| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 17 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 135 | | tagDensity | 0.126 | | leniency | 0.252 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 97.06% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1703 | | totalAiIsmAdverbs | 1 | | found | | | highlights | | |
| 80.00% | AI-ism character names | Target: 0 AI-default names (16 tracked, −20% each) | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 88.26% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1703 | | totalAiIsms | 4 | | found | | | highlights | | 0 | "flickered" | | 1 | "familiar" | | 2 | "silence" | | 3 | "warmth" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "let out a breath" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 1 | | narrationSentences | 110 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 110 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 228 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 34 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1703 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 31 | | unquotedAttributions | 0 | | matches | (empty) | |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 79 | | wordCount | 991 | | uniqueNames | 8 | | maxNameDensity | 3.53 | | worstName | "Rory" | | maxWindowNameDensity | 5.5 | | worstWindowName | "Eva" | | discoveredNames | | Rory | 35 | | Raven | 1 | | Nest | 1 | | Golden | 1 | | Empress | 1 | | Eva | 34 | | Taff | 1 | | Silas | 5 |
| | persons | | 0 | "Rory" | | 1 | "Raven" | | 2 | "Nest" | | 3 | "Eva" | | 4 | "Silas" |
| | places | (empty) | | globalScore | 0 | | windowScore | 0 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 76 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.587 | | wordCount | 1703 | | matches | | 0 | "not in the lines of her face but in the way she kept her coat buttoned, in the patience with" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 228 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 158 | | mean | 10.78 | | std | 11.49 | | cv | 1.066 | | sampleLengths | | 0 | 51 | | 1 | 16 | | 2 | 4 | | 3 | 24 | | 4 | 4 | | 5 | 22 | | 6 | 59 | | 7 | 12 | | 8 | 1 | | 9 | 19 | | 10 | 1 | | 11 | 45 | | 12 | 6 | | 13 | 2 | | 14 | 5 | | 15 | 4 | | 16 | 10 | | 17 | 5 | | 18 | 17 | | 19 | 11 | | 20 | 2 | | 21 | 1 | | 22 | 6 | | 23 | 37 | | 24 | 4 | | 25 | 4 | | 26 | 2 | | 27 | 11 | | 28 | 1 | | 29 | 2 | | 30 | 7 | | 31 | 4 | | 32 | 14 | | 33 | 6 | | 34 | 8 | | 35 | 32 | | 36 | 8 | | 37 | 6 | | 38 | 3 | | 39 | 3 | | 40 | 21 | | 41 | 8 | | 42 | 7 | | 43 | 13 | | 44 | 5 | | 45 | 7 | | 46 | 16 | | 47 | 20 | | 48 | 2 | | 49 | 6 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 110 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 174 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 228 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 992 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 19 | | adverbRatio | 0.019153225806451613 | | lyAdverbCount | 1 | | lyAdverbRatio | 0.0010080645161290322 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 228 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 228 | | mean | 7.47 | | std | 5.6 | | cv | 0.75 | | sampleLengths | | 0 | 17 | | 1 | 18 | | 2 | 10 | | 3 | 6 | | 4 | 9 | | 5 | 7 | | 6 | 4 | | 7 | 20 | | 8 | 4 | | 9 | 4 | | 10 | 22 | | 11 | 16 | | 12 | 24 | | 13 | 9 | | 14 | 10 | | 15 | 12 | | 16 | 1 | | 17 | 2 | | 18 | 8 | | 19 | 9 | | 20 | 1 | | 21 | 3 | | 22 | 13 | | 23 | 5 | | 24 | 5 | | 25 | 19 | | 26 | 6 | | 27 | 2 | | 28 | 5 | | 29 | 4 | | 30 | 10 | | 31 | 5 | | 32 | 10 | | 33 | 7 | | 34 | 11 | | 35 | 2 | | 36 | 1 | | 37 | 6 | | 38 | 7 | | 39 | 4 | | 40 | 26 | | 41 | 4 | | 42 | 4 | | 43 | 2 | | 44 | 9 | | 45 | 2 | | 46 | 1 | | 47 | 2 | | 48 | 7 | | 49 | 4 |
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| 42.54% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 17 | | diversityRatio | 0.25877192982456143 | | totalSentences | 228 | | uniqueOpeners | 59 | |
| 35.09% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 95 | | matches | | 0 | "Then she stood, and the" |
| | ratio | 0.011 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 20 | | totalSentences | 95 | | matches | | 0 | "She shifted the Golden Empress" | | 1 | "Her wrists ached from the" | | 2 | "His silver signet ring caught" | | 3 | "She rubbed the crescent scar" | | 4 | "Her hair, once a thick" | | 5 | "She wore a charcoal coat" | | 6 | "Her hands rested beside the" | | 7 | "They met halfway." | | 8 | "She slid onto the stool" | | 9 | "Their shoulders didn’t touch." | | 10 | "His limp made a soft" | | 11 | "Her throat moved." | | 12 | "She’d laughed with her whole" | | 13 | "She worried one corner into" | | 14 | "She pressed her thumbnail into" | | 15 | "She folded the napkin into" | | 16 | "His shoulder brushed Rory’s." | | 17 | "He set a bowl of" | | 18 | "It had cooled enough to" | | 19 | "She sat back on the" |
| | ratio | 0.211 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 89 | | totalSentences | 95 | | matches | | 0 | "Rain followed Rory through the" | | 1 | "The green neon outside broke" | | 2 | "She shifted the Golden Empress" | | 3 | "Her wrists ached from the" | | 4 | "Silas looked up from a" | | 5 | "His silver signet ring caught" | | 6 | "Rory hung the bag by" | | 7 | "She rubbed the crescent scar" | | 8 | "The woman held a glass" | | 9 | "Her hair, once a thick" | | 10 | "She wore a charcoal coat" | | 11 | "Her hands rested beside the" | | 12 | "Rory knew the shape of" | | 13 | "They met halfway." | | 14 | "Eva’s arms rose as if" | | 15 | "Rory closed the distance herself." | | 16 | "The embrace lasted a breath." | | 17 | "Eva smelled of rain and" | | 18 | "The old rhythm flickered between" | | 19 | "Eva’s smile arrived late and" |
| | ratio | 0.937 | |
| 52.63% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 95 | | matches | | 0 | "Now she left spaces between" |
| | ratio | 0.011 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 35 | | technicalSentenceCount | 2 | | matches | | 0 | "Eva’s arms rose as if by habit, then stopped short of Rory’s shoulders." | | 1 | "The girl who had once slept in Rory’s bed after a fight with her mother, talking until dawn and falling asleep with one hand twisted in Rory’s sleeve." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 17 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 14 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 135 | | tagDensity | 0.104 | | leniency | 0.207 | | rawRatio | 0 | | effectiveRatio | 0 | |