| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 14 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 157 | | tagDensity | 0.089 | | leniency | 0.178 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1847 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 100.00% | AI-ism character names | Target: 0 AI-default names (16 tracked, −20% each) | | codexExemptions | | | found | (empty) | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 75.64% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1847 | | totalAiIsms | 9 | | found | | | highlights | | 0 | "flickered" | | 1 | "electric" | | 2 | "eyebrow" | | 3 | "warmth" | | 4 | "silence" | | 5 | "efficient" |
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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 | 132 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 132 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 275 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 50 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1845 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 47 | | unquotedAttributions | 0 | | matches | (empty) | |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 86 | | wordCount | 1095 | | uniqueNames | 9 | | maxNameDensity | 3.38 | | worstName | "Eva" | | maxWindowNameDensity | 6 | | worstWindowName | "Eva" | | discoveredNames | | Raven | 1 | | Nest | 1 | | Berlin | 1 | | Silas | 11 | | Aurora | 32 | | Eva | 37 | | Cardiff | 1 | | Don | 1 | | Rory | 1 |
| | persons | | 0 | "Raven" | | 1 | "Nest" | | 2 | "Silas" | | 3 | "Aurora" | | 4 | "Eva" | | 5 | "Rory" |
| | places | | | globalScore | 0 | | windowScore | 0 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 74 | | 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 | 1845 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 275 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 214 | | mean | 8.62 | | std | 10.19 | | cv | 1.181 | | sampleLengths | | 0 | 43 | | 1 | 47 | | 2 | 9 | | 3 | 8 | | 4 | 5 | | 5 | 9 | | 6 | 7 | | 7 | 2 | | 8 | 4 | | 9 | 9 | | 10 | 30 | | 11 | 12 | | 12 | 2 | | 13 | 16 | | 14 | 4 | | 15 | 5 | | 16 | 2 | | 17 | 7 | | 18 | 31 | | 19 | 2 | | 20 | 6 | | 21 | 4 | | 22 | 3 | | 23 | 5 | | 24 | 20 | | 25 | 7 | | 26 | 77 | | 27 | 6 | | 28 | 18 | | 29 | 1 | | 30 | 9 | | 31 | 21 | | 32 | 7 | | 33 | 1 | | 34 | 38 | | 35 | 7 | | 36 | 2 | | 37 | 6 | | 38 | 5 | | 39 | 7 | | 40 | 5 | | 41 | 46 | | 42 | 12 | | 43 | 13 | | 44 | 8 | | 45 | 5 | | 46 | 10 | | 47 | 10 | | 48 | 8 | | 49 | 22 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 132 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 208 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 2 | | semicolonCount | 0 | | flaggedSentences | 1 | | totalSentences | 275 | | ratio | 0.004 | | matches | | 0 | "Aurora looked at the woman across from her—the changed hair, the careful coat, the gold ring, the scar across the knuckle—and saw, beneath all of it, the girl who had once sat on a bathroom floor with her knees drawn to her chest, whispering, Don’t tell anyone, Rory." |
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| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1100 | | adjectiveStacks | 1 | | stackExamples | | 0 | "clear beneath pale skin," |
| | adverbCount | 27 | | adverbRatio | 0.024545454545454544 | | lyAdverbCount | 1 | | lyAdverbRatio | 0.0009090909090909091 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 275 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 275 | | mean | 6.71 | | std | 5.52 | | cv | 0.823 | | sampleLengths | | 0 | 22 | | 1 | 21 | | 2 | 8 | | 3 | 10 | | 4 | 16 | | 5 | 13 | | 6 | 9 | | 7 | 8 | | 8 | 5 | | 9 | 9 | | 10 | 5 | | 11 | 2 | | 12 | 2 | | 13 | 4 | | 14 | 9 | | 15 | 12 | | 16 | 8 | | 17 | 10 | | 18 | 5 | | 19 | 7 | | 20 | 2 | | 21 | 6 | | 22 | 10 | | 23 | 4 | | 24 | 5 | | 25 | 2 | | 26 | 7 | | 27 | 18 | | 28 | 6 | | 29 | 7 | | 30 | 2 | | 31 | 6 | | 32 | 4 | | 33 | 3 | | 34 | 5 | | 35 | 5 | | 36 | 15 | | 37 | 7 | | 38 | 14 | | 39 | 4 | | 40 | 16 | | 41 | 22 | | 42 | 21 | | 43 | 6 | | 44 | 18 | | 45 | 1 | | 46 | 9 | | 47 | 5 | | 48 | 16 | | 49 | 7 |
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| 44.91% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 14 | | diversityRatio | 0.21818181818181817 | | totalSentences | 275 | | uniqueOpeners | 60 | |
| 58.48% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 114 | | matches | | 0 | "Even her silence had changed." | | 1 | "Then it vanished." |
| | ratio | 0.018 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 17 | | totalSentences | 114 | | matches | | 0 | "She placed the bag on" | | 1 | "Her straight black hair clung" | | 2 | "His silver signet ring caught" | | 3 | "He came around the bar" | | 4 | "His fingers were warm and" | | 5 | "He examined the cut, then" | | 6 | "Her cheekbones stood clear beneath" | | 7 | "She wore a charcoal coat" | | 8 | "Her hair, once a wild" | | 9 | "His expression did not change," | | 10 | "It was the smile Aurora" | | 11 | "He opened the bag, inspected" | | 12 | "He did not turn on" | | 13 | "She had lost her appetite," | | 14 | "It came out thin, startled." | | 15 | "He had his back turned," | | 16 | "She took a breath, held" |
| | ratio | 0.149 | |
| 8.25% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 103 | | totalSentences | 114 | | matches | | 0 | "The green neon sign above" | | 1 | "Aurora pushed through the door" | | 2 | "The bar had settled into" | | 3 | "A woman in a red" | | 4 | "Silas glanced at the bag." | | 5 | "She placed the bag on" | | 6 | "Her straight black hair clung" | | 7 | "Silas reached for the bag." | | 8 | "His silver signet ring caught" | | 9 | "Aurora looked down at her" | | 10 | "A thin red line crossed" | | 11 | "He came around the bar" | | 12 | "His fingers were warm and" | | 13 | "He examined the cut, then" | | 14 | "The door opened behind her." | | 15 | "Aurora stepped aside, expecting another" | | 16 | "Eva had once possessed a" | | 17 | "Time had sharpened it." | | 18 | "Her cheekbones stood clear beneath" | | 19 | "She wore a charcoal coat" |
| | ratio | 0.904 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 114 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 39 | | technicalSentenceCount | 1 | | matches | | 0 | "Aurora looked at the woman across from her—the changed hair, the careful coat, the gold ring, the scar across the knuckle—and saw, beneath all of it, the girl w…" |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 14 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 14 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 157 | | tagDensity | 0.089 | | leniency | 0.178 | | rawRatio | 0 | | effectiveRatio | 0 | |