| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 21 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 48 | | tagDensity | 0.438 | | leniency | 0.875 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 95.89% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 2436 | | totalAiIsmAdverbs | 2 | | found | | | highlights | | |
| 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) | |
| 81.53% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 2436 | | totalAiIsms | 9 | | found | | | highlights | | 0 | "reminder" | | 1 | "sanctuary" | | 2 | "weight" | | 3 | "footsteps" | | 4 | "unreadable" | | 5 | "shattered" | | 6 | "lurched" |
| |
| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "knuckles turned white" | | count | 1 |
|
| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 447 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 2 | | narrationSentences | 447 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 474 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 29 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 2436 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 21 | | unquotedAttributions | 0 | | matches | (empty) | |
| 50.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 27 | | wordCount | 2197 | | uniqueNames | 6 | | maxNameDensity | 0.96 | | worstName | "Lucien" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Lucien" | | discoveredNames | | Moreau | 1 | | Frenchman | 1 | | Evan | 2 | | Cardiff | 1 | | Wales | 1 | | Lucien | 21 |
| | persons | | 0 | "Moreau" | | 1 | "Frenchman" | | 2 | "Evan" | | 3 | "Lucien" |
| | places | | | globalScore | 1 | | windowScore | 0.5 | |
| 66.67% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 90 | | glossingSentenceCount | 3 | | matches | | 0 | "smelled like magic and danger" | | 1 | "looked like ghosts in the hallway light" | | 2 | "looked like he hadn't fought at all" |
| |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 2436 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 474 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 274 | | mean | 8.89 | | std | 11.35 | | cv | 1.276 | | sampleLengths | | 0 | 75 | | 1 | 3 | | 2 | 57 | | 3 | 3 | | 4 | 54 | | 5 | 22 | | 6 | 33 | | 7 | 5 | | 8 | 61 | | 9 | 23 | | 10 | 39 | | 11 | 40 | | 12 | 4 | | 13 | 1 | | 14 | 2 | | 15 | 47 | | 16 | 2 | | 17 | 7 | | 18 | 12 | | 19 | 41 | | 20 | 45 | | 21 | 26 | | 22 | 9 | | 23 | 18 | | 24 | 4 | | 25 | 50 | | 26 | 16 | | 27 | 2 | | 28 | 23 | | 29 | 12 | | 30 | 6 | | 31 | 5 | | 32 | 3 | | 33 | 54 | | 34 | 6 | | 35 | 4 | | 36 | 6 | | 37 | 41 | | 38 | 5 | | 39 | 1 | | 40 | 5 | | 41 | 3 | | 42 | 25 | | 43 | 4 | | 44 | 35 | | 45 | 3 | | 46 | 41 | | 47 | 7 | | 48 | 18 | | 49 | 5 |
| |
| 39.33% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 84 | | totalSentences | 447 | | matches | | 0 | "was designed" | | 1 | "was slicked" | | 2 | "was gone" | | 3 | "was gone" | | 4 | "was gone" | | 5 | "was gone" | | 6 | "was gone" | | 7 | "was gone" | | 8 | "was gone" | | 9 | "was gone" | | 10 | "was gone" | | 11 | "was gone" | | 12 | "was gone" | | 13 | "was gone" | | 14 | "was gone" | | 15 | "was gone" | | 16 | "was gone" | | 17 | "was gone" | | 18 | "was gone" | | 19 | "was gone" | | 20 | "was gone" | | 21 | "was gone" | | 22 | "was gone" | | 23 | "was gone" | | 24 | "was gone" | | 25 | "was gone" | | 26 | "was gone" | | 27 | "was gone" | | 28 | "was gone" | | 29 | "was gone" | | 30 | "was gone" | | 31 | "was gone" | | 32 | "was gone" | | 33 | "was gone" | | 34 | "was gone" | | 35 | "was gone" | | 36 | "was gone" | | 37 | "was gone" | | 38 | "was gone" | | 39 | "was gone" | | 40 | "was gone" | | 41 | "was gone" | | 42 | "was gone" | | 43 | "was gone" | | 44 | "was gone" | | 45 | "was gone" | | 46 | "was gone" | | 47 | "was gone" | | 48 | "was gone" | | 49 | "was gone" | | 50 | "was gone" | | 51 | "was gone" | | 52 | "was gone" | | 53 | "was gone" | | 54 | "was gone" | | 55 | "was gone" | | 56 | "was gone" | | 57 | "was gone" | | 58 | "was gone" | | 59 | "was gone" | | 60 | "was gone" | | 61 | "was gone" | | 62 | "was gone" | | 63 | "was gone" | | 64 | "was gone" | | 65 | "was gone" | | 66 | "was gone" | | 67 | "was gone" | | 68 | "was gone" | | 69 | "was gone" | | 70 | "was gone" | | 71 | "was gone" | | 72 | "was gone" | | 73 | "was gone" | | 74 | "was gone" | | 75 | "was gone" | | 76 | "was gone" | | 77 | "was gone" | | 78 | "was gone" | | 79 | "was gone" | | 80 | "was gone" | | 81 | "was gone" | | 82 | "was gone" | | 83 | "was gone" |
| |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 3 | | totalVerbs | 504 | | matches | | 0 | "wasn't running" | | 1 | "was holding" | | 2 | "were glowing" |
| |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 474 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 2199 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 47 | | adverbRatio | 0.021373351523419737 | | lyAdverbCount | 7 | | lyAdverbRatio | 0.0031832651205093224 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 474 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 474 | | mean | 5.14 | | std | 3.81 | | cv | 0.741 | | sampleLengths | | 0 | 9 | | 1 | 17 | | 2 | 27 | | 3 | 22 | | 4 | 3 | | 5 | 4 | | 6 | 4 | | 7 | 21 | | 8 | 3 | | 9 | 3 | | 10 | 22 | | 11 | 3 | | 12 | 5 | | 13 | 29 | | 14 | 10 | | 15 | 10 | | 16 | 9 | | 17 | 4 | | 18 | 9 | | 19 | 13 | | 20 | 7 | | 21 | 9 | | 22 | 4 | | 23 | 5 | | 24 | 7 | | 25 | 15 | | 26 | 13 | | 27 | 26 | | 28 | 5 | | 29 | 12 | | 30 | 6 | | 31 | 8 | | 32 | 5 | | 33 | 14 | | 34 | 12 | | 35 | 5 | | 36 | 1 | | 37 | 9 | | 38 | 13 | | 39 | 12 | | 40 | 4 | | 41 | 1 | | 42 | 2 | | 43 | 15 | | 44 | 6 | | 45 | 6 | | 46 | 14 | | 47 | 6 | | 48 | 2 | | 49 | 7 |
| |
| 27.22% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 108 | | diversityRatio | 0.08227848101265822 | | totalSentences | 474 | | uniqueOpeners | 39 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 418 | | matches | (empty) | | ratio | 0 | |
| 13.30% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 216 | | totalSentences | 418 | | matches | | 0 | "I scrubbed the stain on" | | 1 | "My knuckles turned white as" | | 2 | "I froze, rag mid-wipe." | | 3 | "She had a spare key," | | 4 | "I turned slowly." | | 5 | "He wore a tailored charcoal" | | 6 | "His heterochromatic eyes, one amber," | | 7 | "He looked tired, and I" | | 8 | "My voice didn't shake." | | 9 | "I had learned not to" | | 10 | "He stepped inside, the toe" | | 11 | "He didn't close the door" | | 12 | "He just stood there, like" | | 13 | "I had been hiding the" | | 14 | "I picked up the rag" | | 15 | "He reached into his jacket" | | 16 | "His movements were slow, deliberate." | | 17 | "I tensed, my hand instinctively" | | 18 | "He closed it around the" | | 19 | "It was ivory, smooth and" |
| | ratio | 0.517 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 411 | | totalSentences | 418 | | matches | | 0 | "I scrubbed the stain on" | | 1 | "The mark was stubborn, a" | | 2 | "My knuckles turned white as" | | 3 | "The smell of spiced oil" | | 4 | "The handle turned." | | 5 | "I froze, rag mid-wipe." | | 6 | "Eva had the keys." | | 7 | "She had a spare key," | | 8 | "The deadbolt clicked." | | 9 | "The lock was designed to" | | 10 | "I turned slowly." | | 11 | "Lucien Moreau filled the doorway." | | 12 | "He wore a tailored charcoal" | | 13 | "His heterochromatic eyes, one amber," | | 14 | "He looked tired, and I" | | 15 | "My voice didn't shake." | | 16 | "I had learned not to" | | 17 | "He stepped inside, the toe" | | 18 | "He didn't close the door" | | 19 | "He just stood there, like" |
| | ratio | 0.983 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 418 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 35 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 21 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 16 | | fancyCount | 1 | | fancyTags | | 0 | "Lucien shouted (shout)" |
| | dialogueSentences | 48 | | tagDensity | 0.333 | | leniency | 0.667 | | rawRatio | 0.063 | | effectiveRatio | 0.042 | |