| 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 | 1697 | | 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) | |
| 85.27% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1697 | | totalAiIsms | 5 | | found | | | highlights | | 0 | "weight" | | 1 | "pulse" | | 2 | "tenderness" | | 3 | "silence" | | 4 | "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 | 1 | | narrationSentences | 116 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 116 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 200 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 35 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1697 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 16 | | unquotedAttributions | 0 | | matches | (empty) | |
| 66.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 36 | | wordCount | 1216 | | uniqueNames | 7 | | maxNameDensity | 1.64 | | worstName | "Aurora" | | maxWindowNameDensity | 3 | | worstWindowName | "Aurora" | | discoveredNames | | Lucien | 9 | | Moreau | 1 | | Aurora | 20 | | Avaros | 1 | | Eva | 1 | | Evan | 1 | | Ptolemy | 3 |
| | persons | | 0 | "Lucien" | | 1 | "Moreau" | | 2 | "Aurora" | | 3 | "Eva" | | 4 | "Evan" | | 5 | "Ptolemy" |
| | places | (empty) | | globalScore | 0.678 | | windowScore | 0.667 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 90 | | glossingSentenceCount | 1 | | matches | | 0 | "seemed unable to finish the work" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.589 | | wordCount | 1697 | | matches | | 0 | "not close, but the black edge slowed" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 200 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 122 | | mean | 13.91 | | std | 16.27 | | cv | 1.169 | | sampleLengths | | 0 | 20 | | 1 | 32 | | 2 | 8 | | 3 | 14 | | 4 | 20 | | 5 | 5 | | 6 | 4 | | 7 | 7 | | 8 | 22 | | 9 | 3 | | 10 | 1 | | 11 | 3 | | 12 | 7 | | 13 | 3 | | 14 | 7 | | 15 | 14 | | 16 | 8 | | 17 | 55 | | 18 | 2 | | 19 | 9 | | 20 | 4 | | 21 | 6 | | 22 | 7 | | 23 | 39 | | 24 | 2 | | 25 | 9 | | 26 | 4 | | 27 | 14 | | 28 | 3 | | 29 | 7 | | 30 | 61 | | 31 | 30 | | 32 | 4 | | 33 | 19 | | 34 | 5 | | 35 | 3 | | 36 | 24 | | 37 | 8 | | 38 | 4 | | 39 | 9 | | 40 | 39 | | 41 | 47 | | 42 | 3 | | 43 | 4 | | 44 | 1 | | 45 | 5 | | 46 | 21 | | 47 | 18 | | 48 | 42 | | 49 | 22 |
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| 99.21% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 116 | | matches | | 0 | "was gone" | | 1 | "was composed" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 200 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 200 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1217 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 27 | | adverbRatio | 0.02218570254724733 | | lyAdverbCount | 0 | | lyAdverbRatio | 0 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 200 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 200 | | mean | 8.49 | | std | 6.07 | | cv | 0.715 | | sampleLengths | | 0 | 20 | | 1 | 7 | | 2 | 25 | | 3 | 8 | | 4 | 14 | | 5 | 7 | | 6 | 13 | | 7 | 5 | | 8 | 4 | | 9 | 7 | | 10 | 5 | | 11 | 7 | | 12 | 6 | | 13 | 4 | | 14 | 3 | | 15 | 1 | | 16 | 3 | | 17 | 7 | | 18 | 3 | | 19 | 7 | | 20 | 10 | | 21 | 4 | | 22 | 8 | | 23 | 10 | | 24 | 17 | | 25 | 3 | | 26 | 8 | | 27 | 12 | | 28 | 5 | | 29 | 2 | | 30 | 9 | | 31 | 4 | | 32 | 6 | | 33 | 7 | | 34 | 15 | | 35 | 10 | | 36 | 14 | | 37 | 2 | | 38 | 9 | | 39 | 4 | | 40 | 14 | | 41 | 3 | | 42 | 7 | | 43 | 7 | | 44 | 14 | | 45 | 6 | | 46 | 3 | | 47 | 9 | | 48 | 5 | | 49 | 9 |
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| 47.00% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 6 | | diversityRatio | 0.25 | | totalSentences | 200 | | uniqueOpeners | 50 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 115 | | matches | (empty) | | ratio | 0 | |
| 53.04% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 48 | | totalSentences | 115 | | matches | | 0 | "He shifted his weight, the" | | 1 | "She moved her hand to" | | 2 | "He came in with a" | | 3 | "His palm pressed his ribs." | | 4 | "He drew breath through his" | | 5 | "She took it, then grabbed" | | 6 | "She caught the edge of" | | 7 | "He went still." | | 8 | "She peeled back the linen" | | 9 | "She looked at the cane." | | 10 | "His gaze stayed on her" | | 11 | "He watched the metal." | | 12 | "She took his hand off" | | 13 | "His fingers were cold." | | 14 | "She bent and pushed the" | | 15 | "His other hand closed on" | | 16 | "She wiped it on the" | | 17 | "He hissed but did not" | | 18 | "She sat on the floor" | | 19 | "His pulse ran fast under" |
| | ratio | 0.417 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 110 | | totalSentences | 115 | | matches | | 0 | "The door opened on Lucien" | | 1 | "Aurora kept one hand on" | | 2 | "The gap showed a sliver" | | 3 | "He shifted his weight, the" | | 4 | "Ptolemy bolted between Aurora’s ankles" | | 5 | "Lucien looked down at the" | | 6 | "Aurora glanced past his elbow." | | 7 | "The curry house below had" | | 8 | "The landing was empty." | | 9 | "She moved her hand to" | | 10 | "Aurora studied the line where" | | 11 | "He came in with a" | | 12 | "The scent followed him: rain," | | 13 | "The door shut." | | 14 | "Aurora turned the chain and" | | 15 | "Lucien moved into the room" | | 16 | "His palm pressed his ribs." | | 17 | "He drew breath through his" | | 18 | "Aurora dropped to her knees" | | 19 | "The tea towel lay under" |
| | ratio | 0.957 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 115 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 52 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 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 | |