| 95.95% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 31 | | adverbTagCount | 4 | | adverbTags | | 0 | "Marcus said finally [finally]" | | 1 | "He gestured vaguely [vaguely]" | | 2 | "She softened slightly [slightly]" | | 3 | "he asked mildly [mildly]" |
| | dialogueSentences | 74 | | tagDensity | 0.419 | | leniency | 0.838 | | rawRatio | 0.129 | | effectiveRatio | 0.108 | |
| 60.55% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1394 | | totalAiIsmAdverbs | 11 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | adverb | "barely above a whisper" | | count | 1 |
| | 5 | | | 6 | |
| | highlights | | 0 | "suddenly" | | 1 | "really" | | 2 | "slightly" | | 3 | "carefully" | | 4 | "barely above a whisper" | | 5 | "gently" | | 6 | "slowly" |
| |
| 40.00% | AI-ism character names | Target: 0 AI-default names (16 tracked, −20% each) | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 64.13% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1394 | | totalAiIsms | 10 | | found | | | highlights | | 0 | "familiar" | | 1 | "methodical" | | 2 | "measured" | | 3 | "silence" | | 4 | "weight" | | 5 | "unspoken" | | 6 | "constructed" | | 7 | "whisper" | | 8 | "footsteps" |
| |
| 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 | 1 | | narrationSentences | 72 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 72 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 115 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 42 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1386 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 14 | | unquotedAttributions | 0 | | matches | (empty) | |
| 91.92% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 28 | | wordCount | 947 | | uniqueNames | 8 | | maxNameDensity | 1.16 | | worstName | "Aurora" | | maxWindowNameDensity | 2 | | worstWindowName | "Aurora" | | discoveredNames | | Aurora | 11 | | Raven | 1 | | Nest | 1 | | Silas | 7 | | Cardiff | 1 | | Paris | 1 | | Marcus | 5 | | Soho | 1 |
| | persons | | 0 | "Aurora" | | 1 | "Raven" | | 2 | "Nest" | | 3 | "Silas" | | 4 | "Marcus" |
| | places | | 0 | "Cardiff" | | 1 | "Paris" | | 2 | "Soho" |
| | globalScore | 0.919 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 59 | | 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 | 1386 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 115 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 58 | | mean | 23.9 | | std | 18.92 | | cv | 0.792 | | sampleLengths | | 0 | 74 | | 1 | 12 | | 2 | 25 | | 3 | 5 | | 4 | 76 | | 5 | 3 | | 6 | 7 | | 7 | 43 | | 8 | 7 | | 9 | 8 | | 10 | 47 | | 11 | 13 | | 12 | 15 | | 13 | 23 | | 14 | 17 | | 15 | 20 | | 16 | 30 | | 17 | 17 | | 18 | 4 | | 19 | 61 | | 20 | 11 | | 21 | 18 | | 22 | 20 | | 23 | 27 | | 24 | 7 | | 25 | 44 | | 26 | 11 | | 27 | 5 | | 28 | 16 | | 29 | 17 | | 30 | 5 | | 31 | 25 | | 32 | 22 | | 33 | 21 | | 34 | 42 | | 35 | 24 | | 36 | 9 | | 37 | 63 | | 38 | 4 | | 39 | 53 | | 40 | 35 | | 41 | 13 | | 42 | 30 | | 43 | 39 | | 44 | 15 | | 45 | 14 | | 46 | 52 | | 47 | 11 | | 48 | 14 | | 49 | 2 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 72 | | matches | (empty) | |
| 81.66% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 3 | | totalVerbs | 169 | | matches | | 0 | "was polishing" | | 1 | "wasn't talking" | | 2 | "was watching" |
| |
| 18.63% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 5 | | semicolonCount | 0 | | flaggedSentences | 5 | | totalSentences | 115 | | ratio | 0.043 | | matches | | 0 | "The man's shoulders were broader now, his hair cut short instead of the artistic mess she remembered, but she knew that particular way he held his whiskey glass—two fingers underneath, thumb on the rim, like he was afraid it might escape." | | 1 | "She ran a hand through her wet hair, aware suddenly of how she must look—delivery uniform damp and clinging, mascara probably smudged despite its waterproof promises." | | 2 | "He looked up when she was three feet away, and his face went through a series of expressions—surprise, something that might have been joy, then careful neutrality." | | 3 | "She turned to go, but his hand shot out, catching her wrist—the scarred one." | | 4 | "The green neon from the sign painted his face in shades of regret, and for a moment she saw him as he'd been—young and fearless and full of impossible dreams." |
| |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 955 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 37 | | adverbRatio | 0.0387434554973822 | | lyAdverbCount | 16 | | lyAdverbRatio | 0.016753926701570682 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 115 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 115 | | mean | 12.05 | | std | 8.13 | | cv | 0.675 | | sampleLengths | | 0 | 21 | | 1 | 22 | | 2 | 31 | | 3 | 12 | | 4 | 14 | | 5 | 11 | | 6 | 5 | | 7 | 16 | | 8 | 19 | | 9 | 41 | | 10 | 3 | | 11 | 4 | | 12 | 3 | | 13 | 11 | | 14 | 26 | | 15 | 4 | | 16 | 2 | | 17 | 7 | | 18 | 5 | | 19 | 3 | | 20 | 20 | | 21 | 27 | | 22 | 6 | | 23 | 7 | | 24 | 11 | | 25 | 4 | | 26 | 20 | | 27 | 3 | | 28 | 14 | | 29 | 3 | | 30 | 11 | | 31 | 9 | | 32 | 14 | | 33 | 14 | | 34 | 2 | | 35 | 14 | | 36 | 3 | | 37 | 4 | | 38 | 15 | | 39 | 20 | | 40 | 13 | | 41 | 13 | | 42 | 9 | | 43 | 2 | | 44 | 16 | | 45 | 2 | | 46 | 8 | | 47 | 12 | | 48 | 18 | | 49 | 9 |
| |
| 77.10% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 8 | | diversityRatio | 0.5043478260869565 | | totalSentences | 115 | | uniqueOpeners | 58 | |
| 48.31% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 69 | | matches | | 0 | "Then she blinked, and he" |
| | ratio | 0.014 | |
| 40.29% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 31 | | totalSentences | 69 | | matches | | 0 | "He was polishing glasses with" | | 1 | "She grabbed a bar towel" | | 2 | "She ran a hand through" | | 3 | "She walked over before she" | | 4 | "He looked up when she" | | 5 | "He set down his glass" | | 6 | "She remained standing, hands loose" | | 7 | "He gestured to the chair" | | 8 | "He glanced at his ring" | | 9 | "He took a sip of" | | 10 | "They sat in silence for" | | 11 | "He'd had paint under his" | | 12 | "She'd been halfway through her" | | 13 | "He stopped, jaw working" | | 14 | "She kept her voice level," | | 15 | "She watched him fidget with" | | 16 | "He'd been all graceful movements" | | 17 | "He leaned forward slightly" | | 18 | "His voice had an edge" | | 19 | "She laughed, but there was" |
| | ratio | 0.449 | |
| 17.97% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 61 | | totalSentences | 69 | | matches | | 0 | "The rain had just stopped" | | 1 | "The familiar smell of old" | | 2 | "He was polishing glasses with" | | 3 | "Silas asked, not looking up" | | 4 | "Aurora set the bag on" | | 5 | "She grabbed a bar towel" | | 6 | "The man's shoulders were broader" | | 7 | "Silas followed her gaze." | | 8 | "The words came out harder" | | 9 | "She ran a hand through" | | 10 | "Aurora straightened her shoulders" | | 11 | "She walked over before she" | | 12 | "He looked up when she" | | 13 | "He set down his glass" | | 14 | "She remained standing, hands loose" | | 15 | "He gestured to the chair" | | 16 | "The name felt strange in" | | 17 | "He glanced at his ring" | | 18 | "Aurora settled into the chair," | | 19 | "The old maps on the" |
| | ratio | 0.884 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 69 | | matches | (empty) | | ratio | 0 | |
| 58.82% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 34 | | technicalSentenceCount | 4 | | matches | | 0 | "He was polishing glasses with his usual methodical precision, the silver signet ring on his right hand catching the green glow from the neon sign that bled thro…" | | 1 | "He looked up when she was three feet away, and his face went through a series of expressions—surprise, something that might have been joy, then careful neutrali…" | | 2 | "He'd been all graceful movements and easy confidence, the kind of person who made you believe anything was possible if you just wanted it enough." | | 3 | "All of it carefully constructed to hide the artist who used to stay up until dawn, covered in oils and turpentine, talking about how color could change the worl…" |
| |
| 60.48% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 31 | | uselessAdditionCount | 4 | | matches | | 0 | "Silas asked, not looking up from his work" | | 1 | "She remained, hands loose at her sides" | | 2 | "She kept, but her fingers found the edge of the table, gripping hard" | | 3 | "Aurora stood, the chair scraping against the floor" |
| |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 7 | | fancyCount | 3 | | fancyTags | | 0 | "she breathed (breathe)" | | 1 | "She laughed (laugh)" | | 2 | "she admitted (admit)" |
| | dialogueSentences | 74 | | tagDensity | 0.095 | | leniency | 0.189 | | rawRatio | 0.429 | | effectiveRatio | 0.081 | |