| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 6 | | adverbTagCount | 1 | | adverbTags | | 0 | "He hesitated then [then]" |
| | dialogueSentences | 24 | | tagDensity | 0.25 | | leniency | 0.5 | | rawRatio | 0.167 | | effectiveRatio | 0.083 | |
| 81.66% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 818 | | totalAiIsmAdverbs | 3 | | found | | 0 | | | 1 | | adverb | "barely above a whisper" | | count | 1 |
|
| | highlights | | 0 | "really" | | 1 | "barely above a whisper" |
| |
| 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) | |
| 51.10% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 818 | | totalAiIsms | 8 | | found | | | highlights | | 0 | "echoed" | | 1 | "pounding" | | 2 | "dance" | | 3 | "velvet" | | 4 | "eyebrow" | | 5 | "reminder" | | 6 | "whisper" |
| |
| 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 | 50 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 50 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 68 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 37 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 813 | | ratio | 0 | | matches | (empty) | |
| 97.22% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 9 | | unquotedAttributions | 1 | | matches | | 0 | "But she would be careful, she told herself as they stepped out into the night." |
| |
| 50.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 24 | | wordCount | 610 | | uniqueNames | 4 | | maxNameDensity | 1.8 | | worstName | "Rory" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Rory" | | discoveredNames | | Rory | 11 | | London | 1 | | Eva | 1 | | Lucien | 11 |
| | persons | | | places | | | globalScore | 0.598 | | windowScore | 0.5 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 41 | | 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 | 813 | | matches | (empty) | |
| 68.63% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 2 | | totalSentences | 68 | | matches | | 0 | "feel that spark" | | 1 | "knew that she" |
| |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 31 | | mean | 26.23 | | std | 16.9 | | cv | 0.644 | | sampleLengths | | 0 | 70 | | 1 | 1 | | 2 | 31 | | 3 | 16 | | 4 | 46 | | 5 | 29 | | 6 | 20 | | 7 | 55 | | 8 | 19 | | 9 | 20 | | 10 | 6 | | 11 | 9 | | 12 | 13 | | 13 | 20 | | 14 | 26 | | 15 | 23 | | 16 | 3 | | 17 | 19 | | 18 | 30 | | 19 | 45 | | 20 | 12 | | 21 | 22 | | 22 | 34 | | 23 | 18 | | 24 | 56 | | 25 | 23 | | 26 | 12 | | 27 | 45 | | 28 | 37 | | 29 | 49 | | 30 | 4 |
| |
| 98.25% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 50 | | matches | | |
| 14.81% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 3 | | totalVerbs | 108 | | matches | | 0 | "was walking" | | 1 | "was calling" | | 2 | "was standing" |
| |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 1 | | semicolonCount | 0 | | flaggedSentences | 1 | | totalSentences | 68 | | ratio | 0.015 | | matches | | 0 | "She glanced at the clock—nearly midnight." |
| |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 615 | | adjectiveStacks | 1 | | stackExamples | | 0 | "small crescent-shaped scar" |
| | adverbCount | 20 | | adverbRatio | 0.032520325203252036 | | lyAdverbCount | 4 | | lyAdverbRatio | 0.0065040650406504065 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 68 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 68 | | mean | 11.96 | | std | 7.25 | | cv | 0.606 | | sampleLengths | | 0 | 14 | | 1 | 6 | | 2 | 10 | | 3 | 17 | | 4 | 15 | | 5 | 8 | | 6 | 1 | | 7 | 20 | | 8 | 11 | | 9 | 11 | | 10 | 5 | | 11 | 23 | | 12 | 9 | | 13 | 9 | | 14 | 5 | | 15 | 24 | | 16 | 5 | | 17 | 8 | | 18 | 12 | | 19 | 8 | | 20 | 17 | | 21 | 14 | | 22 | 16 | | 23 | 19 | | 24 | 10 | | 25 | 10 | | 26 | 4 | | 27 | 2 | | 28 | 2 | | 29 | 7 | | 30 | 8 | | 31 | 5 | | 32 | 16 | | 33 | 4 | | 34 | 26 | | 35 | 4 | | 36 | 19 | | 37 | 2 | | 38 | 1 | | 39 | 4 | | 40 | 15 | | 41 | 8 | | 42 | 22 | | 43 | 15 | | 44 | 19 | | 45 | 11 | | 46 | 12 | | 47 | 3 | | 48 | 19 | | 49 | 17 |
| |
| 60.78% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 2 | | diversityRatio | 0.38235294117647056 | | totalSentences | 68 | | uniqueOpeners | 26 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 47 | | matches | (empty) | | ratio | 0 | |
| 66.81% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 18 | | totalSentences | 47 | | matches | | 0 | "She glanced at the clock—nearly" | | 1 | "She crossed the room, her" | | 2 | "She hadn't seen him since" | | 3 | "She took a deep breath," | | 4 | "she said, her voice steady" | | 5 | "He leaned against the doorframe," | | 6 | "His heterochromatic eyes, one amber," | | 7 | "he said, his voice as" | | 8 | "She bristled at the use" | | 9 | "He pushed off from the" | | 10 | "he commented, running a finger" | | 11 | "She crossed her arms, leaning" | | 12 | "He hesitated, then said," | | 13 | "She sighed, running a hand" | | 14 | "she asked, her voice barely" | | 15 | "It was good to see" | | 16 | "She pushed off from the" | | 17 | "She would keep her distance," |
| | ratio | 0.383 | |
| 66.38% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 37 | | totalSentences | 47 | | matches | | 0 | "The knock echoed through the" | | 1 | "She glanced at the clock—nearly" | | 2 | "She crossed the room, her" | | 3 | "A man stood in the" | | 4 | "She hadn't seen him since" | | 5 | "She took a deep breath," | | 6 | "she said, her voice steady" | | 7 | "He leaned against the doorframe," | | 8 | "His heterochromatic eyes, one amber," | | 9 | "he said, his voice as" | | 10 | "She bristled at the use" | | 11 | "He pushed off from the" | | 12 | "Rory hesitated, then stepped aside," | | 13 | "The flat was small, little" | | 14 | "Books and research notes were" | | 15 | "Lucien's gaze swept over the" | | 16 | "he commented, running a finger" | | 17 | "Rory said, closing the door" | | 18 | "Lucien raised an eyebrow." | | 19 | "Lucien turned to face her," |
| | ratio | 0.787 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 47 | | matches | | 0 | "Because she knew, better than" |
| | ratio | 0.021 | |
| 60.44% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 26 | | technicalSentenceCount | 3 | | matches | | 0 | "She crossed her arms, leaning against the counter that separated the kitchen from the living area." | | 1 | "A memento from her childhood, a reminder of the darkness that had always been a part of her life." | | 2 | "Rory rolled her eyes at the use of her alias, but she couldn't help the small smile that tugged at the corners of her mouth." |
| |
| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 6 | | uselessAdditionCount | 2 | | matches | | 0 | "she said, her voice steady despite the turmoil inside her" | | 1 | "she asked, her voice barely above a whisper" |
| |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 5 | | fancyCount | 1 | | fancyTags | | 0 | "he commented (comment)" |
| | dialogueSentences | 24 | | tagDensity | 0.208 | | leniency | 0.417 | | rawRatio | 0.2 | | effectiveRatio | 0.083 | |