| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 7 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 32 | | tagDensity | 0.219 | | leniency | 0.438 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 728 | | 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) | |
| 38.19% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 728 | | totalAiIsms | 9 | | found | | | highlights | | 0 | "pulsed" | | 1 | "weight" | | 2 | "silence" | | 3 | "whisper" | | 4 | "shattered" | | 5 | "echoing" |
| |
| 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 | 53 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 53 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 78 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 32 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 1 | | markdownWords | 1 | | totalWords | 723 | | ratio | 0.001 | | matches | | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 12 | | unquotedAttributions | 0 | | matches | (empty) | |
| 48.79% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 22 | | wordCount | 494 | | uniqueNames | 7 | | maxNameDensity | 2.02 | | worstName | "Silas" | | maxWindowNameDensity | 3 | | worstWindowName | "Silas" | | discoveredNames | | Raven | 1 | | Nest | 1 | | Carter | 1 | | Rory | 1 | | Silas | 10 | | Blackwood | 1 | | Aurora | 7 |
| | persons | | 0 | "Raven" | | 1 | "Carter" | | 2 | "Rory" | | 3 | "Silas" | | 4 | "Blackwood" | | 5 | "Aurora" |
| | places | (empty) | | globalScore | 0.488 | | windowScore | 0.667 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 31 | | 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 | 723 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 78 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 35 | | mean | 20.66 | | std | 16.57 | | cv | 0.802 | | sampleLengths | | 0 | 87 | | 1 | 11 | | 2 | 20 | | 3 | 26 | | 4 | 35 | | 5 | 13 | | 6 | 26 | | 7 | 27 | | 8 | 32 | | 9 | 19 | | 10 | 13 | | 11 | 11 | | 12 | 8 | | 13 | 12 | | 14 | 16 | | 15 | 42 | | 16 | 4 | | 17 | 5 | | 18 | 5 | | 19 | 5 | | 20 | 26 | | 21 | 26 | | 22 | 16 | | 23 | 7 | | 24 | 57 | | 25 | 8 | | 26 | 17 | | 27 | 13 | | 28 | 18 | | 29 | 31 | | 30 | 12 | | 31 | 5 | | 32 | 14 | | 33 | 41 | | 34 | 15 |
| |
| 98.64% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 53 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 88 | | matches | | |
| 69.60% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 4 | | semicolonCount | 0 | | flaggedSentences | 2 | | totalSentences | 78 | | ratio | 0.026 | | matches | | 0 | "Aurora Carter—Rory, to those who knew her—stepped inside, her boots crunching on the broken glass left behind by last night’s patrons." | | 1 | "Aurora exhaled through her nose, the scent of her own cologne—something citrus and bitter—clinging to her skin." |
| |
| 99.82% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 398 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 16 | | adverbRatio | 0.04020100502512563 | | lyAdverbCount | 3 | | lyAdverbRatio | 0.007537688442211055 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 78 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 78 | | mean | 9.27 | | std | 7 | | cv | 0.755 | | sampleLengths | | 0 | 20 | | 1 | 21 | | 2 | 15 | | 3 | 4 | | 4 | 2 | | 5 | 25 | | 6 | 11 | | 7 | 17 | | 8 | 3 | | 9 | 22 | | 10 | 4 | | 11 | 3 | | 12 | 14 | | 13 | 18 | | 14 | 3 | | 15 | 10 | | 16 | 20 | | 17 | 6 | | 18 | 4 | | 19 | 23 | | 20 | 32 | | 21 | 14 | | 22 | 5 | | 23 | 6 | | 24 | 7 | | 25 | 4 | | 26 | 7 | | 27 | 5 | | 28 | 3 | | 29 | 9 | | 30 | 3 | | 31 | 12 | | 32 | 4 | | 33 | 3 | | 34 | 25 | | 35 | 6 | | 36 | 8 | | 37 | 4 | | 38 | 3 | | 39 | 2 | | 40 | 5 | | 41 | 3 | | 42 | 2 | | 43 | 16 | | 44 | 10 | | 45 | 22 | | 46 | 4 | | 47 | 4 | | 48 | 12 | | 49 | 3 |
| |
| 47.44% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 2 | | diversityRatio | 0.2564102564102564 | | totalSentences | 78 | | uniqueOpeners | 20 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 47 | | matches | | 0 | "Just moved forward, her fingers" | | 1 | "Instead, she slid onto the" | | 2 | "Instead, he reached into his" |
| | ratio | 0.064 | |
| 92.34% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 15 | | totalSentences | 47 | | matches | | 0 | "She didn’t look around." | | 1 | "he said without turning, his" | | 2 | "She didn’t answer." | | 3 | "she said, her voice quieter" | | 4 | "He didn’t deny it." | | 5 | "She didn’t look at him." | | 6 | "he said, almost to himself" | | 7 | "She finally turned, her bright" | | 8 | "He just watched her, the" | | 9 | "She didn’t flinch." | | 10 | "she shot back, the words" | | 11 | "He didn’t answer." | | 12 | "She didn’t look at the" | | 13 | "She turned on her heel," | | 14 | "He just watched the door" |
| | ratio | 0.319 | |
| 34.47% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 40 | | totalSentences | 47 | | matches | | 0 | "The neon glow of the" | | 1 | "Aurora Carter—Rory, to those who" | | 2 | "The air smelled of stale" | | 3 | "She didn’t look around." | | 4 | "he said without turning, his" | | 5 | "Aurora exhaled through her nose," | | 6 | "Silas finally turned, his hazel" | | 7 | "She didn’t answer." | | 8 | "Silas didn’t smile." | | 9 | "she said, her voice quieter" | | 10 | "He didn’t deny it." | | 11 | "Silas took a slow sip" | | 12 | "Aurora’s fingers twitched against the" | | 13 | "A beat of silence." | | 14 | "She didn’t look at him." | | 15 | "he said, almost to himself" | | 16 | "She finally turned, her bright" | | 17 | "Silas didn’t argue." | | 18 | "He just watched her, the" | | 19 | "Aurora’s jaw tightened." |
| | ratio | 0.851 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 47 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 20 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 7 | | uselessAdditionCount | 2 | | matches | | 0 | "he said, his voice low and rough" | | 1 | "he said, almost to himself" |
| |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 5 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 32 | | tagDensity | 0.156 | | leniency | 0.313 | | rawRatio | 0.2 | | effectiveRatio | 0.063 | |