| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 7 | | adverbTagCount | 1 | | adverbTags | | 0 | "he said slowly [slowly]" |
| | dialogueSentences | 27 | | tagDensity | 0.259 | | leniency | 0.519 | | rawRatio | 0.143 | | effectiveRatio | 0.074 | |
| 85.42% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 686 | | 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) | |
| 63.56% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 686 | | totalAiIsms | 5 | | found | | | highlights | | 0 | "glistening" | | 1 | "flicked" | | 2 | "stomach" | | 3 | "weight" |
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| 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 | 61 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 61 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 82 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 35 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 1 | | markdownWords | 9 | | totalWords | 680 | | ratio | 0.013 | | matches | | 0 | "Don’t ask questions you don’t want answers to, Rory." |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 4 | | unquotedAttributions | 0 | | matches | (empty) | |
| 46.03% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 27 | | wordCount | 529 | | uniqueNames | 7 | | maxNameDensity | 2.08 | | worstName | "Rory" | | maxWindowNameDensity | 3 | | worstWindowName | "Rory" | | discoveredNames | | Eva | 3 | | Rory | 11 | | Moreau | 1 | | Lucien | 7 | | French | 1 | | Evan | 1 | | Ptolemy | 3 |
| | persons | | 0 | "Eva" | | 1 | "Rory" | | 2 | "Moreau" | | 3 | "Lucien" | | 4 | "Evan" | | 5 | "Ptolemy" |
| | places | (empty) | | globalScore | 0.46 | | windowScore | 0.667 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 36 | | 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 | 680 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 82 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 37 | | mean | 18.38 | | std | 13.97 | | cv | 0.76 | | sampleLengths | | 0 | 43 | | 1 | 49 | | 2 | 5 | | 3 | 45 | | 4 | 9 | | 5 | 6 | | 6 | 12 | | 7 | 31 | | 8 | 22 | | 9 | 13 | | 10 | 41 | | 11 | 15 | | 12 | 17 | | 13 | 8 | | 14 | 51 | | 15 | 3 | | 16 | 7 | | 17 | 5 | | 18 | 20 | | 19 | 9 | | 20 | 27 | | 21 | 4 | | 22 | 7 | | 23 | 14 | | 24 | 3 | | 25 | 13 | | 26 | 33 | | 27 | 12 | | 28 | 16 | | 29 | 40 | | 30 | 4 | | 31 | 27 | | 32 | 17 | | 33 | 5 | | 34 | 9 | | 35 | 18 | | 36 | 20 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 61 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 93 | | matches | (empty) | |
| 38.33% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 3 | | semicolonCount | 0 | | flaggedSentences | 3 | | totalSentences | 82 | | ratio | 0.037 | | matches | | 0 | "The knock came at midnight—three sharp raps that cut through the hum of Eva’s ancient refrigerator." | | 1 | "He took up space without trying—the crisp scent of bergamot and something darker cutting through the usual smells of old books and takeout." | | 2 | "Lucien’s gaze flicked to her wrist—to the crescent scar she knew he’d noticed the first time they met." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 374 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 8 | | adverbRatio | 0.0213903743315508 | | lyAdverbCount | 1 | | lyAdverbRatio | 0.00267379679144385 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 82 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 82 | | mean | 8.29 | | std | 6.12 | | cv | 0.738 | | sampleLengths | | 0 | 16 | | 1 | 10 | | 2 | 6 | | 3 | 11 | | 4 | 6 | | 5 | 19 | | 6 | 11 | | 7 | 13 | | 8 | 5 | | 9 | 13 | | 10 | 17 | | 11 | 15 | | 12 | 9 | | 13 | 6 | | 14 | 3 | | 15 | 9 | | 16 | 2 | | 17 | 15 | | 18 | 6 | | 19 | 4 | | 20 | 4 | | 21 | 13 | | 22 | 9 | | 23 | 10 | | 24 | 3 | | 25 | 8 | | 26 | 23 | | 27 | 10 | | 28 | 13 | | 29 | 2 | | 30 | 12 | | 31 | 5 | | 32 | 4 | | 33 | 4 | | 34 | 4 | | 35 | 11 | | 36 | 3 | | 37 | 24 | | 38 | 9 | | 39 | 3 | | 40 | 7 | | 41 | 5 | | 42 | 2 | | 43 | 14 | | 44 | 4 | | 45 | 4 | | 46 | 5 | | 47 | 17 | | 48 | 2 | | 49 | 8 |
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| 56.50% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 2 | | diversityRatio | 0.35365853658536583 | | totalSentences | 82 | | uniqueOpeners | 29 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 52 | | matches | | 0 | "Of course he had." | | 1 | "Just like the last time" |
| | ratio | 0.038 | |
| 73.85% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 19 | | totalSentences | 52 | | matches | | 0 | "He darted under the sofa" | | 1 | "She didn’t reach for the" | | 2 | "She peered through the peephole." | | 3 | "His charcoal suit was immaculate" | | 4 | "His mouth twitched." | | 5 | "She crossed her arms." | | 6 | "He took up space without" | | 7 | "He caught it one-handed." | | 8 | "She hadn’t listened." | | 9 | "he said without looking up" | | 10 | "He folded the towel neatly" | | 11 | "His voice dropped, the French" | | 12 | "Her stomach twisted." | | 13 | "She moved toward the door" | | 14 | "Her fingers curled around the" | | 15 | "he said slowly" | | 16 | "She remembered the weight of" | | 17 | "She reached past him for" | | 18 | "His breath hitched." |
| | ratio | 0.365 | |
| 27.31% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 45 | | totalSentences | 52 | | matches | | 0 | "The knock came at midnight—three" | | 1 | "Rory froze mid-sip, the lukewarm" | | 2 | "Ptolemy’s ears flattened against his" | | 3 | "He darted under the sofa" | | 4 | "She didn’t reach for the" | | 5 | "Something in the rhythm of" | | 6 | "She peered through the peephole." | | 7 | "Lucien Moreau stood on the" | | 8 | "His charcoal suit was immaculate" | | 9 | "The amber and black of" | | 10 | "Rory exhaled through her nose" | | 11 | "His mouth twitched." | | 12 | "The scar on her wrist" | | 13 | "She crossed her arms." | | 14 | "Lucien leaned on his cane," | | 15 | "Rainwater dripped from his sleeve" | | 16 | "Rory stepped aside." | | 17 | "The flat felt smaller with" | | 18 | "He took up space without" | | 19 | "Ptolemy emerged just enough to" |
| | ratio | 0.865 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 52 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 23 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 7 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 3 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 27 | | tagDensity | 0.111 | | leniency | 0.222 | | rawRatio | 0 | | effectiveRatio | 0 | |