| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 10 | | adverbTagCount | 2 | | adverbTags | | 0 | "Eva said softly [softly]" | | 1 | "Eva’s hands clenched around [around]" |
| | dialogueSentences | 50 | | tagDensity | 0.2 | | leniency | 0.4 | | rawRatio | 0.2 | | effectiveRatio | 0.08 | |
| 75.32% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1418 | | totalAiIsmAdverbs | 7 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | adverb | "barely above a whisper" | | count | 1 |
|
| | highlights | | 0 | "very" | | 1 | "slightly" | | 2 | "slowly" | | 3 | "really" | | 4 | "softly" | | 5 | "barely above a whisper" |
| |
| 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) | |
| 29.48% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1418 | | totalAiIsms | 20 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | word | "cast a warm glow" | | count | 1 |
| | 11 | | | 12 | | | 13 | | | 14 | |
| | highlights | | 0 | "tracing" | | 1 | "echoing" | | 2 | "familiar" | | 3 | "stomach" | | 4 | "silence" | | 5 | "glinting" | | 6 | "tension" | | 7 | "weight" | | 8 | "comforting" | | 9 | "could feel" | | 10 | "cast a warm glow" | | 11 | "unreadable" | | 12 | "intensity" | | 13 | "whisper" | | 14 | "reminder" |
| |
| 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 | 111 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 111 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 149 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 41 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 4 | | markdownWords | 13 | | totalWords | 1411 | | ratio | 0.009 | | matches | | 0 | "You’ll be safe here." | | 1 | "Had to go. Don’t look for me." | | 2 | "had" | | 3 | "had" |
| |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 15 | | unquotedAttributions | 0 | | matches | (empty) | |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 80 | | wordCount | 1142 | | uniqueNames | 10 | | maxNameDensity | 3.24 | | worstName | "Eva" | | maxWindowNameDensity | 6.5 | | worstWindowName | "Eva" | | discoveredNames | | Raven | 2 | | Nest | 2 | | Covent | 1 | | Garden | 1 | | London | 1 | | Rory | 30 | | Eva | 37 | | Cardiff | 2 | | Evan | 1 | | Silas | 3 |
| | persons | | 0 | "Raven" | | 1 | "Nest" | | 2 | "Rory" | | 3 | "Eva" | | 4 | "Evan" | | 5 | "Silas" |
| | places | | 0 | "Covent" | | 1 | "Garden" | | 2 | "London" | | 3 | "Cardiff" |
| | globalScore | 0 | | windowScore | 0 | |
| 80.56% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 72 | | glossingSentenceCount | 2 | | matches | | 0 | "felt like a kind of home" | | 1 | "appeared behind the bar, his hazel eyes sharp as he took in the scene" |
| |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1411 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 149 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 57 | | mean | 24.75 | | std | 26.06 | | cv | 1.053 | | sampleLengths | | 0 | 121 | | 1 | 59 | | 2 | 14 | | 3 | 2 | | 4 | 128 | | 5 | 13 | | 6 | 5 | | 7 | 88 | | 8 | 11 | | 9 | 41 | | 10 | 6 | | 11 | 14 | | 12 | 35 | | 13 | 9 | | 14 | 7 | | 15 | 27 | | 16 | 28 | | 17 | 9 | | 18 | 30 | | 19 | 65 | | 20 | 51 | | 21 | 2 | | 22 | 9 | | 23 | 39 | | 24 | 19 | | 25 | 19 | | 26 | 15 | | 27 | 9 | | 28 | 55 | | 29 | 16 | | 30 | 6 | | 31 | 46 | | 32 | 8 | | 33 | 40 | | 34 | 21 | | 35 | 8 | | 36 | 12 | | 37 | 4 | | 38 | 15 | | 39 | 20 | | 40 | 5 | | 41 | 41 | | 42 | 12 | | 43 | 8 | | 44 | 7 | | 45 | 2 | | 46 | 23 | | 47 | 12 | | 48 | 8 | | 49 | 31 |
| |
| 95.78% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 111 | | matches | | 0 | "been carved" | | 1 | "were wrapped" | | 2 | "get tangled" |
| |
| 36.60% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 5 | | totalVerbs | 204 | | matches | | 0 | "was bracing" | | 1 | "weren’t saying" | | 2 | "was, standing" | | 3 | "wasn’t running" | | 4 | "was watching" |
| |
| 46.98% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 7 | | semicolonCount | 0 | | flaggedSentences | 5 | | totalSentences | 149 | | ratio | 0.034 | | matches | | 0 | "The delivery to Covent Garden had taken less time than expected, and the thought of going back to the flat—empty, echoing—had sent her here instead, to the one place in London that still felt like a kind of home." | | 1 | "Then the scent hit her—leather and bergamot, something familiar beneath the rain." | | 2 | "It was the way Eva held herself—shoulders squared, chin lifted, like she was bracing for a fight." | | 3 | "And her hands—Rory’s gaze snagged on them—were wrapped in bandages, the kind that spoke of stitches and antiseptic." | | 4 | "She should have felt something—relief, maybe, or anger." |
| |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1153 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 44 | | adverbRatio | 0.03816131830008673 | | lyAdverbCount | 11 | | lyAdverbRatio | 0.009540329575021683 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 149 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 149 | | mean | 9.47 | | std | 7.14 | | cv | 0.754 | | sampleLengths | | 0 | 28 | | 1 | 22 | | 2 | 25 | | 3 | 7 | | 4 | 39 | | 5 | 18 | | 6 | 4 | | 7 | 22 | | 8 | 12 | | 9 | 3 | | 10 | 9 | | 11 | 5 | | 12 | 2 | | 13 | 14 | | 14 | 10 | | 15 | 17 | | 16 | 31 | | 17 | 16 | | 18 | 14 | | 19 | 8 | | 20 | 18 | | 21 | 11 | | 22 | 2 | | 23 | 2 | | 24 | 3 | | 25 | 16 | | 26 | 37 | | 27 | 3 | | 28 | 28 | | 29 | 4 | | 30 | 11 | | 31 | 15 | | 32 | 15 | | 33 | 11 | | 34 | 6 | | 35 | 10 | | 36 | 4 | | 37 | 4 | | 38 | 18 | | 39 | 9 | | 40 | 4 | | 41 | 2 | | 42 | 7 | | 43 | 3 | | 44 | 4 | | 45 | 6 | | 46 | 13 | | 47 | 8 | | 48 | 11 | | 49 | 17 |
| |
| 45.30% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 7 | | diversityRatio | 0.28859060402684567 | | totalSentences | 149 | | uniqueOpeners | 43 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 6 | | totalSentences | 102 | | matches | | 0 | "Then the scent hit her—leather" | | 1 | "Then she turned to Rory," | | 2 | "Then, slowly, she nodded." | | 3 | "Instead, she went to the" | | 4 | "Instead, she reached across the" | | 5 | "Instead, she reached across the" |
| | ratio | 0.059 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 15 | | totalSentences | 102 | | matches | | 0 | "She hadn’t meant to stay" | | 1 | "She was too busy watching" | | 2 | "Her stomach tightened." | | 3 | "It was the way Eva" | | 4 | "Her coat, once a vibrant" | | 5 | "He didn’t say anything, just" | | 6 | "She caught it with her" | | 7 | "she said, voice rough" | | 8 | "He nodded, his signet ring" | | 9 | "She downed the whiskey in" | | 10 | "She held up her bandaged" | | 11 | "She should have felt something—relief," | | 12 | "She *had* been running." | | 13 | "They sat at the small" | | 14 | "She could feel the weight" |
| | ratio | 0.147 | |
| 97.25% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 74 | | totalSentences | 102 | | matches | | 0 | "The Raven’s Nest hummed with" | | 1 | "The green neon sign outside" | | 2 | "Rory leaned against the bar," | | 3 | "She hadn’t meant to stay" | | 4 | "The delivery to Covent Garden" | | 5 | "The door swung open, letting" | | 6 | "Rory didn’t look up." | | 7 | "She was too busy watching" | | 8 | "Her stomach tightened." | | 9 | "a voice said, low and" | | 10 | "Eva stood there, dripping onto" | | 11 | "It was the way Eva" | | 12 | "The last time Rory had" | | 13 | "Her coat, once a vibrant" | | 14 | "The silver hoops in her" | | 15 | "Eva followed her stare and" | | 16 | "The silence between them was" | | 17 | "Eva had been the one" | | 18 | "Silas appeared behind the bar," | | 19 | "He didn’t say anything, just" |
| | ratio | 0.725 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 4 | | totalSentences | 102 | | matches | | 0 | "Now, there was something hollowed" | | 1 | "Now here she was, standing" | | 2 | "Because Eva wasn’t wrong." | | 3 | "Because Eva was right." |
| | ratio | 0.039 | |
| 99.13% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 49 | | technicalSentenceCount | 3 | | matches | | 0 | "The Raven’s Nest hummed with the low murmur of conversation and the clink of glasses, the kind of noise that settled into the bones like a second heartbeat." | | 1 | "But it wasn’t the rain that made Rory’s breath catch." | | 2 | "When she turned back, Eva was watching her with an intensity that made her stomach flip." |
| |
| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 10 | | uselessAdditionCount | 3 | | matches | | 0 | "she said, voice rough" | | 1 | "Eva leaned, her voice dropping" | | 2 | "Eva said, her voice barely above a whisper" |
| |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 5 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 50 | | tagDensity | 0.1 | | leniency | 0.2 | | rawRatio | 0 | | effectiveRatio | 0 | |