| 97.44% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 10 | | adverbTagCount | 2 | | adverbTags | | 0 | "He stepped further [further]" | | 1 | "he said simply [simply]" |
| | dialogueSentences | 39 | | tagDensity | 0.256 | | leniency | 0.513 | | rawRatio | 0.2 | | effectiveRatio | 0.103 | |
| 84.03% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 626 | | 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) | |
| 84.03% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 626 | | totalAiIsms | 2 | | found | | | highlights | | |
| 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 | 37 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 37 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 66 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 31 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 622 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 13 | | unquotedAttributions | 0 | | matches | (empty) | |
| 79.78% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 12 | | wordCount | 356 | | uniqueNames | 6 | | maxNameDensity | 1.4 | | worstName | "Aurora" | | maxWindowNameDensity | 2 | | worstWindowName | "Aurora" | | discoveredNames | | Aurora | 5 | | Empress | 1 | | Eva | 3 | | Silas | 1 | | Evan | 1 | | Lucien | 1 |
| | persons | | 0 | "Aurora" | | 1 | "Eva" | | 2 | "Silas" | | 3 | "Evan" | | 4 | "Lucien" |
| | places | (empty) | | globalScore | 0.798 | | windowScore | 1 | |
| 41.30% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 23 | | glossingSentenceCount | 1 | | matches | | 0 | "smelled like last night's vindaloo every d" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 622 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 66 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 36 | | mean | 17.28 | | std | 10.51 | | cv | 0.608 | | sampleLengths | | 0 | 27 | | 1 | 1 | | 2 | 35 | | 3 | 3 | | 4 | 36 | | 5 | 23 | | 6 | 22 | | 7 | 38 | | 8 | 2 | | 9 | 2 | | 10 | 20 | | 11 | 29 | | 12 | 22 | | 13 | 11 | | 14 | 32 | | 15 | 6 | | 16 | 15 | | 17 | 23 | | 18 | 5 | | 19 | 19 | | 20 | 6 | | 21 | 32 | | 22 | 6 | | 23 | 20 | | 24 | 14 | | 25 | 20 | | 26 | 33 | | 27 | 19 | | 28 | 10 | | 29 | 15 | | 30 | 14 | | 31 | 13 | | 32 | 6 | | 33 | 11 | | 34 | 11 | | 35 | 21 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 37 | | matches | (empty) | |
| 88.89% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 60 | | matches | | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 5 | | semicolonCount | 0 | | flaggedSentences | 5 | | totalSentences | 66 | | ratio | 0.076 | | matches | | 0 | "Three months since her and Eva had sorted out the flat-sharing arrangement, three months since he'd last deigned to acknowledge her existence outside the bar's backdoor exchanges, three months since—" | | 1 | "She'd moved in above Silas's bar after the divorce, trading cramped student accommodation for something with character—or so she'd told herself." | | 2 | "Ptolemy—the tabby cat who'd moved in with Eva after the split, now somehow ended up in her new flat too?" | | 3 | "He smiled—that slow, dangerous thing that had gotten them both into trouble more than once." | | 4 | "The memory surfaced unbidden—Evan's shadow on the apartment wall, the way he'd slept with the lights off, the bruises that bloomed like dark flowers under her vigilance." |
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| 96.22% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 361 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 16 | | adverbRatio | 0.0443213296398892 | | lyAdverbCount | 3 | | lyAdverbRatio | 0.008310249307479225 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 66 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 66 | | mean | 9.42 | | std | 6.55 | | cv | 0.695 | | sampleLengths | | 0 | 16 | | 1 | 11 | | 2 | 1 | | 3 | 5 | | 4 | 30 | | 5 | 3 | | 6 | 8 | | 7 | 22 | | 8 | 6 | | 9 | 14 | | 10 | 8 | | 11 | 1 | | 12 | 15 | | 13 | 7 | | 14 | 7 | | 15 | 21 | | 16 | 10 | | 17 | 2 | | 18 | 2 | | 19 | 20 | | 20 | 3 | | 21 | 20 | | 22 | 6 | | 23 | 4 | | 24 | 18 | | 25 | 7 | | 26 | 4 | | 27 | 15 | | 28 | 17 | | 29 | 6 | | 30 | 15 | | 31 | 5 | | 32 | 13 | | 33 | 5 | | 34 | 5 | | 35 | 19 | | 36 | 3 | | 37 | 3 | | 38 | 23 | | 39 | 9 | | 40 | 6 | | 41 | 7 | | 42 | 13 | | 43 | 5 | | 44 | 7 | | 45 | 2 | | 46 | 10 | | 47 | 10 | | 48 | 27 | | 49 | 6 |
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| 75.25% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 2 | | diversityRatio | 0.4696969696969697 | | totalSentences | 66 | | uniqueOpeners | 31 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 35 | | matches | (empty) | | ratio | 0 | |
| 71.43% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 13 | | totalSentences | 35 | | matches | | 0 | "She stared at him, incredulous." | | 1 | "he said, pushing off the" | | 2 | "His platinum hair was perfectly" | | 3 | "She turned away, wiping sauce" | | 4 | "He stepped further inside, ivory" | | 5 | "She'd moved in above Silas's" | | 6 | "He smiled—that slow, dangerous thing" | | 7 | "He set the takeaway box" | | 8 | "His voice dropped low" | | 9 | "She turned, meeting his gaze." | | 10 | "He lifted his cane, the" | | 11 | "He tapped his temple" | | 12 | "he said simply" |
| | ratio | 0.371 | |
| 45.71% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 29 | | totalSentences | 35 | | matches | | 0 | "The door burst inward with" | | 1 | "She stared at him, incredulous." | | 2 | "he said, pushing off the" | | 3 | "His platinum hair was perfectly" | | 4 | "She turned away, wiping sauce" | | 5 | "The crescent scar felt tender" | | 6 | "He stepped further inside, ivory" | | 7 | "The flat reeked of cardamom" | | 8 | "She'd moved in above Silas's" | | 9 | "Truth was, it smelled like" | | 10 | "That stopped her." | | 11 | "Ptolemy—the tabby cat who'd moved" | | 12 | "Aurora's fingers tightened around the" | | 13 | "He smiled—that slow, dangerous thing" | | 14 | "The kettle began to whistle." | | 15 | "Aurora's breath hitched." | | 16 | "He set the takeaway box" | | 17 | "His voice dropped low" | | 18 | "She turned, meeting his gaze." | | 19 | "He lifted his cane, the" |
| | ratio | 0.829 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 35 | | matches | (empty) | | ratio | 0 | |
| 0.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 12 | | technicalSentenceCount | 3 | | matches | | 0 | "The door burst inward with a scrape of hinges that made Aurora drop the takeaway container." | | 1 | "His platinum hair was perfectly dishevelled, as if he'd just stepped out of a séance rather than barging into a stranger's flat." | | 2 | "The memory surfaced unbidden—Evan's shadow on the apartment wall, the way he'd slept with the lights off, the bruises that bloomed like dark flowers under her v…" |
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| 75.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 10 | | uselessAdditionCount | 1 | | matches | | 0 | "He lifted, the ivory handle gleaming" |
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| 73.08% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 5 | | fancyCount | 3 | | fancyTags | | 0 | "he corrected (correct)" | | 1 | "Eva's voice called out (call out)" | | 2 | "he hissed (hiss)" |
| | dialogueSentences | 39 | | tagDensity | 0.128 | | leniency | 0.256 | | rawRatio | 0.6 | | effectiveRatio | 0.154 | |