| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 23 | | adverbTagCount | 2 | | adverbTags | | 0 | "Quinn said suddenly [suddenly]" | | 1 | "Eva said softly [softly]" |
| | dialogueSentences | 53 | | tagDensity | 0.434 | | leniency | 0.868 | | rawRatio | 0.087 | | effectiveRatio | 0.075 | |
| 66.24% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1185 | | totalAiIsmAdverbs | 8 | | found | | | highlights | | 0 | "slightly" | | 1 | "suddenly" | | 2 | "softly" | | 3 | "really" |
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| 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) | |
| 49.37% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1185 | | totalAiIsms | 12 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | word | "scratched his head" | | count | 1 |
| | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | |
| | highlights | | 0 | "traced" | | 1 | "measured" | | 2 | "eyebrow" | | 3 | "etched" | | 4 | "pawn" | | 5 | "scratched his head" | | 6 | "unreadable" | | 7 | "complex" | | 8 | "otherworldly" | | 9 | "familiar" | | 10 | "apprehension" | | 11 | "flickered" |
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| 66.67% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 2 | | maxInWindow | 2 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 2 |
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| | highlights | | 0 | "eyes widened" | | 1 | "eyes narrowed" |
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| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 67 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 1 | | narrationSentences | 67 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 96 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 34 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1181 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 18 | | unquotedAttributions | 0 | | matches | (empty) | |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 58 | | wordCount | 674 | | uniqueNames | 12 | | maxNameDensity | 3.41 | | worstName | "Quinn" | | maxWindowNameDensity | 5.5 | | worstWindowName | "Quinn" | | discoveredNames | | Harlow | 1 | | Quinn | 23 | | Tube | 1 | | Camden | 1 | | Sergeant | 1 | | Davies | 12 | | Veil | 2 | | Market | 1 | | Kowalski | 1 | | Eva | 13 | | Morris | 1 | | Compass | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Camden" | | 3 | "Sergeant" | | 4 | "Davies" | | 5 | "Kowalski" | | 6 | "Eva" | | 7 | "Morris" | | 8 | "Compass" |
| | places | | | globalScore | 0 | | windowScore | 0 | |
| 96.81% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 47 | | glossingSentenceCount | 1 | | matches | | 0 | "pattern that seemed to emanate from the heart" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.847 | | wordCount | 1181 | | matches | | 0 | "Not by whoever found the body, but during whatever happened here" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 96 | | matches | (empty) | |
| 85.40% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 53 | | mean | 22.28 | | std | 10 | | cv | 0.449 | | sampleLengths | | 0 | 47 | | 1 | 31 | | 2 | 20 | | 3 | 30 | | 4 | 25 | | 5 | 36 | | 6 | 9 | | 7 | 31 | | 8 | 34 | | 9 | 10 | | 10 | 27 | | 11 | 6 | | 12 | 43 | | 13 | 8 | | 14 | 21 | | 15 | 40 | | 16 | 21 | | 17 | 30 | | 18 | 20 | | 19 | 22 | | 20 | 19 | | 21 | 33 | | 22 | 12 | | 23 | 5 | | 24 | 30 | | 25 | 7 | | 26 | 21 | | 27 | 16 | | 28 | 17 | | 29 | 12 | | 30 | 12 | | 31 | 19 | | 32 | 33 | | 33 | 31 | | 34 | 15 | | 35 | 38 | | 36 | 21 | | 37 | 29 | | 38 | 20 | | 39 | 9 | | 40 | 17 | | 41 | 29 | | 42 | 19 | | 43 | 34 | | 44 | 15 | | 45 | 15 | | 46 | 27 | | 47 | 17 | | 48 | 22 | | 49 | 6 |
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| 89.55% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 67 | | matches | | 0 | "been positioned" | | 1 | "been knocked" | | 2 | "was thrown" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 131 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 1 | | semicolonCount | 0 | | flaggedSentences | 1 | | totalSentences | 96 | | ratio | 0.01 | | matches | | 0 | "The portal suddenly flickered, and a figure materialised in front of it - tall, dressed in dark robes, face obscured by shadows." |
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| 99.38% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 675 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 21 | | adverbRatio | 0.03111111111111111 | | lyAdverbCount | 14 | | lyAdverbRatio | 0.02074074074074074 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 96 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 96 | | mean | 12.3 | | std | 6.51 | | cv | 0.529 | | sampleLengths | | 0 | 26 | | 1 | 21 | | 2 | 17 | | 3 | 14 | | 4 | 11 | | 5 | 2 | | 6 | 7 | | 7 | 18 | | 8 | 12 | | 9 | 7 | | 10 | 18 | | 11 | 16 | | 12 | 20 | | 13 | 9 | | 14 | 12 | | 15 | 19 | | 16 | 34 | | 17 | 10 | | 18 | 18 | | 19 | 9 | | 20 | 4 | | 21 | 2 | | 22 | 23 | | 23 | 20 | | 24 | 2 | | 25 | 6 | | 26 | 7 | | 27 | 14 | | 28 | 11 | | 29 | 20 | | 30 | 9 | | 31 | 6 | | 32 | 15 | | 33 | 18 | | 34 | 12 | | 35 | 4 | | 36 | 16 | | 37 | 3 | | 38 | 19 | | 39 | 9 | | 40 | 10 | | 41 | 15 | | 42 | 18 | | 43 | 8 | | 44 | 4 | | 45 | 5 | | 46 | 14 | | 47 | 16 | | 48 | 3 | | 49 | 4 |
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| 84.03% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 1 | | diversityRatio | 0.5104166666666666 | | totalSentences | 96 | | uniqueOpeners | 49 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 62 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 7 | | totalSentences | 62 | | matches | | 0 | "She angled her head, the" | | 1 | "She tucked a stray lock" | | 2 | "She moved through the market," | | 3 | "She answered it, her expression" | | 4 | "She moved to a nearby" | | 5 | "She trailed off, following the" | | 6 | "She pressed it, and a" |
| | ratio | 0.113 | |
| 24.52% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 54 | | totalSentences | 62 | | matches | | 0 | "Detective Harlow Quinn crouched beside" | | 1 | "The abandoned Tube station beneath" | | 2 | "Quinn's fingers traced the precise" | | 3 | "She angled her head, the" | | 4 | "Davies approached, his boots crunching" | | 5 | "Quinn stood, her sharp jaw" | | 6 | "Bone tokens, enchanted artefacts, and" | | 7 | "A figure emerged from the" | | 8 | "Eva Kowalski clutched a worn" | | 9 | "She tucked a stray lock" | | 10 | "Davies said, his tone dismissive" | | 11 | "Eva's eyes darted to the" | | 12 | "Quinn raised an eyebrow." | | 13 | "Eva knelt beside the body," | | 14 | "Quinn's voice cut through the" | | 15 | "She moved through the market," | | 16 | "A brass compass lay near" | | 17 | "Quinn picked it up, turning" | | 18 | "Eva said, recognition dawning" | | 19 | "Quinn glanced at the stalls" |
| | ratio | 0.871 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 62 | | matches | (empty) | | ratio | 0 | |
| 77.92% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 22 | | technicalSentenceCount | 2 | | matches | | 0 | "She moved to a nearby stall, examining a set of scales that had been knocked over." | | 1 | "Behind them, the robed figure stepped through the archway, which snapped shut with a deafening crack, sealing them in the darkness with the killer." |
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| 59.78% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 23 | | uselessAdditionCount | 3 | | matches | | 0 | "Davies said, his tone dismissive" | | 1 | "Eva said, recognition dawning" | | 2 | "Eva whispered, her eyes wide with a mixture of fear and fascination" |
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| 74.53% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 14 | | fancyCount | 4 | | fancyTags | | 0 | "Eva whispered (whisper)" | | 1 | "Quinn corrected (correct)" | | 2 | "Davies shouted (shout)" | | 3 | "Quinn yelled (yell)" |
| | dialogueSentences | 53 | | tagDensity | 0.264 | | leniency | 0.528 | | rawRatio | 0.286 | | effectiveRatio | 0.151 | |