| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 15 | | adverbTagCount | 1 | | adverbTags | | 0 | "Dunmore shuffled back [back]" |
| | dialogueSentences | 34 | | tagDensity | 0.441 | | leniency | 0.882 | | rawRatio | 0.067 | | effectiveRatio | 0.059 | |
| 85.28% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1019 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | 0 | "perfectly" | | 1 | "very" | | 2 | "carefully" |
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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) | |
| 85.28% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1019 | | totalAiIsms | 3 | | found | | | highlights | | |
| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "hung in the air" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 51 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 51 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 70 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 52 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1019 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 7 | | unquotedAttributions | 0 | | matches | (empty) | |
| 83.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 18 | | wordCount | 679 | | uniqueNames | 5 | | maxNameDensity | 1.18 | | worstName | "Dunmore" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Dunmore" | | discoveredNames | | Camden | 1 | | Quinn | 7 | | Sergeant | 1 | | Ray | 1 | | Dunmore | 8 |
| | persons | | 0 | "Quinn" | | 1 | "Sergeant" | | 2 | "Ray" | | 3 | "Dunmore" |
| | places | (empty) | | globalScore | 0.911 | | windowScore | 0.833 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 39 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.981 | | wordCount | 1019 | | matches | | 0 | "No footprints up here but" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 70 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 31 | | mean | 32.87 | | std | 25.46 | | cv | 0.774 | | sampleLengths | | 0 | 53 | | 1 | 53 | | 2 | 58 | | 3 | 11 | | 4 | 77 | | 5 | 55 | | 6 | 8 | | 7 | 10 | | 8 | 67 | | 9 | 7 | | 10 | 40 | | 11 | 5 | | 12 | 23 | | 13 | 8 | | 14 | 69 | | 15 | 42 | | 16 | 12 | | 17 | 7 | | 18 | 26 | | 19 | 33 | | 20 | 75 | | 21 | 60 | | 22 | 9 | | 23 | 9 | | 24 | 3 | | 25 | 32 | | 26 | 13 | | 27 | 80 | | 28 | 13 | | 29 | 54 | | 30 | 7 |
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| 70.86% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 5 | | totalSentences | 51 | | matches | | 0 | "been arranged" | | 1 | "been stripped" | | 2 | "was clenched" | | 3 | "was etched" | | 4 | "been sealed" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 105 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 70 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 680 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 16 | | adverbRatio | 0.023529411764705882 | | lyAdverbCount | 0 | | lyAdverbRatio | 0 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 70 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 70 | | mean | 14.56 | | std | 9.9 | | cv | 0.68 | | sampleLengths | | 0 | 19 | | 1 | 34 | | 2 | 13 | | 3 | 2 | | 4 | 38 | | 5 | 19 | | 6 | 22 | | 7 | 17 | | 8 | 11 | | 9 | 25 | | 10 | 52 | | 11 | 8 | | 12 | 15 | | 13 | 9 | | 14 | 23 | | 15 | 8 | | 16 | 4 | | 17 | 6 | | 18 | 15 | | 19 | 13 | | 20 | 13 | | 21 | 26 | | 22 | 7 | | 23 | 21 | | 24 | 19 | | 25 | 2 | | 26 | 3 | | 27 | 7 | | 28 | 16 | | 29 | 8 | | 30 | 12 | | 31 | 25 | | 32 | 9 | | 33 | 23 | | 34 | 13 | | 35 | 19 | | 36 | 4 | | 37 | 6 | | 38 | 6 | | 39 | 6 | | 40 | 7 | | 41 | 20 | | 42 | 6 | | 43 | 18 | | 44 | 15 | | 45 | 9 | | 46 | 12 | | 47 | 12 | | 48 | 25 | | 49 | 17 |
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| 95.71% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 3 | | diversityRatio | 0.6 | | totalSentences | 70 | | uniqueOpeners | 42 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 44 | | matches | (empty) | | ratio | 0 | |
| 92.73% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 14 | | totalSentences | 44 | | matches | | 0 | "Its white glare pooled over" | | 1 | "He had the weathered face" | | 2 | "His face had gone the" | | 3 | "She tilted her torch so" | | 4 | "She moved the beam along" | | 5 | "They ran in from the" | | 6 | "Her voice came out flat" | | 7 | "She let that sit for" | | 8 | "His right fist was clenched" | | 9 | "She eased his fingers open" | | 10 | "It trembled, swung toward the" | | 11 | "She turned her wrist and" | | 12 | "She looked at the bone" | | 13 | "Her own watch ticked against" |
| | ratio | 0.318 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 42 | | totalSentences | 44 | | matches | | 0 | "The Camden platform smelled of" | | 1 | "Harlow Quinn ducked beneath the" | | 2 | "Someone had hung a work" | | 3 | "Its white glare pooled over" | | 4 | "Detective Sergeant Ray Dunmore came" | | 5 | "He had the weathered face" | | 6 | "Quinn took the cup and" | | 7 | "Dunmore pointed his torch at" | | 8 | "Quinn crouched at the edge" | | 9 | "The dead man wore a" | | 10 | "His face had gone the" | | 11 | "A dark stain had spread" | | 12 | "Dunmore lifted his shoulders." | | 13 | "She tilted her torch so" | | 14 | "The grime on the tiles" | | 15 | "Dust hung in the air" | | 16 | "She moved the beam along" | | 17 | "Dunmore opened his mouth, then" | | 18 | "Quinn stood and crossed the" | | 19 | "The air grew colder near" |
| | ratio | 0.955 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 44 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 25 | | technicalSentenceCount | 1 | | matches | | 0 | "Its white glare pooled over a man lying on his back between the rails of the disused northbound line, one arm flung wide, the other folded across his chest as t…" |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 15 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 3 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 34 | | tagDensity | 0.088 | | leniency | 0.176 | | rawRatio | 0 | | effectiveRatio | 0 | |