| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 10 | | adverbTagCount | 2 | | adverbTags | | 0 | "he asked suddenly [suddenly]" | | 1 | "she said softly [softly]" |
| | dialogueSentences | 65 | | tagDensity | 0.154 | | leniency | 0.308 | | rawRatio | 0.2 | | effectiveRatio | 0.062 | |
| 90.05% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1005 | | 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) | |
| 20.40% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1005 | | totalAiIsms | 16 | | found | | 0 | | | 1 | | | 2 | | word | "the last thing" | | count | 1 |
| | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | |
| | highlights | | 0 | "tracing" | | 1 | "stomach" | | 2 | "the last thing" | | 3 | "flicker" | | 4 | "weight" | | 5 | "footsteps" | | 6 | "unspoken" | | 7 | "silence" | | 8 | "calculated" | | 9 | "jaw clenched" | | 10 | "unreadable" | | 11 | "tension" | | 12 | "trembled" |
| |
| 33.33% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 3 | | maxInWindow | 3 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 1 |
| | 1 | | label | "stomach dropped/sank" | | count | 1 |
| | 2 | | label | "jaw/fists clenched" | | count | 1 |
|
| | highlights | | 0 | "eyes narrowed" | | 1 | "stomach dropped" | | 2 | "jaw clenched" |
| |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 70 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 70 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 123 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 32 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 998 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 13 | | unquotedAttributions | 0 | | matches | (empty) | |
| 89.43% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 26 | | wordCount | 743 | | uniqueNames | 9 | | maxNameDensity | 1.21 | | worstName | "Evan" | | maxWindowNameDensity | 2 | | worstWindowName | "Evan" | | discoveredNames | | Raven | 1 | | Nest | 1 | | London | 2 | | Cardiff | 1 | | Evan | 9 | | Oxfords | 1 | | Silas | 4 | | Rory | 6 | | Eva | 1 |
| | persons | | 0 | "Raven" | | 1 | "Nest" | | 2 | "Evan" | | 3 | "Oxfords" | | 4 | "Silas" | | 5 | "Rory" | | 6 | "Eva" |
| | places | | | globalScore | 0.894 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 56 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 99.80% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 1.002 | | wordCount | 998 | | matches | | 0 | "not since she’d left Cardiff in the dead of night with nothing but a backpack" |
| |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 123 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 64 | | mean | 15.59 | | std | 15.68 | | cv | 1.006 | | sampleLengths | | 0 | 76 | | 1 | 13 | | 2 | 73 | | 3 | 57 | | 4 | 13 | | 5 | 15 | | 6 | 43 | | 7 | 17 | | 8 | 12 | | 9 | 36 | | 10 | 8 | | 11 | 12 | | 12 | 34 | | 13 | 19 | | 14 | 3 | | 15 | 2 | | 16 | 5 | | 17 | 19 | | 18 | 4 | | 19 | 27 | | 20 | 8 | | 21 | 9 | | 22 | 2 | | 23 | 6 | | 24 | 2 | | 25 | 7 | | 26 | 14 | | 27 | 35 | | 28 | 12 | | 29 | 4 | | 30 | 1 | | 31 | 14 | | 32 | 15 | | 33 | 3 | | 34 | 20 | | 35 | 11 | | 36 | 38 | | 37 | 9 | | 38 | 9 | | 39 | 7 | | 40 | 9 | | 41 | 25 | | 42 | 17 | | 43 | 4 | | 44 | 3 | | 45 | 7 | | 46 | 1 | | 47 | 2 | | 48 | 11 | | 49 | 12 |
| |
| 95.24% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 70 | | matches | | 0 | "was slicked" | | 1 | "was gone" |
| |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 136 | | matches | (empty) | |
| 73.17% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 5 | | semicolonCount | 0 | | flaggedSentences | 3 | | totalSentences | 123 | | ratio | 0.024 | | matches | | 0 | "Evan’s face was the same—sharp jaw, dark eyes—but everything else about him felt alien." | | 1 | "A flicker of something—recognition, surprise, maybe even guilt—passed over his face before he masked it with a cool smile." | | 2 | "Evan’s gaze drifted to the photographs on the wall—old maps, black-and-white shots of London in another era." |
| |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 750 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 17 | | adverbRatio | 0.02266666666666667 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.006666666666666667 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 123 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 123 | | mean | 8.11 | | std | 6.04 | | cv | 0.744 | | sampleLengths | | 0 | 32 | | 1 | 23 | | 2 | 21 | | 3 | 9 | | 4 | 4 | | 5 | 3 | | 6 | 25 | | 7 | 14 | | 8 | 31 | | 9 | 5 | | 10 | 16 | | 11 | 17 | | 12 | 19 | | 13 | 7 | | 14 | 6 | | 15 | 11 | | 16 | 4 | | 17 | 17 | | 18 | 11 | | 19 | 15 | | 20 | 17 | | 21 | 7 | | 22 | 5 | | 23 | 16 | | 24 | 4 | | 25 | 16 | | 26 | 6 | | 27 | 2 | | 28 | 9 | | 29 | 3 | | 30 | 3 | | 31 | 16 | | 32 | 15 | | 33 | 10 | | 34 | 9 | | 35 | 3 | | 36 | 2 | | 37 | 4 | | 38 | 1 | | 39 | 14 | | 40 | 5 | | 41 | 4 | | 42 | 10 | | 43 | 13 | | 44 | 4 | | 45 | 5 | | 46 | 3 | | 47 | 5 | | 48 | 4 | | 49 | 2 |
| |
| 74.25% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 2 | | diversityRatio | 0.45528455284552843 | | totalSentences | 123 | | uniqueOpeners | 56 | |
| 47.62% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 70 | | matches | | 0 | "Instead, he took a slow" |
| | ratio | 0.014 | |
| 0.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 39 | | totalSentences | 70 | | matches | | 0 | "She hadn’t seen him in" | | 1 | "His tailored suit clung to" | | 2 | "She didn’t move, didn’t breathe." | | 3 | "he said, his voice smooth," | | 4 | "She gripped the edge of" | | 5 | "He slid onto the stool" | | 6 | "he asked, his tone casual," | | 7 | "she corrected, her voice clipped" | | 8 | "He chuckled, low and throaty," | | 9 | "He leaned in, his elbow" | | 10 | "She didn’t answer." | | 11 | "Her laugh was brittle." | | 12 | "He studied her, his gaze" | | 13 | "His jaw tightened, but he" | | 14 | "Her voice was flat" | | 15 | "Her fingers twitched, but she" | | 16 | "He seemed to be searching" | | 17 | "he asked suddenly, his voice" | | 18 | "Her chest tightened." | | 19 | "She turned to him, her" |
| | ratio | 0.557 | |
| 10.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 63 | | totalSentences | 70 | | matches | | 0 | "The door of The Raven’s" | | 1 | "Rory glanced up from the" | | 2 | "The man who stepped in" | | 3 | "Silas’s voice broke the quiet" | | 4 | "Rory’s stomach dropped." | | 5 | "She hadn’t seen him in" | | 6 | "Evan’s face was the same—sharp" | | 7 | "His tailored suit clung to" | | 8 | "She didn’t move, didn’t breathe." | | 9 | "The last thing she wanted" | | 10 | "A flicker of something—recognition, surprise," | | 11 | "he said, his voice smooth," | | 12 | "She gripped the edge of" | | 13 | "Silas’s eyes narrowed, but he" | | 14 | "Evan stepped closer, his polished" | | 15 | "He slid onto the stool" | | 16 | "he asked, his tone casual," | | 17 | "she corrected, her voice clipped" | | 18 | "He chuckled, low and throaty," | | 19 | "Rory’s fingers tightened around her" |
| | ratio | 0.9 | |
| 71.43% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 70 | | matches | | | ratio | 0.014 | |
| 27.65% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 31 | | technicalSentenceCount | 5 | | matches | | 0 | "Rory glanced up from the foamy pint she’d been nursing, her fingers tracing the small crescent scar on her wrist out of habit." | | 1 | "The man who stepped in hesitated at the threshold, his silhouette framed by the green neon glow of the sign outside." | | 2 | "His tailored suit clung to him in a way his old leather jacket never had, and his hair, once perpetually messy, was slicked back with a precision that made her …" | | 3 | "Silas’s eyes narrowed, but he said nothing, his hands busy polishing a glass that didn’t need it." | | 4 | "He studied her, his gaze lingering on the scar she’d been tracing moments ago." |
| |
| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 10 | | uselessAdditionCount | 7 | | matches | | 0 | "he said, his voice smooth, deliberate" | | 1 | "he asked, his tone casual, though his eyes drilled into her" | | 2 | "she corrected, her voice clipped" | | 3 | "He leaned in, his elbow brushing hers" | | 4 | "he asked suddenly, his voice quieter now" | | 5 | "He leaned, his breath warm against her cheek" | | 6 | "she said softly, almost to herself" |
| |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 7 | | fancyCount | 1 | | fancyTags | | 0 | "she corrected (correct)" |
| | dialogueSentences | 65 | | tagDensity | 0.108 | | leniency | 0.215 | | rawRatio | 0.143 | | effectiveRatio | 0.031 | |