| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1746 | | 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) | |
| 82.82% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1746 | | totalAiIsms | 6 | | found | | | highlights | | 0 | "trembled" | | 1 | "etched" | | 2 | "traced" | | 3 | "weight" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 101 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 101 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 139 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 47 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1746 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 4 | | unquotedAttributions | 0 | | matches | (empty) | |
| 83.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 37 | | wordCount | 1081 | | uniqueNames | 11 | | maxNameDensity | 1.3 | | worstName | "Quinn" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Quinn" | | discoveredNames | | Harlow | 1 | | Quinn | 14 | | Tube | 1 | | Camden | 2 | | Met | 1 | | Kowalski | 1 | | High | 1 | | Street | 1 | | Eva | 9 | | Dust | 3 | | Mud | 3 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Met" | | 3 | "Kowalski" | | 4 | "Eva" | | 5 | "Dust" | | 6 | "Mud" |
| | places | | 0 | "Camden" | | 1 | "High" | | 2 | "Street" |
| | globalScore | 0.852 | | windowScore | 0.833 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 83 | | 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 | 1746 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 139 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 65 | | mean | 26.86 | | std | 20.56 | | cv | 0.765 | | sampleLengths | | 0 | 73 | | 1 | 57 | | 2 | 45 | | 3 | 60 | | 4 | 6 | | 5 | 15 | | 6 | 17 | | 7 | 22 | | 8 | 64 | | 9 | 5 | | 10 | 25 | | 11 | 36 | | 12 | 14 | | 13 | 25 | | 14 | 39 | | 15 | 15 | | 16 | 23 | | 17 | 12 | | 18 | 31 | | 19 | 61 | | 20 | 9 | | 21 | 24 | | 22 | 7 | | 23 | 7 | | 24 | 9 | | 25 | 26 | | 26 | 4 | | 27 | 24 | | 28 | 55 | | 29 | 46 | | 30 | 9 | | 31 | 25 | | 32 | 6 | | 33 | 15 | | 34 | 23 | | 35 | 12 | | 36 | 31 | | 37 | 4 | | 38 | 47 | | 39 | 67 | | 40 | 58 | | 41 | 9 | | 42 | 24 | | 43 | 4 | | 44 | 12 | | 45 | 5 | | 46 | 51 | | 47 | 15 | | 48 | 27 | | 49 | 16 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 101 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 152 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 139 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1086 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 9 | | adverbRatio | 0.008287292817679558 | | lyAdverbCount | 1 | | lyAdverbRatio | 0.0009208103130755065 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 139 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 139 | | mean | 12.56 | | std | 8.85 | | cv | 0.705 | | sampleLengths | | 0 | 35 | | 1 | 1 | | 2 | 1 | | 3 | 4 | | 4 | 9 | | 5 | 23 | | 6 | 23 | | 7 | 8 | | 8 | 10 | | 9 | 16 | | 10 | 11 | | 11 | 8 | | 12 | 5 | | 13 | 21 | | 14 | 23 | | 15 | 8 | | 16 | 7 | | 17 | 22 | | 18 | 6 | | 19 | 15 | | 20 | 17 | | 21 | 22 | | 22 | 7 | | 23 | 5 | | 24 | 21 | | 25 | 5 | | 26 | 6 | | 27 | 20 | | 28 | 5 | | 29 | 18 | | 30 | 7 | | 31 | 36 | | 32 | 14 | | 33 | 25 | | 34 | 12 | | 35 | 10 | | 36 | 5 | | 37 | 2 | | 38 | 10 | | 39 | 15 | | 40 | 23 | | 41 | 12 | | 42 | 31 | | 43 | 7 | | 44 | 6 | | 45 | 9 | | 46 | 7 | | 47 | 14 | | 48 | 4 | | 49 | 8 |
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| 46.52% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 17 | | diversityRatio | 0.35251798561151076 | | totalSentences | 139 | | uniqueOpeners | 49 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 96 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 15 | | totalSentences | 96 | | matches | | 0 | "Her salt-and-pepper crop sat damp" | | 1 | "His throat bore a clean" | | 2 | "Her curly red hair had" | | 3 | "Her round glasses carried flecks" | | 4 | "She tucked a strand behind" | | 5 | "She bent and touched a" | | 6 | "Her green eyes narrowed behind" | | 7 | "She returned to the body" | | 8 | "Her lips moved without sound." | | 9 | "Her fingertip hovered above the" | | 10 | "She stopped at the fourth" | | 11 | "She traced the row again" | | 12 | "She followed the grooves with" | | 13 | "Her jaw set in a" | | 14 | "She turned her torch from" |
| | ratio | 0.156 | |
| 38.13% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 81 | | totalSentences | 96 | | matches | | 0 | "Detective Harlow Quinn ducked under" | | 1 | "The air tasted of wet" | | 2 | "A generator chugged beyond the" | | 3 | "Quinn lifted her chin and" | | 4 | "Her salt-and-pepper crop sat damp" | | 5 | "The worn leather watch on" | | 6 | "Constables crowded the platform edge" | | 7 | "A man lay on the" | | 8 | "Someone had laid his arms" | | 9 | "Someone had closed his eyes." | | 10 | "His throat bore a clean" | | 11 | "Eva Kowalski stood at the" | | 12 | "Her curly red hair had" | | 13 | "Her round glasses carried flecks" | | 14 | "She tucked a strand behind" | | 15 | "Quinn stepped down into the" | | 16 | "Gravel crunched under her boots." | | 17 | "The dead man wore a" | | 18 | "Eva climbed down beside her" | | 19 | "Water soaked the toe of" |
| | ratio | 0.844 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 96 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 37 | | technicalSentenceCount | 1 | | matches | | 0 | "The dead man wore a black coat, black gloves pushed into one pocket, and a shirt that had once been white." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 0 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |