| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 10 | | adverbTagCount | 1 | | adverbTags | | 0 | "He glanced back [back]" |
| | dialogueSentences | 23 | | tagDensity | 0.435 | | leniency | 0.87 | | rawRatio | 0.1 | | effectiveRatio | 0.087 | |
| 90.88% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1097 | | totalAiIsmAdverbs | 2 | | found | | | highlights | | |
| 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) | |
| 81.77% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1097 | | totalAiIsms | 4 | | found | | | highlights | | 0 | "glinting" | | 1 | "scanned" | | 2 | "flickered" | | 3 | "pulsed" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "blood ran cold" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 111 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 111 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 124 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 36 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1097 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 10 | | unquotedAttributions | 0 | | matches | (empty) | |
| 90.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 17 | | wordCount | 927 | | uniqueNames | 7 | | maxNameDensity | 1.19 | | worstName | "Quinn" | | maxWindowNameDensity | 2 | | worstWindowName | "Quinn" | | discoveredNames | | Quinn | 11 | | Camden | 1 | | High | 1 | | Street | 1 | | Underground | 1 | | Morris | 1 | | London | 1 |
| | persons | | | places | | 0 | "Camden" | | 1 | "High" | | 2 | "Street" | | 3 | "London" |
| | globalScore | 0.907 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 57 | | glossingSentenceCount | 1 | | matches | | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1097 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 124 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 46 | | mean | 23.85 | | std | 21.14 | | cv | 0.886 | | sampleLengths | | 0 | 9 | | 1 | 36 | | 2 | 2 | | 3 | 5 | | 4 | 42 | | 5 | 47 | | 6 | 5 | | 7 | 58 | | 8 | 17 | | 9 | 5 | | 10 | 8 | | 11 | 57 | | 12 | 8 | | 13 | 41 | | 14 | 8 | | 15 | 47 | | 16 | 61 | | 17 | 16 | | 18 | 9 | | 19 | 50 | | 20 | 6 | | 21 | 9 | | 22 | 79 | | 23 | 6 | | 24 | 41 | | 25 | 5 | | 26 | 48 | | 27 | 10 | | 28 | 5 | | 29 | 52 | | 30 | 21 | | 31 | 2 | | 32 | 26 | | 33 | 4 | | 34 | 60 | | 35 | 20 | | 36 | 11 | | 37 | 29 | | 38 | 3 | | 39 | 41 | | 40 | 6 | | 41 | 48 | | 42 | 4 | | 43 | 4 | | 44 | 11 | | 45 | 15 |
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| 95.78% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 111 | | matches | | 0 | "been pried" | | 1 | "been clocked" | | 2 | "was gone" |
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| 89.50% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 3 | | totalVerbs | 181 | | matches | | 0 | "wasn't fleeing" | | 1 | "was heading" | | 2 | "was watching" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 124 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 932 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 27 | | adverbRatio | 0.028969957081545063 | | lyAdverbCount | 1 | | lyAdverbRatio | 0.001072961373390558 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 124 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 124 | | mean | 8.85 | | std | 7.55 | | cv | 0.853 | | sampleLengths | | 0 | 9 | | 1 | 3 | | 2 | 3 | | 3 | 26 | | 4 | 4 | | 5 | 2 | | 6 | 2 | | 7 | 3 | | 8 | 11 | | 9 | 19 | | 10 | 6 | | 11 | 3 | | 12 | 3 | | 13 | 13 | | 14 | 4 | | 15 | 4 | | 16 | 5 | | 17 | 12 | | 18 | 4 | | 19 | 5 | | 20 | 5 | | 21 | 10 | | 22 | 18 | | 23 | 17 | | 24 | 13 | | 25 | 17 | | 26 | 5 | | 27 | 8 | | 28 | 12 | | 29 | 6 | | 30 | 13 | | 31 | 26 | | 32 | 8 | | 33 | 3 | | 34 | 9 | | 35 | 8 | | 36 | 21 | | 37 | 8 | | 38 | 13 | | 39 | 2 | | 40 | 8 | | 41 | 21 | | 42 | 3 | | 43 | 5 | | 44 | 21 | | 45 | 2 | | 46 | 5 | | 47 | 13 | | 48 | 2 | | 49 | 2 |
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| 68.82% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 13 | | diversityRatio | 0.47580645161290325 | | totalSentences | 124 | | uniqueOpeners | 59 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 93 | | matches | (empty) | | ratio | 0 | |
| 82.37% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 32 | | totalSentences | 93 | | matches | | 0 | "She'd expected it." | | 1 | "They always ran." | | 2 | "He didn't slow." | | 3 | "He kept glancing left, checking" | | 4 | "He wasn't fleeing blind." | | 5 | "He was heading somewhere specific." | | 6 | "She wanted to know where." | | 7 | "He ducked into an alley" | | 8 | "Her left wrist ached where" | | 9 | "He dropped over the other" | | 10 | "She reached the fence, hooked" | | 11 | "Her coat snagged at the" | | 12 | "She tore it free and" | | 13 | "It had closed decades ago," | | 14 | "She paused at the top" | | 15 | "He'd never come back up." | | 16 | "They'd found his torch, his" | | 17 | "She'd been holding position ever" | | 18 | "It carried smells that didn't" | | 19 | "Her torch beam caught tiled" |
| | ratio | 0.344 | |
| 46.02% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 77 | | totalSentences | 93 | | matches | | 0 | "The kid bolted the second" | | 1 | "She'd expected it." | | 2 | "They always ran." | | 3 | "Quinn went after him." | | 4 | "Nobody ever stopped." | | 5 | "Rain needled her face as" | | 6 | "The boy, eighteen at most," | | 7 | "A night bus screamed its" | | 8 | "He didn't slow." | | 9 | "Neither did Quinn." | | 10 | "Some panicked and zigzagged." | | 11 | "Some made for crowds." | | 12 | "This one had a destination." | | 13 | "He kept glancing left, checking" | | 14 | "He wasn't fleeing blind." | | 15 | "He was heading somewhere specific." | | 16 | "She wanted to know where." | | 17 | "He ducked into an alley" | | 18 | "Quinn followed, boots splashing through" | | 19 | "Her left wrist ached where" |
| | ratio | 0.828 | |
| 53.76% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 93 | | matches | | 0 | "Either way, not welcome." |
| | ratio | 0.011 | |
| 71.43% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 30 | | technicalSentenceCount | 3 | | matches | | 0 | "But this one moved like he'd done it before, vaulting the bin outside the kebab shop without breaking stride, his trainers slapping against the wet pavement." | | 1 | "It carried smells that didn't belong underground, woodsmoke and crushed herbs and something sweet that coated the back of her tongue like burnt sugar." | | 2 | "One vendor had set out jars that glowed faint green from within, and the liquid in them moved against the glass like it was watching her back." |
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| 75.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 10 | | uselessAdditionCount | 1 | | matches | | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 4 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 23 | | tagDensity | 0.174 | | leniency | 0.348 | | rawRatio | 0 | | effectiveRatio | 0 | |