| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 20 | | adverbTagCount | 3 | | adverbTags | | 0 | "Eva nodded barely [barely]" | | 1 | "Eva gestured around [around]" | | 2 | "Eva turned back [back]" |
| | dialogueSentences | 92 | | tagDensity | 0.217 | | leniency | 0.435 | | rawRatio | 0.15 | | effectiveRatio | 0.065 | |
| 94.18% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1718 | | totalAiIsmAdverbs | 2 | | 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) | |
| 50.52% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1718 | | totalAiIsms | 17 | | found | | | highlights | | 0 | "scanned" | | 1 | "weight" | | 2 | "scanning" | | 3 | "silence" | | 4 | "flicked" | | 5 | "tension" | | 6 | "trembled" | | 7 | "echoed" | | 8 | "porcelain" | | 9 | "warmth" | | 10 | "flickered" | | 11 | "gloom" |
| |
| 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 | 157 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 157 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 227 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 26 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1718 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 20 | | unquotedAttributions | 0 | | matches | (empty) | |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 61 | | wordCount | 1208 | | uniqueNames | 8 | | maxNameDensity | 1.57 | | worstName | "Eva" | | maxWindowNameDensity | 5.5 | | worstWindowName | "Eva" | | discoveredNames | | Raven | 2 | | Nest | 2 | | Soho | 2 | | Blackwood | 1 | | Cardiff | 1 | | Eva | 19 | | Rory | 18 | | Silas | 16 |
| | persons | | 0 | "Nest" | | 1 | "Blackwood" | | 2 | "Eva" | | 3 | "Rory" | | 4 | "Silas" |
| | places | | 0 | "Raven" | | 1 | "Soho" | | 2 | "Cardiff" |
| | globalScore | 0.714 | | windowScore | 0 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 96 | | glossingSentenceCount | 1 | | matches | | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1718 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 227 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 115 | | mean | 14.94 | | std | 13.82 | | cv | 0.925 | | sampleLengths | | 0 | 60 | | 1 | 80 | | 2 | 55 | | 3 | 17 | | 4 | 50 | | 5 | 6 | | 6 | 19 | | 7 | 31 | | 8 | 7 | | 9 | 23 | | 10 | 3 | | 11 | 48 | | 12 | 16 | | 13 | 25 | | 14 | 11 | | 15 | 5 | | 16 | 32 | | 17 | 4 | | 18 | 35 | | 19 | 27 | | 20 | 27 | | 21 | 15 | | 22 | 21 | | 23 | 6 | | 24 | 1 | | 25 | 30 | | 26 | 7 | | 27 | 13 | | 28 | 4 | | 29 | 8 | | 30 | 24 | | 31 | 7 | | 32 | 7 | | 33 | 3 | | 34 | 18 | | 35 | 4 | | 36 | 22 | | 37 | 5 | | 38 | 5 | | 39 | 8 | | 40 | 23 | | 41 | 7 | | 42 | 5 | | 43 | 1 | | 44 | 25 | | 45 | 4 | | 46 | 8 | | 47 | 7 | | 48 | 26 | | 49 | 5 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 157 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 220 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 227 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1211 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 34 | | adverbRatio | 0.028075970272502065 | | lyAdverbCount | 6 | | lyAdverbRatio | 0.00495458298926507 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 227 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 227 | | mean | 7.57 | | std | 4.77 | | cv | 0.63 | | sampleLengths | | 0 | 21 | | 1 | 15 | | 2 | 24 | | 3 | 17 | | 4 | 15 | | 5 | 21 | | 6 | 13 | | 7 | 14 | | 8 | 6 | | 9 | 23 | | 10 | 7 | | 11 | 19 | | 12 | 6 | | 13 | 11 | | 14 | 7 | | 15 | 17 | | 16 | 10 | | 17 | 16 | | 18 | 6 | | 19 | 7 | | 20 | 12 | | 21 | 4 | | 22 | 14 | | 23 | 13 | | 24 | 4 | | 25 | 3 | | 26 | 9 | | 27 | 14 | | 28 | 3 | | 29 | 21 | | 30 | 16 | | 31 | 11 | | 32 | 8 | | 33 | 8 | | 34 | 15 | | 35 | 10 | | 36 | 6 | | 37 | 3 | | 38 | 2 | | 39 | 5 | | 40 | 13 | | 41 | 4 | | 42 | 15 | | 43 | 4 | | 44 | 10 | | 45 | 5 | | 46 | 20 | | 47 | 13 | | 48 | 14 | | 49 | 14 |
| |
| 37.67% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 28 | | diversityRatio | 0.2026431718061674 | | totalSentences | 227 | | uniqueOpeners | 46 | |
| 21.79% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 153 | | matches | | 0 | "Just the shadow of the" |
| | ratio | 0.007 | |
| 63.14% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 60 | | totalSentences | 153 | | matches | | 0 | "Her straight black hair fell" | | 1 | "She picked up her glass," | | 2 | "She rubbed the crescent scar" | | 3 | "His knee clicked softly as" | | 4 | "He didn't look up at" | | 5 | "She shook a black umbrella," | | 6 | "She stopped just inside the" | | 7 | "Her gaze landed on the" | | 8 | "She wore a watch that" | | 9 | "Her face was sharper, harder" | | 10 | "She smelled of tobacco and" | | 11 | "His hazel eyes flicked to" | | 12 | "He leaned on his cane," | | 13 | "Her fingers gripped the stem" | | 14 | "She turned her wrist, letting" | | 15 | "She swallowed hard." | | 16 | "She took a sip of" | | 17 | "Her throat worked visibly." | | 18 | "She laughed, a dry sound" | | 19 | "Her perfume masked the tension" |
| | ratio | 0.392 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 148 | | totalSentences | 153 | | matches | | 0 | "The green neon sign hummed" | | 1 | "Maps lined the walls, tattered" | | 2 | "Aurora sat at the far" | | 3 | "Her straight black hair fell" | | 4 | "She picked up her glass," | | 5 | "The silver signet ring on" | | 6 | "She rubbed the crescent scar" | | 7 | "Silas Blackwood moved behind the" | | 8 | "His knee clicked softly as" | | 9 | "The grey-streaked auburn hair caught" | | 10 | "He didn't look up at" | | 11 | "The bell above the door" | | 12 | "A gust of wind swept" | | 13 | "A woman stepped out of" | | 14 | "The coat she wore was" | | 15 | "She shook a black umbrella," | | 16 | "She stopped just inside the" | | 17 | "Her gaze landed on the" | | 18 | "Aurora didn't move, but she" | | 19 | "The space between them held" |
| | ratio | 0.967 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 153 | | matches | (empty) | | ratio | 0 | |
| 90.59% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 41 | | technicalSentenceCount | 3 | | matches | | 0 | "Maps lined the walls, tattered corners peeled away like dead skin, framing faded black-and-white photographs that held the eyes of people gone for decades." | | 1 | "She stopped just inside the threshold, scanning the bar with an expression that looked like hunger." | | 2 | "She wore a watch that flashed diamond light when the streetlamp outside hit it." |
| |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 20 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 7 | | fancyCount | 3 | | fancyTags | | 0 | "She laughed (laugh)" | | 1 | "Rory observed (observe)" | | 2 | "she whispered (whisper)" |
| | dialogueSentences | 92 | | tagDensity | 0.076 | | leniency | 0.152 | | rawRatio | 0.429 | | effectiveRatio | 0.065 | |