| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 3 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 60 | | tagDensity | 0.05 | | leniency | 0.1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 77.19% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 877 | | totalAiIsmAdverbs | 4 | | found | | | highlights | | |
| 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) | |
| 20.18% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 877 | | totalAiIsms | 14 | | found | | | highlights | | 0 | "silence" | | 1 | "unspoken" | | 2 | "oppressive" | | 3 | "newfound" | | 4 | "resolve" | | 5 | "flicker" | | 6 | "warmth" | | 7 | "weight" | | 8 | "eyebrow" | | 9 | "racing" | | 10 | "tension" | | 11 | "flickered" | | 12 | "reminder" |
| |
| 66.67% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 2 | | maxInWindow | 2 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 1 |
| | 1 | | label | "hung in the air" | | count | 1 |
|
| | highlights | | 0 | "eyes narrowed" | | 1 | "hung in the air" |
| |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 49 | | matches | (empty) | |
| 84.55% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 2 | | narrationSentences | 49 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 107 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 20 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 875 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 10 | | unquotedAttributions | 0 | | matches | (empty) | |
| 62.62% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 19 | | wordCount | 515 | | uniqueNames | 6 | | maxNameDensity | 1.75 | | worstName | "Silas" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Silas" | | discoveredNames | | Silas | 9 | | Blackwood | 1 | | Raven | 2 | | Nest | 2 | | Eva | 1 | | Aurora | 4 |
| | persons | | 0 | "Silas" | | 1 | "Blackwood" | | 2 | "Raven" | | 3 | "Nest" | | 4 | "Eva" | | 5 | "Aurora" |
| | places | (empty) | | globalScore | 0.626 | | windowScore | 0.833 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 45 | | 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 | 875 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 107 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 89 | | mean | 9.83 | | std | 9.18 | | cv | 0.934 | | sampleLengths | | 0 | 49 | | 1 | 8 | | 2 | 46 | | 3 | 25 | | 4 | 11 | | 5 | 22 | | 6 | 3 | | 7 | 5 | | 8 | 17 | | 9 | 5 | | 10 | 17 | | 11 | 3 | | 12 | 3 | | 13 | 31 | | 14 | 2 | | 15 | 6 | | 16 | 1 | | 17 | 11 | | 18 | 9 | | 19 | 12 | | 20 | 13 | | 21 | 4 | | 22 | 4 | | 23 | 25 | | 24 | 4 | | 25 | 2 | | 26 | 9 | | 27 | 6 | | 28 | 7 | | 29 | 10 | | 30 | 11 | | 31 | 9 | | 32 | 8 | | 33 | 6 | | 34 | 6 | | 35 | 31 | | 36 | 3 | | 37 | 9 | | 38 | 5 | | 39 | 2 | | 40 | 10 | | 41 | 7 | | 42 | 3 | | 43 | 27 | | 44 | 3 | | 45 | 9 | | 46 | 6 | | 47 | 11 | | 48 | 2 | | 49 | 4 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 49 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 101 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 107 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 492 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 17 | | adverbRatio | 0.034552845528455285 | | lyAdverbCount | 8 | | lyAdverbRatio | 0.016260162601626018 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 107 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 107 | | mean | 8.18 | | std | 4.69 | | cv | 0.573 | | sampleLengths | | 0 | 14 | | 1 | 11 | | 2 | 12 | | 3 | 5 | | 4 | 7 | | 5 | 8 | | 6 | 18 | | 7 | 15 | | 8 | 13 | | 9 | 15 | | 10 | 10 | | 11 | 11 | | 12 | 9 | | 13 | 13 | | 14 | 3 | | 15 | 5 | | 16 | 17 | | 17 | 5 | | 18 | 17 | | 19 | 3 | | 20 | 3 | | 21 | 9 | | 22 | 11 | | 23 | 8 | | 24 | 3 | | 25 | 2 | | 26 | 6 | | 27 | 1 | | 28 | 11 | | 29 | 9 | | 30 | 12 | | 31 | 13 | | 32 | 4 | | 33 | 4 | | 34 | 17 | | 35 | 8 | | 36 | 4 | | 37 | 2 | | 38 | 9 | | 39 | 6 | | 40 | 7 | | 41 | 10 | | 42 | 11 | | 43 | 9 | | 44 | 8 | | 45 | 6 | | 46 | 6 | | 47 | 14 | | 48 | 17 | | 49 | 3 |
| |
| 67.29% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 3 | | diversityRatio | 0.4205607476635514 | | totalSentences | 107 | | uniqueOpeners | 45 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 49 | | matches | (empty) | | ratio | 0 | |
| 64.90% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 19 | | totalSentences | 49 | | matches | | 0 | "She didn’t need to look" | | 1 | "His auburn hair, streaked with" | | 2 | "She sipped the whiskey, letting" | | 3 | "His laugh was low, humorless." | | 4 | "He’d been family." | | 5 | "She hesitated, caught between old" | | 6 | "She stayed standing, her bright" | | 7 | "She turned to leave, but" | | 8 | "She paused, her hand resting" | | 9 | "She hesitated, the weight of" | | 10 | "She returned to the bar," | | 11 | "She raised an eyebrow, her" | | 12 | "Her heart pounded, the whiskey" | | 13 | "She stared at him, the" | | 14 | "She leaned back, her mind" | | 15 | "She studied him, searching for" | | 16 | "She picked it up, the" | | 17 | "She stood, tucking the card" | | 18 | "She turned to leave, the" |
| | ratio | 0.388 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 46 | | totalSentences | 49 | | matches | | 0 | "The glass slid across the" | | 1 | "Aurora caught it mid-spin, her" | | 2 | "She didn’t need to look" | | 3 | "The whiskey smelled sharp, expensive." | | 4 | "Silas Blackwood leaned against the" | | 5 | "His auburn hair, streaked with" | | 6 | "The silver signet ring on" | | 7 | "Aurora lifted the glass, forcing" | | 8 | "The words stung more than" | | 9 | "She sipped the whiskey, letting" | | 10 | "His laugh was low, humorless." | | 11 | "Silas straightened, his limp barely" | | 12 | "The silence between them stretched," | | 13 | "Memories of late nights and" | | 14 | "Silas had been more than" | | 15 | "He’d been family." | | 16 | "Aurora’s fingers tightened around the" | | 17 | "The glass hit the bar" | | 18 | "Silas froze, the glass in" | | 19 | "The dim light of the" |
| | ratio | 0.939 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 49 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 24 | | technicalSentenceCount | 1 | | matches | | 0 | "Silas straightened, his limp barely noticeable as he moved to clean a glass that didn’t need cleaning." |
| |
| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 3 | | uselessAdditionCount | 1 | | matches | | 0 | "She turned, but Silas’ voice stopped her" |
| |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |