| 90.91% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 19 | | adverbTagCount | 3 | | adverbTags | | 0 | "She gestured around [around]" | | 1 | "she said quietly [quietly]" | | 2 | "He stopped abruptly [abruptly]" |
| | dialogueSentences | 55 | | tagDensity | 0.345 | | leniency | 0.691 | | rawRatio | 0.158 | | effectiveRatio | 0.109 | |
| 67.24% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1221 | | totalAiIsmAdverbs | 8 | | found | | | highlights | | 0 | "carefully" | | 1 | "slightly" | | 2 | "really" |
| |
| 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) | |
| 1.72% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1221 | | totalAiIsms | 24 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | word | "down her spine" | | count | 1 |
| | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | | | 13 | | | 14 | | | 15 | | | 16 | | | 17 | | | 18 | |
| | highlights | | 0 | "constructed" | | 1 | "comfortable" | | 2 | "familiar" | | 3 | "intensity" | | 4 | "flicker" | | 5 | "unreadable" | | 6 | "down her spine" | | 7 | "echoed" | | 8 | "fleeting" | | 9 | "reminder" | | 10 | "complex" | | 11 | "flickered" | | 12 | "chaotic" | | 13 | "silence" | | 14 | "unspoken" | | 15 | "traced" | | 16 | "resolve" | | 17 | "whisper" | | 18 | "tension" |
| |
| 66.67% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 2 | | maxInWindow | 2 | | found | | 0 | | label | "sent a shiver through" | | count | 1 |
| | 1 | | label | "flicker of emotion" | | count | 1 |
|
| | highlights | | 0 | "sent a shiver down" | | 1 | "a flicker of amusement" |
| |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 97 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 2 | | narrationSentences | 97 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 131 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 24 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 6 | | markdownWords | 6 | | totalWords | 1218 | | ratio | 0.005 | | matches | | 0 | "into" | | 1 | "chérie" | | 2 | "were" | | 3 | "Eva" | | 4 | "get" | | 5 | "him" |
| |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 17 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 23 | | wordCount | 861 | | uniqueNames | 7 | | maxNameDensity | 0.81 | | worstName | "Lucien" | | maxWindowNameDensity | 2 | | worstWindowName | "Rory" | | discoveredNames | | Rory | 6 | | Eva | 4 | | French | 1 | | Lucien | 7 | | Books | 1 | | Silence | 1 | | Six | 3 |
| | persons | | 0 | "Rory" | | 1 | "Eva" | | 2 | "Lucien" | | 3 | "Books" | | 4 | "Silence" |
| | places | (empty) | | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 70 | | glossingSentenceCount | 1 | | matches | | 0 | "as if gauging her reaction" |
| |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1218 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 131 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 56 | | mean | 21.75 | | std | 14.78 | | cv | 0.679 | | sampleLengths | | 0 | 65 | | 1 | 4 | | 2 | 48 | | 3 | 30 | | 4 | 33 | | 5 | 16 | | 6 | 44 | | 7 | 11 | | 8 | 21 | | 9 | 18 | | 10 | 32 | | 11 | 15 | | 12 | 19 | | 13 | 65 | | 14 | 9 | | 15 | 21 | | 16 | 39 | | 17 | 9 | | 18 | 5 | | 19 | 23 | | 20 | 40 | | 21 | 8 | | 22 | 4 | | 23 | 14 | | 24 | 47 | | 25 | 24 | | 26 | 19 | | 27 | 22 | | 28 | 8 | | 29 | 37 | | 30 | 31 | | 31 | 16 | | 32 | 24 | | 33 | 8 | | 34 | 10 | | 35 | 17 | | 36 | 14 | | 37 | 15 | | 38 | 55 | | 39 | 22 | | 40 | 12 | | 41 | 3 | | 42 | 15 | | 43 | 9 | | 44 | 9 | | 45 | 7 | | 46 | 1 | | 47 | 31 | | 48 | 12 | | 49 | 21 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 97 | | matches | | |
| 70.13% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 3 | | totalVerbs | 154 | | matches | | 0 | "was doing" | | 1 | "was standing" | | 2 | "was hammering" |
| |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 1 | | semicolonCount | 0 | | flaggedSentences | 1 | | totalSentences | 131 | | ratio | 0.008 | | matches | | 0 | "The tailored charcoal suit, the slicked-back platinum blond hair, the faintly amused expression – it was all infuriatingly familiar." |
| |
| 66.87% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 863 | | adjectiveStacks | 1 | | stackExamples | | 0 | "small crescent-shaped scar." |
| | adverbCount | 52 | | adverbRatio | 0.06025492468134415 | | lyAdverbCount | 27 | | lyAdverbRatio | 0.031286210892236384 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 131 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 131 | | mean | 9.3 | | std | 5.38 | | cv | 0.579 | | sampleLengths | | 0 | 8 | | 1 | 14 | | 2 | 8 | | 3 | 5 | | 4 | 6 | | 5 | 13 | | 6 | 11 | | 7 | 4 | | 8 | 10 | | 9 | 1 | | 10 | 15 | | 11 | 19 | | 12 | 3 | | 13 | 6 | | 14 | 8 | | 15 | 9 | | 16 | 7 | | 17 | 16 | | 18 | 17 | | 19 | 10 | | 20 | 6 | | 21 | 11 | | 22 | 8 | | 23 | 10 | | 24 | 15 | | 25 | 11 | | 26 | 9 | | 27 | 12 | | 28 | 9 | | 29 | 9 | | 30 | 4 | | 31 | 6 | | 32 | 2 | | 33 | 2 | | 34 | 3 | | 35 | 15 | | 36 | 4 | | 37 | 7 | | 38 | 4 | | 39 | 19 | | 40 | 22 | | 41 | 11 | | 42 | 17 | | 43 | 12 | | 44 | 3 | | 45 | 9 | | 46 | 21 | | 47 | 13 | | 48 | 3 | | 49 | 7 |
| |
| 46.82% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 12 | | diversityRatio | 0.33587786259541985 | | totalSentences | 131 | | uniqueOpeners | 44 | |
| 74.91% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 89 | | matches | | 0 | "Instead, he walked further into" | | 1 | "Then, he stepped closer, closing" |
| | ratio | 0.022 | |
| 0.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 54 | | totalSentences | 89 | | matches | | 0 | "She braced herself, hand hovering" | | 1 | "It had been six months." | | 2 | "She turned the knob." | | 3 | "He was leaning against the" | | 4 | "He hadn’t changed a damn" | | 5 | "he said, his voice a" | | 6 | "She swallowed, forcing words past" | | 7 | "He pushed himself off the" | | 8 | "He didn’t step *into* the" | | 9 | "He remained on the threshold," | | 10 | "He held his ivory-handled cane" | | 11 | "she echoed, skepticism dripping from" | | 12 | "She glared at him." | | 13 | "He was doing it on" | | 14 | "He always did." | | 15 | "His expression sobered slightly." | | 16 | "She instinctively pulled her sleeve" | | 17 | "He’d seen it countless times," | | 18 | "It was a reminder of" | | 19 | "She attracted trouble." |
| | ratio | 0.607 | |
| 10.56% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 80 | | totalSentences | 89 | | matches | | 0 | "The third deadbolt clicked, then" | | 1 | "Eva never skimped on security," | | 2 | "She braced herself, hand hovering" | | 3 | "It had been six months." | | 4 | "She turned the knob." | | 5 | "He was leaning against the" | | 6 | "The tailored charcoal suit, the" | | 7 | "He hadn’t changed a damn" | | 8 | "The amber one seemed to" | | 9 | "The black one was unreadable," | | 10 | "he said, his voice a" | | 11 | "The accent was still thick," | | 12 | "She swallowed, forcing words past" | | 13 | "He pushed himself off the" | | 14 | "He didn’t step *into* the" | | 15 | "He remained on the threshold," | | 16 | "He held his ivory-handled cane" | | 17 | "she echoed, skepticism dripping from" | | 18 | "A ghost of a smile" | | 19 | "She glared at him." |
| | ratio | 0.899 | |
| 56.18% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 89 | | matches | | 0 | "Even after all this time," |
| | ratio | 0.011 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 30 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 19 | | uselessAdditionCount | 7 | | matches | | 0 | "she echoed, skepticism dripping from her voice" | | 1 | "she said, her voice softening slightly" | | 2 | "she said, her voice rising again" | | 3 | "she said quietly, the words barely a whisper" | | 4 | "Rory said, her voice trembling slightly" | | 5 | "she said, her voice barely audible" | | 6 | "he said, his voice rough with emotion" |
| |
| 95.45% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 10 | | fancyCount | 3 | | fancyTags | | 0 | "Lucien admitted (admit)" | | 1 | "Rory muttered (mutter)" | | 2 | "she protested (protest)" |
| | dialogueSentences | 55 | | tagDensity | 0.182 | | leniency | 0.364 | | rawRatio | 0.3 | | effectiveRatio | 0.109 | |