| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 19 | | adverbTagCount | 1 | | adverbTags | | 0 | "He stopped then [then]" |
| | dialogueSentences | 166 | | tagDensity | 0.114 | | leniency | 0.229 | | rawRatio | 0.053 | | effectiveRatio | 0.012 | |
| 97.85% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 2323 | | totalAiIsmAdverbs | 1 | | found | | | highlights | | |
| 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) | |
| 93.54% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 2323 | | totalAiIsms | 3 | | found | | | highlights | | 0 | "stomach" | | 1 | "warmth" | | 2 | "silence" |
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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 | 142 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 142 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 288 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 41 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 2323 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 49 | | unquotedAttributions | 0 | | matches | (empty) | |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 79 | | wordCount | 1180 | | uniqueNames | 8 | | maxNameDensity | 2.54 | | worstName | "Lucien" | | maxWindowNameDensity | 5.5 | | worstWindowName | "Lucien" | | discoveredNames | | Eva | 9 | | Moreau | 1 | | Aurora | 25 | | Ptolemy | 11 | | Lucien | 30 | | Golden | 1 | | Empress | 1 | | Ask | 1 |
| | persons | | 0 | "Eva" | | 1 | "Moreau" | | 2 | "Aurora" | | 3 | "Ptolemy" | | 4 | "Lucien" |
| | places | | | globalScore | 0.229 | | windowScore | 0 | |
| 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 | 2323 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 288 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 193 | | mean | 12.04 | | std | 12.08 | | cv | 1.004 | | sampleLengths | | 0 | 12 | | 1 | 50 | | 2 | 4 | | 3 | 24 | | 4 | 2 | | 5 | 5 | | 6 | 5 | | 7 | 15 | | 8 | 4 | | 9 | 13 | | 10 | 2 | | 11 | 8 | | 12 | 14 | | 13 | 2 | | 14 | 23 | | 15 | 21 | | 16 | 3 | | 17 | 12 | | 18 | 12 | | 19 | 1 | | 20 | 8 | | 21 | 2 | | 22 | 34 | | 23 | 5 | | 24 | 9 | | 25 | 8 | | 26 | 1 | | 27 | 4 | | 28 | 7 | | 29 | 7 | | 30 | 72 | | 31 | 6 | | 32 | 4 | | 33 | 3 | | 34 | 7 | | 35 | 16 | | 36 | 5 | | 37 | 20 | | 38 | 9 | | 39 | 4 | | 40 | 14 | | 41 | 4 | | 42 | 6 | | 43 | 6 | | 44 | 5 | | 45 | 5 | | 46 | 23 | | 47 | 3 | | 48 | 44 | | 49 | 21 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 142 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 215 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 3 | | flaggedSentences | 3 | | totalSentences | 288 | | ratio | 0.01 | | matches | | 0 | "The first had Eva’s canvas bag on it; the second held a string of drying herbs." | | 1 | "One of Eva’s books occupied the seat; she moved it to the floor and sat." | | 2 | "Eva had bought strong tea; it needed milk, but Aurora stayed where she was." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1180 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 24 | | adverbRatio | 0.020338983050847456 | | lyAdverbCount | 1 | | lyAdverbRatio | 0.000847457627118644 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 288 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 288 | | mean | 8.07 | | std | 6.21 | | cv | 0.769 | | sampleLengths | | 0 | 12 | | 1 | 14 | | 2 | 14 | | 3 | 22 | | 4 | 4 | | 5 | 17 | | 6 | 7 | | 7 | 2 | | 8 | 5 | | 9 | 5 | | 10 | 11 | | 11 | 4 | | 12 | 4 | | 13 | 7 | | 14 | 6 | | 15 | 2 | | 16 | 8 | | 17 | 11 | | 18 | 3 | | 19 | 2 | | 20 | 23 | | 21 | 7 | | 22 | 14 | | 23 | 2 | | 24 | 1 | | 25 | 2 | | 26 | 10 | | 27 | 8 | | 28 | 4 | | 29 | 1 | | 30 | 8 | | 31 | 2 | | 32 | 6 | | 33 | 4 | | 34 | 24 | | 35 | 5 | | 36 | 9 | | 37 | 6 | | 38 | 2 | | 39 | 1 | | 40 | 4 | | 41 | 7 | | 42 | 3 | | 43 | 4 | | 44 | 6 | | 45 | 12 | | 46 | 17 | | 47 | 6 | | 48 | 13 | | 49 | 18 |
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| 45.49% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 13 | | diversityRatio | 0.21180555555555555 | | totalSentences | 288 | | uniqueOpeners | 61 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 125 | | matches | (empty) | | ratio | 0 | |
| 69.60% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 47 | | totalSentences | 125 | | matches | | 0 | "His platinum hair held its" | | 1 | "He looked at her left" | | 2 | "She bent to lift the" | | 3 | "His hand rested on the" | | 4 | "She looked past him, down" | | 5 | "She wanted to close the" | | 6 | "Its corner bore a smear" | | 7 | "She stepped back." | | 8 | "She shut the door, drove" | | 9 | "His gaze returned to her." | | 10 | "he told her" | | 11 | "She picked it up by" | | 12 | "She opened it." | | 13 | "Her stomach contracted." | | 14 | "She gave a short laugh." | | 15 | "He shifted his cane away" | | 16 | "She remembered that care." | | 17 | "He’d once carried a bowl" | | 18 | "She put the photograph down" | | 19 | "His mouth tightened." |
| | ratio | 0.376 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 117 | | totalSentences | 125 | | matches | | 0 | "Aurora opened Eva’s door with" | | 1 | "Lucien Moreau stood on the" | | 2 | "His platinum hair held its" | | 3 | "He looked at her left" | | 4 | "Neither of them moved." | | 5 | "Aurora tightened her grip on" | | 6 | "Lucien held up a narrow" | | 7 | "The amber eye caught the" | | 8 | "The black one gave nothing" | | 9 | "Ptolemy squeezed between Aurora’s ankles" | | 10 | "Lucien glanced down." | | 11 | "The tabby sniffed the toe" | | 12 | "She bent to lift the" | | 13 | "Ptolemy dug his claws into" | | 14 | "His hand rested on the" | | 15 | "She looked past him, down" | | 16 | "She wanted to close the" | | 17 | "The envelope stopped her." | | 18 | "Its corner bore a smear" | | 19 | "Aurora shifted Ptolemy to one" |
| | ratio | 0.936 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 125 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 46 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 19 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 15 | | fancyCount | 2 | | fancyTags | | 0 | "Lucien urged (urge)" | | 1 | "she continued (continue)" |
| | dialogueSentences | 166 | | tagDensity | 0.09 | | leniency | 0.181 | | rawRatio | 0.133 | | effectiveRatio | 0.024 | |