| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 12 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 85 | | tagDensity | 0.141 | | leniency | 0.282 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1494 | | 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) | |
| 83.27% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1494 | | totalAiIsms | 5 | | found | | | highlights | | 0 | "silence" | | 1 | "pulse" | | 2 | "weight" | | 3 | "charm" |
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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 | 99 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 99 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 172 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 48 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1494 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 17 | | unquotedAttributions | 0 | | matches | (empty) | |
| 16.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 51 | | wordCount | 868 | | uniqueNames | 7 | | maxNameDensity | 2.19 | | worstName | "Quinn" | | maxWindowNameDensity | 4.5 | | worstWindowName | "Quinn" | | discoveredNames | | Quinn | 19 | | Veil | 1 | | Market | 1 | | Constable | 1 | | Malik | 15 | | Eva | 11 | | One | 3 |
| | persons | | 0 | "Quinn" | | 1 | "Market" | | 2 | "Constable" | | 3 | "Malik" | | 4 | "Eva" |
| | places | (empty) | | globalScore | 0.406 | | windowScore | 0.167 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 68 | | 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 | 1494 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 172 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 93 | | mean | 16.06 | | std | 15.13 | | cv | 0.942 | | sampleLengths | | 0 | 52 | | 1 | 49 | | 2 | 43 | | 3 | 27 | | 4 | 31 | | 5 | 32 | | 6 | 19 | | 7 | 46 | | 8 | 4 | | 9 | 7 | | 10 | 10 | | 11 | 17 | | 12 | 53 | | 13 | 6 | | 14 | 18 | | 15 | 49 | | 16 | 6 | | 17 | 6 | | 18 | 3 | | 19 | 47 | | 20 | 9 | | 21 | 4 | | 22 | 48 | | 23 | 13 | | 24 | 2 | | 25 | 8 | | 26 | 11 | | 27 | 11 | | 28 | 46 | | 29 | 5 | | 30 | 12 | | 31 | 3 | | 32 | 5 | | 33 | 5 | | 34 | 2 | | 35 | 11 | | 36 | 12 | | 37 | 33 | | 38 | 6 | | 39 | 16 | | 40 | 3 | | 41 | 3 | | 42 | 3 | | 43 | 17 | | 44 | 4 | | 45 | 30 | | 46 | 5 | | 47 | 1 | | 48 | 4 | | 49 | 8 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 99 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 142 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 2 | | flaggedSentences | 2 | | totalSentences | 172 | | ratio | 0.012 | | matches | | 0 | "One arm rested on the desk; the other hung over his knee." | | 1 | "Its casing carried green patina; protective sigils ringed its face." |
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| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 870 | | adjectiveStacks | 1 | | stackExamples | | 0 | "broad purple-red stain" |
| | adverbCount | 11 | | adverbRatio | 0.01264367816091954 | | lyAdverbCount | 2 | | lyAdverbRatio | 0.0022988505747126436 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 172 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 172 | | mean | 8.69 | | std | 5.76 | | cv | 0.663 | | sampleLengths | | 0 | 22 | | 1 | 16 | | 2 | 14 | | 3 | 25 | | 4 | 6 | | 5 | 3 | | 6 | 15 | | 7 | 9 | | 8 | 12 | | 9 | 6 | | 10 | 16 | | 11 | 19 | | 12 | 8 | | 13 | 4 | | 14 | 27 | | 15 | 5 | | 16 | 13 | | 17 | 11 | | 18 | 3 | | 19 | 9 | | 20 | 10 | | 21 | 5 | | 22 | 15 | | 23 | 7 | | 24 | 6 | | 25 | 13 | | 26 | 4 | | 27 | 7 | | 28 | 10 | | 29 | 3 | | 30 | 14 | | 31 | 5 | | 32 | 8 | | 33 | 14 | | 34 | 8 | | 35 | 18 | | 36 | 6 | | 37 | 11 | | 38 | 7 | | 39 | 7 | | 40 | 10 | | 41 | 11 | | 42 | 13 | | 43 | 8 | | 44 | 6 | | 45 | 3 | | 46 | 3 | | 47 | 3 | | 48 | 7 | | 49 | 8 |
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| 53.29% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 5 | | diversityRatio | 0.3372093023255814 | | totalSentences | 172 | | uniqueOpeners | 58 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 92 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 19 | | totalSentences | 92 | | matches | | 0 | "Their silence followed Quinn down" | | 1 | "He had a notebook open" | | 2 | "Her closely cropped hair showed" | | 3 | "She checked her worn leather" | | 4 | "Her leather satchel bulged with" | | 5 | "She tucked a curl behind" | | 6 | "It stopped short of a" | | 7 | "She followed the floor’s slope" | | 8 | "She stood and examined the" | | 9 | "Its casing carried green patina;" | | 10 | "It did not match the" | | 11 | "She kept her hands behind" | | 12 | "Its lock had no scratches." | | 13 | "Its needle held steady on" | | 14 | "She lifted her torch and" | | 15 | "His collar hid a faint" | | 16 | "She leaned closer." | | 17 | "She pointed to the chest." | | 18 | "she told the scene photographer" |
| | ratio | 0.207 | |
| 30.65% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 79 | | totalSentences | 92 | | matches | | 0 | "Harlow Quinn ducked beneath the" | | 1 | "The token had a hole" | | 2 | "The uniformed constable at the" | | 3 | "Traders watched from behind their" | | 4 | "Their silence followed Quinn down" | | 5 | "A man sat slumped beside" | | 6 | "A knife protruded from his" | | 7 | "Blood covered the front of" | | 8 | "Detective Constable Malik stood by" | | 9 | "He had a notebook open" | | 10 | "Quinn took in the room." | | 11 | "Her closely cropped hair showed" | | 12 | "She checked her worn leather" | | 13 | "Malik tilted his head towards" | | 14 | "Quinn looked through the doorway." | | 15 | "Eva stood beside a stack" | | 16 | "Her leather satchel bulged with" | | 17 | "She tucked a curl behind" | | 18 | "Malik’s jaw tightened." | | 19 | "Quinn crouched beside the desk." |
| | ratio | 0.859 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 92 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 39 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 12 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 9 | | fancyCount | 1 | | fancyTags | | 0 | "Eva continued (continue)" |
| | dialogueSentences | 85 | | tagDensity | 0.106 | | leniency | 0.212 | | rawRatio | 0.111 | | effectiveRatio | 0.024 | |