| 50.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 16 | | adverbTagCount | 3 | | adverbTags | | 0 | "he interrupted gently [gently]" | | 1 | "he said quietly [quietly]" | | 2 | "she admitted quietly [quietly]" |
| | dialogueSentences | 40 | | tagDensity | 0.4 | | leniency | 0.8 | | rawRatio | 0.188 | | effectiveRatio | 0.15 | |
| 84.34% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1277 | | totalAiIsmAdverbs | 4 | | found | | | highlights | | 0 | "gently" | | 1 | "lightly" | | 2 | "softly" |
| |
| 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) | |
| 37.35% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1277 | | totalAiIsms | 16 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | word | "down her spine" | | count | 1 |
| | 12 | | | 13 | | | 14 | |
| | highlights | | 0 | "silence" | | 1 | "flicked" | | 2 | "stomach" | | 3 | "glint" | | 4 | "racing" | | 5 | "unravel" | | 6 | "potential" | | 7 | "sense of" | | 8 | "unspoken" | | 9 | "encounter" | | 10 | "warmth" | | 11 | "down her spine" | | 12 | "weight" | | 13 | "desire" | | 14 | "pounding" |
| |
| 33.33% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 3 | | maxInWindow | 3 | | found | | 0 | | label | "air was thick with" | | count | 1 |
| | 1 | | label | "weight of words/silence" | | count | 1 |
| | 2 | | label | "hung in the air" | | count | 1 |
|
| | highlights | | 0 | "the air was thick with" | | 1 | "the weight of his words" | | 2 | "hung in the air" |
| |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 75 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 2 | | narrationSentences | 75 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 99 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 31 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1268 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 22 | | unquotedAttributions | 0 | | matches | (empty) | |
| 66.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 32 | | wordCount | 957 | | uniqueNames | 10 | | maxNameDensity | 1.15 | | worstName | "Aurora" | | maxWindowNameDensity | 3 | | worstWindowName | "Aurora" | | discoveredNames | | Edinburgh | 1 | | Aurora | 11 | | Thursday | 1 | | Eva | 5 | | Moreau | 1 | | Mayfair | 1 | | Lucien | 5 | | Ptolemy | 3 | | Enochian | 2 | | Codex | 2 |
| | persons | | 0 | "Aurora" | | 1 | "Eva" | | 2 | "Moreau" | | 3 | "Lucien" | | 4 | "Ptolemy" |
| | places | | | globalScore | 0.925 | | windowScore | 0.667 | |
| 70.63% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 63 | | glossingSentenceCount | 2 | | matches | | 0 | "something like this—she’d always been driven" | | 1 | "felt like she could breathe again" |
| |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.789 | | wordCount | 1268 | | matches | | 0 | "not yet, but it was a start" |
| |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 99 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 45 | | mean | 28.18 | | std | 14.56 | | cv | 0.517 | | sampleLengths | | 0 | 50 | | 1 | 33 | | 2 | 49 | | 3 | 58 | | 4 | 53 | | 5 | 14 | | 6 | 36 | | 7 | 23 | | 8 | 27 | | 9 | 19 | | 10 | 21 | | 11 | 11 | | 12 | 24 | | 13 | 21 | | 14 | 13 | | 15 | 5 | | 16 | 21 | | 17 | 54 | | 18 | 32 | | 19 | 9 | | 20 | 26 | | 21 | 34 | | 22 | 7 | | 23 | 18 | | 24 | 51 | | 25 | 10 | | 26 | 40 | | 27 | 39 | | 28 | 16 | | 29 | 36 | | 30 | 35 | | 31 | 17 | | 32 | 12 | | 33 | 28 | | 34 | 41 | | 35 | 41 | | 36 | 16 | | 37 | 27 | | 38 | 50 | | 39 | 43 | | 40 | 27 | | 41 | 16 | | 42 | 8 | | 43 | 42 | | 44 | 15 |
| |
| 95.91% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 75 | | matches | | 0 | "was slicked" | | 1 | "were fixed" | | 2 | "been driven" |
| |
| 51.02% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 4 | | totalVerbs | 179 | | matches | | 0 | "wasn’t expecting" | | 1 | "was, standing" | | 2 | "was already stepping" | | 3 | "was surveying" |
| |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 9 | | semicolonCount | 0 | | flaggedSentences | 7 | | totalSentences | 99 | | ratio | 0.071 | | matches | | 0 | "His platinum blond hair was slicked back, and his heterochromatic eyes—one amber, one black—were fixed on the door with a faint smirk tugging at the corner of his lips." | | 1 | "But she knew Lucien—he wasn’t the type to go away quietly." | | 2 | "It was a mess—books and papers everywhere, Ptolemy’s fur clinging to every surface." | | 3 | "Of course Eva would go after something like this—she’d always been driven by a fierce sense of justice, even if it meant putting herself in harm’s way." | | 4 | "Aurora’s chest tightened, the memories of their last encounter flooding back—the anger, the hurt, the way his voice had cracked when she’d walked out." | | 5 | "His scent—spicy and faintly metallic—filled the space between them." | | 6 | "It wasn’t forgiveness, not yet, but it was a start—a fragile, hesitant step toward something they’d both been too afraid to face." |
| |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 970 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 36 | | adverbRatio | 0.03711340206185567 | | lyAdverbCount | 14 | | lyAdverbRatio | 0.01443298969072165 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 99 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 99 | | mean | 12.81 | | std | 7.01 | | cv | 0.547 | | sampleLengths | | 0 | 14 | | 1 | 15 | | 2 | 21 | | 3 | 4 | | 4 | 19 | | 5 | 10 | | 6 | 25 | | 7 | 9 | | 8 | 15 | | 9 | 14 | | 10 | 15 | | 11 | 29 | | 12 | 6 | | 13 | 30 | | 14 | 17 | | 15 | 14 | | 16 | 8 | | 17 | 17 | | 18 | 11 | | 19 | 17 | | 20 | 6 | | 21 | 15 | | 22 | 12 | | 23 | 11 | | 24 | 8 | | 25 | 12 | | 26 | 9 | | 27 | 11 | | 28 | 10 | | 29 | 14 | | 30 | 3 | | 31 | 12 | | 32 | 6 | | 33 | 5 | | 34 | 8 | | 35 | 2 | | 36 | 3 | | 37 | 9 | | 38 | 12 | | 39 | 8 | | 40 | 13 | | 41 | 16 | | 42 | 17 | | 43 | 12 | | 44 | 20 | | 45 | 9 | | 46 | 16 | | 47 | 10 | | 48 | 9 | | 49 | 25 |
| |
| 74.41% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 3 | | diversityRatio | 0.46464646464646464 | | totalSentences | 99 | | uniqueOpeners | 46 | |
| 92.59% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 72 | | matches | | 0 | "Especially not at nine o’clock" | | 1 | "Of course Eva would go" |
| | ratio | 0.028 | |
| 14.44% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 37 | | totalSentences | 72 | | matches | | 0 | "She wasn’t expecting anyone." | | 1 | "She set the bowl down" | | 2 | "Her bare feet whispered against" | | 3 | "He wore his usual tailored" | | 4 | "His platinum blond hair was" | | 5 | "It had been six months" | | 6 | "She hesitated, her hand hovering" | | 7 | "His smirk widened into a" | | 8 | "She crossed her arms over" | | 9 | "He tilted his head, studying" | | 10 | "she said, her voice sharper" | | 11 | "His expression softened, the teasing" | | 12 | "She hated how easily he" | | 13 | "he interrupted gently" | | 14 | "He straightened, tapping his cane" | | 15 | "She hesitated again, glancing back" | | 16 | "It was a mess—books and" | | 17 | "She closed the door behind" | | 18 | "he said, his tone teasing" | | 19 | "He turned to face her," |
| | ratio | 0.514 | |
| 78.06% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 55 | | totalSentences | 72 | | matches | | 0 | "The knock came soft, almost" | | 1 | "Aurora froze, her spoon hovering" | | 2 | "Ptolemy, sprawled on the armchair" | | 3 | "She wasn’t expecting anyone." | | 4 | "Eva was in Edinburgh for" | | 5 | "She set the bowl down" | | 6 | "Her bare feet whispered against" | | 7 | "Lucien Moreau leaned casually against" | | 8 | "He wore his usual tailored" | | 9 | "His platinum blond hair was" | | 10 | "Aurora’s breath caught in her" | | 11 | "It had been six months" | | 12 | "She hesitated, her hand hovering" | | 13 | "Part of her wanted to" | | 14 | "His smirk widened into a" | | 15 | "She crossed her arms over" | | 16 | "He tilted his head, studying" | | 17 | "she said, her voice sharper" | | 18 | "His expression softened, the teasing" | | 19 | "Aurora’s jaw tightened." |
| | ratio | 0.764 | |
| 69.44% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 72 | | matches | | 0 | "Before she could say more," |
| | ratio | 0.014 | |
| 63.49% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 45 | | technicalSentenceCount | 5 | | matches | | 0 | "But he was already stepping past her, his cane clicking softly against the floor as he entered." | | 1 | "When she turned, he was surveying the room with quiet amusement, his gaze lingering on the half-eaten bowl of noodles." | | 2 | "The Enochian Codex was one of the most forbidden texts in the supernatural world, rumored to contain secrets that could unravel reality itself." | | 3 | "He hesitated, his gaze flickering to the floor before meeting hers again." | | 4 | "Before she could say more, he leaned in, his lips brushing against hers in a kiss that was soft, tentative, and full of all the things they’d left unsaid." |
| |
| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 16 | | uselessAdditionCount | 6 | | matches | | 0 | "she said, her voice sharper than she intended" | | 1 | "He trailed, his voice softening" | | 2 | "he countered, his voice firmer now" | | 3 | "she demanded, standing to face him" | | 4 | "he murmured, his gaze searching hers" | | 5 | "he promised, his voice steady" |
| |
| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 13 | | fancyCount | 7 | | fancyTags | | 0 | "he interrupted gently (interrupt)" | | 1 | "Aurora muttered (mutter)" | | 2 | "she admitted quietly (admit)" | | 3 | "she demanded (demand)" | | 4 | "he murmured (murmur)" | | 5 | "he whispered (whisper)" | | 6 | "he promised (promise)" |
| | dialogueSentences | 40 | | tagDensity | 0.325 | | leniency | 0.65 | | rawRatio | 0.538 | | effectiveRatio | 0.35 | |