| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 13 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 50 | | tagDensity | 0.26 | | leniency | 0.52 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 84.31% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1275 | | 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) | |
| 49.02% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1275 | | totalAiIsms | 13 | | found | | | highlights | | 0 | "flickered" | | 1 | "scanned" | | 2 | "measured" | | 3 | "unreadable" | | 4 | "silence" | | 5 | "furrowed" | | 6 | "traced" | | 7 | "weight" | | 8 | "familiar" | | 9 | "pulse" |
| |
| 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 | 101 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 101 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 138 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 37 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 3 | | markdownWords | 6 | | totalWords | 1258 | | ratio | 0.005 | | matches | | 0 | "The Raven’s Nest" | | 1 | "Ask him." | | 2 | "sorry" |
| |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 7 | | unquotedAttributions | 0 | | matches | (empty) | |
| 66.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 35 | | wordCount | 1029 | | uniqueNames | 6 | | maxNameDensity | 1.36 | | worstName | "Evan" | | maxWindowNameDensity | 3 | | worstWindowName | "Evan" | | discoveredNames | | Rory | 9 | | Raven | 1 | | Evan | 14 | | Brendan | 1 | | Carter | 1 | | Silas | 9 |
| | persons | | 0 | "Rory" | | 1 | "Raven" | | 2 | "Evan" | | 3 | "Brendan" | | 4 | "Carter" | | 5 | "Silas" |
| | places | (empty) | | globalScore | 0.82 | | windowScore | 0.667 | |
| 68.03% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 61 | | glossingSentenceCount | 2 | | matches | | 0 | "something like guilt" | | 1 | "looked like he wanted to argue, but he ju" |
| |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1258 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 138 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 64 | | mean | 19.66 | | std | 19.21 | | cv | 0.977 | | sampleLengths | | 0 | 100 | | 1 | 21 | | 2 | 8 | | 3 | 47 | | 4 | 13 | | 5 | 48 | | 6 | 5 | | 7 | 73 | | 8 | 1 | | 9 | 6 | | 10 | 59 | | 11 | 2 | | 12 | 23 | | 13 | 23 | | 14 | 23 | | 15 | 7 | | 16 | 41 | | 17 | 11 | | 18 | 11 | | 19 | 4 | | 20 | 7 | | 21 | 52 | | 22 | 3 | | 23 | 8 | | 24 | 32 | | 25 | 15 | | 26 | 2 | | 27 | 16 | | 28 | 8 | | 29 | 26 | | 30 | 8 | | 31 | 15 | | 32 | 16 | | 33 | 5 | | 34 | 10 | | 35 | 17 | | 36 | 55 | | 37 | 29 | | 38 | 8 | | 39 | 1 | | 40 | 6 | | 41 | 5 | | 42 | 19 | | 43 | 9 | | 44 | 6 | | 45 | 12 | | 46 | 8 | | 47 | 25 | | 48 | 5 | | 49 | 15 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 101 | | matches | | |
| 94.18% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 3 | | totalVerbs | 189 | | matches | | 0 | "was giving" | | 1 | "was doing" | | 2 | "was rising" |
| |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 14 | | semicolonCount | 0 | | flaggedSentences | 11 | | totalSentences | 138 | | ratio | 0.08 | | matches | | 0 | "The bar smelled of aged whiskey and old secrets—polished wood, damp wool, the faint metallic tang of the rain that had just stopped outside." | | 1 | "The bar was quiet tonight—just a couple of regulars hunched over their drinks in the corner, the hum of their voices low and indistinct." | | 2 | "But it was the eyes that did it—sharp, assessing, the same deep brown she’d once known better than her own reflection." | | 3 | "He hesitated just inside the door, blinking against the dim light, and when his gaze landed on her, something flickered across his face—surprise, then something darker, something like guilt." | | 4 | "His hands were different—thicker, knuckles scarred, the left one wrapped in a faded leather bracelet she didn’t recognize." | | 5 | "But the whiskey was warm in her veins, and the old, reckless part of her—the part that had once thought she could outrun her own mistakes—whispered, *Ask him.*" | | 6 | "She didn’t touch her face, but she felt it—the way her cheekbones were sharper now, the dark circles under her eyes that no amount of sleep ever quite erased." | | 7 | "He knew Brendan Carter’s particular brand of disappointment—how it settled in your bones, heavy as a second skeleton." | | 8 | "Considered giving him the polished version—the one she told acquaintances, the one that didn’t include the flat above a bar, the delivery job, the way she still sometimes woke up gasping, her sheets tangled like ropes." | | 9 | "The boy she’d known—the one who’d made her laugh until her sides ached, who’d held her hair back when she was sick, who’d known her better than anyone—was gone." | | 10 | "But the weight of it all—the exhaustion, the whiskey, the way her pulse still jumped when he looked at her—settled over her like a blanket." |
| |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1034 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 37 | | adverbRatio | 0.035783365570599614 | | lyAdverbCount | 4 | | lyAdverbRatio | 0.0038684719535783366 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 138 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 138 | | mean | 9.12 | | std | 7.9 | | cv | 0.867 | | sampleLengths | | 0 | 24 | | 1 | 24 | | 2 | 18 | | 3 | 19 | | 4 | 15 | | 5 | 18 | | 6 | 3 | | 7 | 5 | | 8 | 3 | | 9 | 7 | | 10 | 26 | | 11 | 14 | | 12 | 9 | | 13 | 4 | | 14 | 13 | | 15 | 24 | | 16 | 11 | | 17 | 5 | | 18 | 24 | | 19 | 28 | | 20 | 21 | | 21 | 1 | | 22 | 6 | | 23 | 29 | | 24 | 7 | | 25 | 23 | | 26 | 2 | | 27 | 17 | | 28 | 2 | | 29 | 4 | | 30 | 22 | | 31 | 1 | | 32 | 11 | | 33 | 7 | | 34 | 5 | | 35 | 3 | | 36 | 1 | | 37 | 3 | | 38 | 11 | | 39 | 4 | | 40 | 18 | | 41 | 3 | | 42 | 5 | | 43 | 11 | | 44 | 10 | | 45 | 1 | | 46 | 4 | | 47 | 3 | | 48 | 4 | | 49 | 6 |
| |
| 51.45% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 4 | | diversityRatio | 0.32608695652173914 | | totalSentences | 138 | | uniqueOpeners | 45 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 4 | | totalSentences | 90 | | matches | | 0 | "Then the door opened again." | | 1 | "Then he shut the door" | | 2 | "Of course he knew." | | 3 | "Then Evan’s, too quiet to" |
| | ratio | 0.044 | |
| 64.44% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 35 | | totalSentences | 90 | | matches | | 0 | "She shook the water from" | | 1 | "He didn’t look up, but" | | 2 | "She slid onto a stool," | | 3 | "She reached for the bowl" | | 4 | "She took the glass, let" | | 5 | "He was taller than she" | | 6 | "Her fingers tightened around the" | | 7 | "He hesitated just inside the" | | 8 | "Her name in his voice" | | 9 | "She swallowed, forced her fingers" | | 10 | "He almost smiled." | | 11 | "His hands were different—thicker, knuckles" | | 12 | "she said, because someone had" | | 13 | "He took a sip, winced" | | 14 | "His lips quirked." | | 15 | "She should’ve left it at" | | 16 | "She didn’t touch her face," | | 17 | "He rubbed his thumb along" | | 18 | "He knew Brendan Carter’s particular" | | 19 | "She considered lying." |
| | ratio | 0.389 | |
| 54.44% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 73 | | totalSentences | 90 | | matches | | 0 | "The green neon raven flickered" | | 1 | "The bar smelled of aged" | | 2 | "She shook the water from" | | 3 | "Silas was behind the bar," | | 4 | "He didn’t look up, but" | | 5 | "She slid onto a stool," | | 6 | "Silas set the glass down." | | 7 | "Rory exhaled through her nose," | | 8 | "She reached for the bowl" | | 9 | "The salt stung the small" | | 10 | "Silas poured her a finger" | | 11 | "She took the glass, let" | | 12 | "The bar was quiet tonight—just" | | 13 | "The kind of night where" | | 14 | "A gust of wind sent" | | 15 | "He was taller than she" | | 16 | "Her fingers tightened around the" | | 17 | "He hesitated just inside the" | | 18 | "Silas glanced between them, his" | | 19 | "Evan took the stool two" |
| | ratio | 0.811 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 90 | | matches | (empty) | | ratio | 0 | |
| 46.33% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 37 | | technicalSentenceCount | 5 | | matches | | 0 | "The bar smelled of aged whiskey and old secrets—polished wood, damp wool, the faint metallic tang of the rain that had just stopped outside." | | 1 | "A gust of wind sent a scatter of rain across the threshold, and for a second, Rory didn’t recognize the man who stepped inside." | | 2 | "But it was the eyes that did it—sharp, assessing, the same deep brown she’d once known better than her own reflection." | | 3 | "But the whiskey was warm in her veins, and the old, reckless part of her—the part that had once thought she could outrun her own mistakes—whispered, *Ask him.*" | | 4 | "Silas was already reaching for her coat, holding it out." |
| |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 13 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 4 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 50 | | tagDensity | 0.08 | | leniency | 0.16 | | rawRatio | 0 | | effectiveRatio | 0 | |