| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 25 | | adverbTagCount | 1 | | adverbTags | | 0 | "He swallowed hard [hard]" |
| | dialogueSentences | 55 | | tagDensity | 0.455 | | leniency | 0.909 | | rawRatio | 0.04 | | effectiveRatio | 0.036 | |
| 92.20% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1924 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | 0 | "suddenly" | | 1 | "lightly" | | 2 | "carefully" |
| |
| 100.00% | AI-ism character names | Target: 0 AI-default names (17 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 35.03% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1924 | | totalAiIsms | 25 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | word | "down her spine" | | count | 1 |
| | 12 | | | 13 | | | 14 | | | 15 | | | 16 | | | 17 | | | 18 | | | 19 | | | 20 | | | 21 | |
| | highlights | | 0 | "flicked" | | 1 | "dancing" | | 2 | "pulse" | | 3 | "familiar" | | 4 | "intensity" | | 5 | "stomach" | | 6 | "shattered" | | 7 | "lilt" | | 8 | "perfect" | | 9 | "echoed" | | 10 | "silence" | | 11 | "down her spine" | | 12 | "pulsed" | | 13 | "clenching" | | 14 | "magnetic" | | 15 | "warmth" | | 16 | "tenderness" | | 17 | "shimmered" | | 18 | "unspoken" | | 19 | "blown wide" | | 20 | "traced" | | 21 | "fluttered" |
| |
| 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 | 137 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 137 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 167 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 39 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1922 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 11 | | unquotedAttributions | 0 | | matches | (empty) | |
| 98.20% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 42 | | wordCount | 1448 | | uniqueNames | 9 | | maxNameDensity | 1.04 | | worstName | "Aurora" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Aurora" | | discoveredNames | | Eva | 2 | | Brick | 3 | | Lane | 3 | | Moreau | 2 | | Marseilles | 1 | | Aurora | 15 | | Cardiff | 1 | | Lucien | 10 | | Ptolemy | 5 |
| | persons | | 0 | "Eva" | | 1 | "Moreau" | | 2 | "Aurora" | | 3 | "Lucien" | | 4 | "Ptolemy" |
| | places | | 0 | "Brick" | | 1 | "Lane" | | 2 | "Cardiff" |
| | globalScore | 0.982 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 105 | | 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 | 1922 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 167 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 52 | | mean | 36.96 | | std | 19.41 | | cv | 0.525 | | sampleLengths | | 0 | 64 | | 1 | 57 | | 2 | 13 | | 3 | 68 | | 4 | 17 | | 5 | 14 | | 6 | 30 | | 7 | 37 | | 8 | 64 | | 9 | 14 | | 10 | 50 | | 11 | 15 | | 12 | 55 | | 13 | 22 | | 14 | 46 | | 15 | 58 | | 16 | 26 | | 17 | 31 | | 18 | 17 | | 19 | 50 | | 20 | 72 | | 21 | 21 | | 22 | 21 | | 23 | 41 | | 24 | 48 | | 25 | 49 | | 26 | 44 | | 27 | 32 | | 28 | 65 | | 29 | 47 | | 30 | 13 | | 31 | 68 | | 32 | 28 | | 33 | 18 | | 34 | 10 | | 35 | 30 | | 36 | 69 | | 37 | 73 | | 38 | 13 | | 39 | 50 | | 40 | 15 | | 41 | 25 | | 42 | 38 | | 43 | 54 | | 44 | 8 | | 45 | 24 | | 46 | 44 | | 47 | 21 | | 48 | 47 | | 49 | 51 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 137 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 247 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 2 | | semicolonCount | 0 | | flaggedSentences | 1 | | totalSentences | 167 | | ratio | 0.006 | | matches | | 0 | "His heterochromatic eyes caught the light—one amber, one black—fixing on her with that familiar intensity that always made her stomach flip." |
| |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 719 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 28 | | adverbRatio | 0.03894297635605007 | | lyAdverbCount | 8 | | lyAdverbRatio | 0.011126564673157162 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 167 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 167 | | mean | 11.51 | | std | 6.96 | | cv | 0.605 | | sampleLengths | | 0 | 20 | | 1 | 13 | | 2 | 19 | | 3 | 2 | | 4 | 5 | | 5 | 5 | | 6 | 16 | | 7 | 4 | | 8 | 9 | | 9 | 11 | | 10 | 17 | | 11 | 9 | | 12 | 4 | | 13 | 18 | | 14 | 21 | | 15 | 9 | | 16 | 5 | | 17 | 15 | | 18 | 14 | | 19 | 3 | | 20 | 6 | | 21 | 8 | | 22 | 3 | | 23 | 15 | | 24 | 12 | | 25 | 7 | | 26 | 6 | | 27 | 10 | | 28 | 6 | | 29 | 8 | | 30 | 19 | | 31 | 17 | | 32 | 28 | | 33 | 14 | | 34 | 20 | | 35 | 9 | | 36 | 12 | | 37 | 9 | | 38 | 10 | | 39 | 5 | | 40 | 3 | | 41 | 6 | | 42 | 2 | | 43 | 30 | | 44 | 14 | | 45 | 21 | | 46 | 1 | | 47 | 24 | | 48 | 7 | | 49 | 15 |
| |
| 43.41% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 11 | | diversityRatio | 0.2994011976047904 | | totalSentences | 167 | | uniqueOpeners | 50 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 4 | | totalSentences | 132 | | matches | | 0 | "Only one person knocked like" | | 1 | "Instead he tilted his head," | | 2 | "Instead she stepped back, jaw" | | 3 | "Instead she found herself stepping" |
| | ratio | 0.03 | |
| 38.18% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 60 | | totalSentences | 132 | | matches | | 0 | "She always checked them twice." | | 1 | "She set the books down" | | 2 | "Her pulse kicked up." | | 3 | "Her left wrist itched where" | | 4 | "She rolled her shoulders, smoothed" | | 5 | "She opened the door." | | 6 | "His heterochromatic eyes caught the" | | 7 | "He looked exactly as he" | | 8 | "His voice carried the faint" | | 9 | "She gripped the doorframe, knuckles" | | 10 | "He didn't flinch." | | 11 | "She wanted to slam the" | | 12 | "She wanted to drag him" | | 13 | "He moved past her with" | | 14 | "he murmured, the corner of" | | 15 | "She turned, arms crossed, bright" | | 16 | "He tapped his cane once" | | 17 | "She moved to the tiny" | | 18 | "He set the cane against" | | 19 | "She cursed under her breath," |
| | ratio | 0.455 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 122 | | totalSentences | 132 | | matches | | 0 | "The brass knocker on Eva's" | | 1 | "Aurora froze mid-step, the stack" | | 2 | "Ptolemy, the tabby cat, flicked" | | 3 | "She always checked them twice." | | 4 | "Tonight she hadn't expected company." | | 5 | "She set the books down" | | 6 | "Her pulse kicked up." | | 7 | "Her left wrist itched where" | | 8 | "She rolled her shoulders, smoothed" | | 9 | "The third deadbolt slid free" | | 10 | "She opened the door." | | 11 | "Lucien Moreau stood in the" | | 12 | "His heterochromatic eyes caught the" | | 13 | "The ivory-handled cane rested lightly" | | 14 | "Rain glistened on his shoulders." | | 15 | "He looked exactly as he" | | 16 | "His voice carried the faint" | | 17 | "She gripped the doorframe, knuckles" | | 18 | "He didn't flinch." | | 19 | "The scar on her wrist" |
| | ratio | 0.924 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 132 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 51 | | technicalSentenceCount | 3 | | matches | | 0 | "Instead he tilted his head, studying her the way he studied arcane contracts, missing nothing." | | 1 | "Every surface reminded her of late nights spent deciphering texts together, of his fingers brushing hers over yellowed parchment, of stolen kisses between resea…" | | 2 | "Aurora buried her face in his neck, inhaling the scent that had haunted her dreams." |
| |
| 25.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 25 | | uselessAdditionCount | 5 | | matches | | 0 | "he murmured, the corner of his mouth twitching" | | 1 | "He stopped, jaw clenching" | | 2 | "other hand came up, thumb brushing her cheekbone with devastating tenderness" | | 3 | "he murmured, voice wrecked" | | 4 | "she whispered, teeth grazing the lobe" |
| |
| 59.09% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 5 | | fancyCount | 5 | | fancyTags | | 0 | "he murmured (murmur)" | | 1 | "Lucien laughed (laugh)" | | 2 | "she whispered (whisper)" | | 3 | "he murmured (murmur)" | | 4 | "she whispered (whisper)" |
| | dialogueSentences | 55 | | tagDensity | 0.091 | | leniency | 0.182 | | rawRatio | 1 | | effectiveRatio | 0.182 | |