| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 19 | | adverbTagCount | 2 | | adverbTags | | 0 | "His knuckles whitened around [around]" | | 1 | "His voice cracked just [just]" |
| | dialogueSentences | 78 | | tagDensity | 0.244 | | leniency | 0.487 | | rawRatio | 0.105 | | effectiveRatio | 0.051 | |
| 83.53% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1518 | | totalAiIsmAdverbs | 5 | | found | | | highlights | | 0 | "slightly" | | 1 | "really" | | 2 | "softly" |
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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) | |
| 50.59% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1518 | | totalAiIsms | 15 | | found | | | highlights | | 0 | "flickered" | | 1 | "glinting" | | 2 | "footsteps" | | 3 | "flicked" | | 4 | "unreadable" | | 5 | "weight" | | 6 | "silence" | | 7 | "etched" | | 8 | "charged" | | 9 | "stomach" | | 10 | "jaw clenched" | | 11 | "tension" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "jaw/fists clenched" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 117 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 117 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 177 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 29 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1514 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 17 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 29 | | wordCount | 1122 | | uniqueNames | 7 | | maxNameDensity | 0.8 | | worstName | "Rory" | | maxWindowNameDensity | 2 | | worstWindowName | "Evan" | | discoveredNames | | Raven | 1 | | Nest | 1 | | Rory | 9 | | Silas | 7 | | Evan | 9 | | London | 1 | | Spymaster | 1 |
| | persons | | 0 | "Raven" | | 1 | "Nest" | | 2 | "Rory" | | 3 | "Silas" | | 4 | "Evan" |
| | places | | | globalScore | 1 | | windowScore | 1 | |
| 57.41% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 81 | | glossingSentenceCount | 3 | | matches | | 0 | "not quite a smile" | | 1 | "quite spit out" | | 2 | "as if surfacing from deep water" |
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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 | 1514 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 177 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 82 | | mean | 18.46 | | std | 13.03 | | cv | 0.706 | | sampleLengths | | 0 | 74 | | 1 | 39 | | 2 | 13 | | 3 | 14 | | 4 | 26 | | 5 | 18 | | 6 | 9 | | 7 | 35 | | 8 | 15 | | 9 | 2 | | 10 | 36 | | 11 | 1 | | 12 | 19 | | 13 | 30 | | 14 | 42 | | 15 | 8 | | 16 | 8 | | 17 | 12 | | 18 | 3 | | 19 | 31 | | 20 | 32 | | 21 | 3 | | 22 | 12 | | 23 | 20 | | 24 | 15 | | 25 | 26 | | 26 | 12 | | 27 | 8 | | 28 | 2 | | 29 | 6 | | 30 | 18 | | 31 | 8 | | 32 | 27 | | 33 | 7 | | 34 | 34 | | 35 | 21 | | 36 | 2 | | 37 | 4 | | 38 | 46 | | 39 | 6 | | 40 | 1 | | 41 | 16 | | 42 | 3 | | 43 | 16 | | 44 | 23 | | 45 | 22 | | 46 | 26 | | 47 | 19 | | 48 | 3 | | 49 | 33 |
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| 99.27% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 117 | | matches | | 0 | "was threaded" | | 1 | "was gone" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 208 | | matches | | 0 | "was coming" | | 1 | "was stepping" |
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| 78.29% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 5 | | semicolonCount | 0 | | flaggedSentences | 4 | | totalSentences | 177 | | ratio | 0.023 | | matches | | 0 | "The bar smelled of aged wood and something sharper—whiskey, maybe, or the ghost of a thousand half-finished conversations." | | 1 | "Footsteps—hesitant, like someone testing the ground before committing to it." | | 2 | "But the eyes—bright, sharp, like a bird of prey’s—were the same." | | 3 | "But there was something else—something brittle, like a man who’d spent too long holding his breath." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 480 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 12 | | adverbRatio | 0.025 | | lyAdverbCount | 1 | | lyAdverbRatio | 0.0020833333333333333 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 177 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 177 | | mean | 8.55 | | std | 5.81 | | cv | 0.679 | | sampleLengths | | 0 | 25 | | 1 | 18 | | 2 | 13 | | 3 | 18 | | 4 | 18 | | 5 | 21 | | 6 | 11 | | 7 | 2 | | 8 | 10 | | 9 | 4 | | 10 | 18 | | 11 | 8 | | 12 | 15 | | 13 | 3 | | 14 | 7 | | 15 | 2 | | 16 | 12 | | 17 | 13 | | 18 | 10 | | 19 | 7 | | 20 | 8 | | 21 | 2 | | 22 | 21 | | 23 | 11 | | 24 | 4 | | 25 | 1 | | 26 | 10 | | 27 | 8 | | 28 | 1 | | 29 | 8 | | 30 | 22 | | 31 | 6 | | 32 | 23 | | 33 | 13 | | 34 | 8 | | 35 | 8 | | 36 | 8 | | 37 | 4 | | 38 | 3 | | 39 | 7 | | 40 | 24 | | 41 | 10 | | 42 | 6 | | 43 | 16 | | 44 | 3 | | 45 | 5 | | 46 | 7 | | 47 | 15 | | 48 | 5 | | 49 | 12 |
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| 49.72% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 7 | | diversityRatio | 0.3220338983050847 | | totalSentences | 177 | | uniqueOpeners | 57 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 5 | | totalSentences | 108 | | matches | | 0 | "Then his mouth twisted, not" | | 1 | "Instead, she said," | | 2 | "Then he was gone, the" | | 3 | "Of course he did." | | 4 | "Always watching, always listening." |
| | ratio | 0.046 | |
| 38.52% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 49 | | totalSentences | 108 | | matches | | 0 | "She shook rain from her" | | 1 | "He gave a slow nod," | | 2 | "She slid onto a stool," | | 3 | "He set the glass down," | | 4 | "She tapped her fingers against" | | 5 | "She exhaled through her nose," | | 6 | "She’d know them anywhere." | | 7 | "He froze, as if the" | | 8 | "He reached for a bottle," | | 9 | "His hair, once dark as" | | 10 | "He glanced at Silas, then" | | 11 | "He limped toward the far" | | 12 | "He trailed off, as if" | | 13 | "She took a sip of" | | 14 | "He rubbed his thumb along" | | 15 | "She nodded, as if that" | | 16 | "He exhaled, long and slow." | | 17 | "Her fingers tightened around the" | | 18 | "She didn’t look at him" | | 19 | "She took another drink, the" |
| | ratio | 0.454 | |
| 52.59% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 88 | | totalSentences | 108 | | matches | | 0 | "The green neon sign of" | | 1 | "The bar smelled of aged" | | 2 | "She shook rain from her" | | 3 | "The place was near empty," | | 4 | "Silas looked up from polishing" | | 5 | "He gave a slow nod," | | 6 | "She slid onto a stool," | | 7 | "He set the glass down," | | 8 | "She tapped her fingers against" | | 9 | "Silas wiped his hands on" | | 10 | "She exhaled through her nose," | | 11 | "The door swung open again," | | 12 | "Rory didn’t turn, but the" | | 13 | "Footsteps—hesitant, like someone testing the" | | 14 | "a voice said, rough with" | | 15 | "The man in the doorway" | | 16 | "She’d know them anywhere." | | 17 | "He froze, as if the" | | 18 | "He reached for a bottle," | | 19 | "Evan stepped forward, shedding his" |
| | ratio | 0.815 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 3 | | totalSentences | 108 | | matches | | 0 | "As if it explained why" | | 1 | "As if he’d known, all" | | 2 | "To pretend none of it" |
| | ratio | 0.028 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 47 | | technicalSentenceCount | 2 | | matches | | 0 | "He gave a slow nod, the kind that said he’d been expecting her, though she’d never told him she was coming." | | 1 | "The years had carved him leaner, his once-broad shoulders now slightly stooped, as if the weight of something unseen pressed down on him." |
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| 46.05% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 19 | | uselessAdditionCount | 3 | | matches | | 0 | "He trailed, as if the words had dissolved before he could shape them" | | 1 | "She nodded, as if that explained everything" | | 2 | "she said, quiet" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 5 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 78 | | tagDensity | 0.064 | | leniency | 0.128 | | rawRatio | 0 | | effectiveRatio | 0 | |