| 94.74% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 16 | | adverbTagCount | 2 | | adverbTags | | 0 | "She crouched again [again]" | | 1 | "Quinn looked again [again]" |
| | dialogueSentences | 38 | | tagDensity | 0.421 | | leniency | 0.842 | | rawRatio | 0.125 | | effectiveRatio | 0.105 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1164 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 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) | |
| 74.23% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1164 | | totalAiIsms | 6 | | found | | | highlights | | 0 | "weight" | | 1 | "pulse" | | 2 | "quickened" | | 3 | "chill" | | 4 | "perfect" |
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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 | 76 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 76 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 98 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 40 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1157 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 14 | | unquotedAttributions | 0 | | matches | (empty) | |
| 66.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 23 | | wordCount | 772 | | uniqueNames | 5 | | maxNameDensity | 1.55 | | worstName | "Bell" | | maxWindowNameDensity | 3 | | worstWindowName | "Bell" | | discoveredNames | | Tube | 1 | | Quinn | 7 | | Camden | 2 | | Bell | 12 | | Morris | 1 |
| | persons | | | places | (empty) | | globalScore | 0.723 | | windowScore | 0.667 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 54 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.864 | | wordCount | 1157 | | matches | | 0 | "not been down yet, but there's no wound" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 98 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 41 | | mean | 28.22 | | std | 19.27 | | cv | 0.683 | | sampleLengths | | 0 | 45 | | 1 | 19 | | 2 | 30 | | 3 | 5 | | 4 | 46 | | 5 | 49 | | 6 | 11 | | 7 | 3 | | 8 | 33 | | 9 | 45 | | 10 | 2 | | 11 | 24 | | 12 | 18 | | 13 | 52 | | 14 | 18 | | 15 | 3 | | 16 | 44 | | 17 | 16 | | 18 | 8 | | 19 | 43 | | 20 | 37 | | 21 | 5 | | 22 | 40 | | 23 | 42 | | 24 | 84 | | 25 | 7 | | 26 | 67 | | 27 | 36 | | 28 | 3 | | 29 | 14 | | 30 | 54 | | 31 | 21 | | 32 | 21 | | 33 | 46 | | 34 | 16 | | 35 | 41 | | 36 | 33 | | 37 | 36 | | 38 | 4 | | 39 | 16 | | 40 | 20 |
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| 91.41% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 76 | | matches | | 0 | "were splayed" | | 1 | "been pulled" | | 2 | "been scoured" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 129 | | matches | (empty) | |
| 84.55% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 2 | | semicolonCount | 0 | | flaggedSentences | 2 | | totalSentences | 98 | | ratio | 0.02 | | matches | | 0 | "One belonged to the victim—she could trace where he'd walked the platform's length, paced it, even, the prints overlapping." | | 1 | "Bone—actual bone, carved with marks she didn't recognise, worn smooth at the edges as though handled often." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 777 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 18 | | adverbRatio | 0.023166023166023165 | | lyAdverbCount | 2 | | lyAdverbRatio | 0.002574002574002574 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 98 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 98 | | mean | 11.81 | | std | 7.78 | | cv | 0.659 | | sampleLengths | | 0 | 23 | | 1 | 22 | | 2 | 1 | | 3 | 5 | | 4 | 13 | | 5 | 19 | | 6 | 8 | | 7 | 3 | | 8 | 5 | | 9 | 14 | | 10 | 21 | | 11 | 11 | | 12 | 15 | | 13 | 14 | | 14 | 2 | | 15 | 6 | | 16 | 12 | | 17 | 11 | | 18 | 3 | | 19 | 14 | | 20 | 19 | | 21 | 11 | | 22 | 16 | | 23 | 10 | | 24 | 8 | | 25 | 2 | | 26 | 8 | | 27 | 16 | | 28 | 4 | | 29 | 14 | | 30 | 11 | | 31 | 13 | | 32 | 19 | | 33 | 9 | | 34 | 3 | | 35 | 15 | | 36 | 3 | | 37 | 29 | | 38 | 15 | | 39 | 16 | | 40 | 4 | | 41 | 4 | | 42 | 18 | | 43 | 15 | | 44 | 10 | | 45 | 2 | | 46 | 7 | | 47 | 11 | | 48 | 17 | | 49 | 5 |
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| 80.95% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 4 | | diversityRatio | 0.5102040816326531 | | totalSentences | 98 | | uniqueOpeners | 50 | |
| 49.02% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 68 | | matches | | 0 | "Of course it was Camden." |
| | ratio | 0.015 | |
| 78.82% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 24 | | totalSentences | 68 | | matches | | 0 | "She ducked under the tape" | | 1 | "He stopped, searching" | | 2 | "He led her along a" | | 3 | "Her torch beam caught the" | | 4 | "His arms were splayed, palms" | | 5 | "She studied the man's face" | | 6 | "She gestured at the frost" | | 7 | "She rose and walked the" | | 8 | "Her beam snagged on something" | | 9 | "She pulled an evidence glove" | | 10 | "She didn't tell him her" | | 11 | "She'd seen one of these" | | 12 | "She crouched again, close to" | | 13 | "She tilted her head" | | 14 | "She studied the advertisement above" | | 15 | "She pressed two gloved fingers" | | 16 | "He obliged, then snatched his" | | 17 | "She straightened, working it through" | | 18 | "she said, more to herself" | | 19 | "She didn't answer." |
| | ratio | 0.353 | |
| 40.88% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 57 | | totalSentences | 68 | | matches | | 0 | "The abandoned Tube station stank" | | 1 | "She ducked under the tape" | | 2 | "Every strange thing in this" | | 3 | "Sergeant Bell met her at" | | 4 | "He stopped, searching" | | 5 | "He led her along a" | | 6 | "Tiles had peeled from the" | | 7 | "Her torch beam caught the" | | 8 | "A man, mid-forties, slumped against" | | 9 | "His arms were splayed, palms" | | 10 | "That was the first thing" | | 11 | "A body in this posture," | | 12 | "Quinn crouched two feet from" | | 13 | "Bell crouched beside her, eager" | | 14 | "She studied the man's face" | | 15 | "The eyes were open, fixed" | | 16 | "Frost rimed his eyebrows and" | | 17 | "She gestured at the frost" | | 18 | "Bell rubbed his arms." | | 19 | "Quinn filed that away and" |
| | ratio | 0.838 | |
| 73.53% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 68 | | matches | | 0 | "As though something had opened" |
| | ratio | 0.015 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 32 | | technicalSentenceCount | 1 | | matches | | 0 | "The abandoned Tube station stank of standing water and something older, something that crawled up the back of Quinn's throat and lodged there." |
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| 62.50% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 16 | | uselessAdditionCount | 2 | | matches | | 0 | "Sergeant Bell met, his face the colour of wet chalk" | | 1 | "she said, more to herself than Bell" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 3 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 38 | | tagDensity | 0.079 | | leniency | 0.158 | | rawRatio | 0 | | effectiveRatio | 0 | |