| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 8 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 62 | | tagDensity | 0.129 | | leniency | 0.258 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 89.40% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1415 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | 0 | "carefully" | | 1 | "very" | | 2 | "gently" |
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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) | |
| 78.80% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1415 | | totalAiIsms | 6 | | found | | | highlights | | 0 | "flickered" | | 1 | "weight" | | 2 | "stomach" | | 3 | "grave" | | 4 | "pulse" | | 5 | "could feel" |
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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 | 129 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 56 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1415 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 16 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 20 | | wordCount | 946 | | uniqueNames | 7 | | maxNameDensity | 0.63 | | worstName | "Lucien" | | maxWindowNameDensity | 2 | | worstWindowName | "Lucien" | | discoveredNames | | Rory | 5 | | Lucien | 6 | | Hearing | 1 | | Cardiff | 1 | | Eva | 3 | | Akkadian | 1 | | Ptolemy | 3 |
| | persons | | 0 | "Rory" | | 1 | "Lucien" | | 2 | "Eva" | | 3 | "Ptolemy" |
| | places | | | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 52 | | 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 | 1415 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 129 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 77 | | mean | 18.38 | | std | 21.79 | | cv | 1.186 | | sampleLengths | | 0 | 49 | | 1 | 4 | | 2 | 73 | | 3 | 3 | | 4 | 15 | | 5 | 22 | | 6 | 3 | | 7 | 2 | | 8 | 9 | | 9 | 37 | | 10 | 4 | | 11 | 30 | | 12 | 1 | | 13 | 5 | | 14 | 70 | | 15 | 3 | | 16 | 13 | | 17 | 2 | | 18 | 7 | | 19 | 58 | | 20 | 13 | | 21 | 96 | | 22 | 13 | | 23 | 2 | | 24 | 10 | | 25 | 51 | | 26 | 4 | | 27 | 4 | | 28 | 5 | | 29 | 28 | | 30 | 7 | | 31 | 40 | | 32 | 25 | | 33 | 6 | | 34 | 2 | | 35 | 48 | | 36 | 33 | | 37 | 2 | | 38 | 2 | | 39 | 10 | | 40 | 9 | | 41 | 23 | | 42 | 17 | | 43 | 1 | | 44 | 2 | | 45 | 44 | | 46 | 18 | | 47 | 29 | | 48 | 3 | | 49 | 57 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 76 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 166 | | matches | (empty) | |
| 98.56% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 2 | | flaggedSentences | 2 | | totalSentences | 129 | | ratio | 0.016 | | matches | | 0 | "Lucien always took his jacket off; he treated wet fabric like a personal insult." | | 1 | "Three steps did it; the flat allowed nothing more." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 951 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 33 | | adverbRatio | 0.03470031545741325 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.005257623554153523 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 129 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 129 | | mean | 10.97 | | std | 10.28 | | cv | 0.937 | | sampleLengths | | 0 | 26 | | 1 | 6 | | 2 | 9 | | 3 | 8 | | 4 | 4 | | 5 | 31 | | 6 | 9 | | 7 | 33 | | 8 | 3 | | 9 | 10 | | 10 | 5 | | 11 | 7 | | 12 | 15 | | 13 | 3 | | 14 | 2 | | 15 | 9 | | 16 | 3 | | 17 | 24 | | 18 | 10 | | 19 | 4 | | 20 | 30 | | 21 | 1 | | 22 | 5 | | 23 | 5 | | 24 | 26 | | 25 | 6 | | 26 | 6 | | 27 | 27 | | 28 | 3 | | 29 | 13 | | 30 | 2 | | 31 | 7 | | 32 | 23 | | 33 | 35 | | 34 | 13 | | 35 | 4 | | 36 | 39 | | 37 | 4 | | 38 | 20 | | 39 | 29 | | 40 | 6 | | 41 | 3 | | 42 | 4 | | 43 | 2 | | 44 | 10 | | 45 | 7 | | 46 | 8 | | 47 | 36 | | 48 | 4 | | 49 | 4 |
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| 48.58% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 19 | | diversityRatio | 0.3798449612403101 | | totalSentences | 129 | | uniqueOpeners | 49 | |
| 46.30% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 72 | | matches | | 0 | "Then she slid the chain" |
| | ratio | 0.014 | |
| 0.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 41 | | totalSentences | 72 | | matches | | 0 | "She had the chain still" | | 1 | "She saw a face." | | 2 | "His charcoal suit had soaked" | | 3 | "He shifted his weight onto" | | 4 | "He didn't smile." | | 5 | "He usually smiled, that crooked," | | 6 | "She shut the door in" | | 7 | "He stepped past her." | | 8 | "He brought the cold in" | | 9 | "He had to turn sideways" | | 10 | "His hand stopped an inch" | | 11 | "She could feel the heat" | | 12 | "She shoved the bolt across" | | 13 | "He set the cane against" | | 14 | "He rounded the vowels the" | | 15 | "She walked past him into" | | 16 | "She filled it." | | 17 | "She didn't offer him tea." | | 18 | "She got two mugs down" | | 19 | "He stayed in the doorway," |
| | ratio | 0.569 | |
| 8.61% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 65 | | totalSentences | 72 | | matches | | 0 | "The third deadbolt stuck, the" | | 1 | "She had the chain still" | | 2 | "Eva had drilled that into" | | 3 | "She saw a face." | | 4 | "Lucien stood on the landing" | | 5 | "His charcoal suit had soaked" | | 6 | "Steam and cumin climbed the" | | 7 | "He shifted his weight onto" | | 8 | "Rory kept her hand on" | | 9 | "The chain sat between them," | | 10 | "He didn't smile." | | 11 | "He usually smiled, that crooked," | | 12 | "Water ran off his cuff" | | 13 | "Something moved at her ankles." | | 14 | "Ptolemy wound between her feet" | | 15 | "Lucien looked down at the" | | 16 | "The cat looked up at" | | 17 | "Ptolemy chirped, then sat down" | | 18 | "She shut the door in" | | 19 | "He stepped past her." |
| | ratio | 0.903 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 72 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 30 | | technicalSentenceCount | 1 | | matches | | 0 | "Her shoulder touching his, and neither of them moving it away." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 8 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 3 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 62 | | tagDensity | 0.048 | | leniency | 0.097 | | rawRatio | 0.333 | | effectiveRatio | 0.032 | |