 | | rawRatio | 0 | | effectiveRatio | 0 | |