| 57.14% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 21 | | adverbTagCount | 5 | | adverbTags | | 0 | "Rory stepped back [back]" | | 1 | "Lucien's fingers curled gently [gently]" | | 2 | "Rory asked quietly [quietly]" | | 3 | "she said softly [softly]" | | 4 | "Rory pulled back [back]" |
| | dialogueSentences | 70 | | tagDensity | 0.3 | | leniency | 0.6 | | rawRatio | 0.238 | | effectiveRatio | 0.143 | |
| 85.63% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1740 | | totalAiIsmAdverbs | 5 | | found | | 0 | | | 1 | | adverb | "deliberately" | | count | 1 |
| | 2 | | | 3 | |
| | highlights | | 0 | "slightly" | | 1 | "deliberately" | | 2 | "gently" | | 3 | "softly" |
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| 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) | |
| 71.26% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1740 | | totalAiIsms | 10 | | found | | | highlights | | 0 | "traced" | | 1 | "weight" | | 2 | "intensity" | | 3 | "stomach" | | 4 | "efficient" | | 5 | "flickered" | | 6 | "warmth" | | 7 | "silence" |
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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 | 2 | | narrationSentences | 116 | | matches | | 0 | "was angry" | | 1 | "was bitter" |
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| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 2 | | narrationSentences | 116 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 164 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 45 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1727 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 11 | | unquotedAttributions | 0 | | matches | (empty) | |
| 83.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 30 | | wordCount | 1219 | | uniqueNames | 5 | | maxNameDensity | 1.23 | | worstName | "Rory" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Rory" | | discoveredNames | | Rory | 15 | | Eva | 1 | | Lucien | 7 | | Ptolemy | 4 | | Three | 3 |
| | persons | | 0 | "Rory" | | 1 | "Eva" | | 2 | "Lucien" | | 3 | "Ptolemy" |
| | places | (empty) | | globalScore | 0.885 | | windowScore | 0.833 | |
| 86.71% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 79 | | glossingSentenceCount | 2 | | matches | | 0 | "wounds that seemed to follow her new life like a shadow" | | 1 | "something between a hiss and a gasp, and his ha" |
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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 | 1727 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 164 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 87 | | mean | 19.85 | | std | 16 | | cv | 0.806 | | sampleLengths | | 0 | 9 | | 1 | 44 | | 2 | 27 | | 3 | 6 | | 4 | 5 | | 5 | 40 | | 6 | 8 | | 7 | 4 | | 8 | 30 | | 9 | 11 | | 10 | 13 | | 11 | 42 | | 12 | 7 | | 13 | 40 | | 14 | 58 | | 15 | 34 | | 16 | 5 | | 17 | 28 | | 18 | 2 | | 19 | 15 | | 20 | 36 | | 21 | 19 | | 22 | 2 | | 23 | 51 | | 24 | 6 | | 25 | 47 | | 26 | 5 | | 27 | 24 | | 28 | 46 | | 29 | 2 | | 30 | 6 | | 31 | 16 | | 32 | 37 | | 33 | 36 | | 34 | 21 | | 35 | 5 | | 36 | 3 | | 37 | 23 | | 38 | 4 | | 39 | 15 | | 40 | 3 | | 41 | 7 | | 42 | 37 | | 43 | 9 | | 44 | 48 | | 45 | 40 | | 46 | 22 | | 47 | 28 | | 48 | 15 | | 49 | 49 |
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| 99.21% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 116 | | matches | | 0 | "was scraped" | | 1 | "was ruined" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 217 | | matches | | 0 | "was surveying" | | 1 | "were shaking" |
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| 55.75% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 8 | | semicolonCount | 0 | | flaggedSentences | 5 | | totalSentences | 164 | | ratio | 0.03 | | matches | | 0 | "The heterochromatic eyes—one amber, one black—held hers with an intensity that made her stomach twist." | | 1 | "Every surface still overflowed with Eva's research—leather-bound grimoires stacked on the kitchen counter, scrolls unfurled across the sofa, index cards pinned to every available wall space." | | 2 | "She pulled a first-aid kit from beneath the sink—one benefit of having a best friend who attracted supernatural trouble like pigeons to breadcrumbs—and set it on the scarred table between them." | | 3 | "Something flickered behind his eyes—surprise, perhaps, at the steel in her voice." | | 4 | "\"Three months, and you show up at Eva's door at—\" she glanced at the clock \"—eleven at night, looking like someone put you through a meat grinder, and you expect me to what? Just forget everything?\"" |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1183 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 44 | | adverbRatio | 0.037193575655114115 | | lyAdverbCount | 17 | | lyAdverbRatio | 0.014370245139475908 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 164 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 164 | | mean | 10.53 | | std | 8.11 | | cv | 0.77 | | sampleLengths | | 0 | 9 | | 1 | 24 | | 2 | 8 | | 3 | 12 | | 4 | 7 | | 5 | 2 | | 6 | 5 | | 7 | 13 | | 8 | 6 | | 9 | 5 | | 10 | 5 | | 11 | 20 | | 12 | 15 | | 13 | 8 | | 14 | 4 | | 15 | 30 | | 16 | 6 | | 17 | 2 | | 18 | 1 | | 19 | 1 | | 20 | 1 | | 21 | 13 | | 22 | 21 | | 23 | 21 | | 24 | 3 | | 25 | 4 | | 26 | 15 | | 27 | 25 | | 28 | 10 | | 29 | 8 | | 30 | 26 | | 31 | 14 | | 32 | 13 | | 33 | 16 | | 34 | 5 | | 35 | 5 | | 36 | 22 | | 37 | 6 | | 38 | 2 | | 39 | 12 | | 40 | 3 | | 41 | 7 | | 42 | 7 | | 43 | 22 | | 44 | 18 | | 45 | 1 | | 46 | 2 | | 47 | 31 | | 48 | 20 | | 49 | 6 |
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| 51.02% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 13 | | diversityRatio | 0.35365853658536583 | | totalSentences | 164 | | uniqueOpeners | 58 | |
| 31.15% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 107 | | matches | | 0 | "Instead, she reached out and" |
| | ratio | 0.009 | |
| 62.99% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 42 | | totalSentences | 107 | | matches | | 0 | "His ivory-handled cane hung crooked" | | 1 | "His voice scraped like gravel." | | 2 | "She noted the way he" | | 3 | "She moved to shut the" | | 4 | "His palm pressed against the" | | 5 | "He limped inside, his shoe" | | 6 | "She gestured at the droplets" | | 7 | "His jaw tightened, the muscle" | | 8 | "She pulled a first-aid kit" | | 9 | "His lip was split." | | 10 | "His right hand, braced against" | | 11 | "Her hands moved automatically, guided" | | 12 | "She met his gaze" | | 13 | "He shrugged out of the" | | 14 | "His fingers were shaking." | | 15 | "She made quick work of" | | 16 | "She'd seen him injured before." | | 17 | "It came with the territory" | | 18 | "She pressed her lips together" | | 19 | "She poured it directly onto" |
| | ratio | 0.393 | |
| 25.42% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 93 | | totalSentences | 107 | | matches | | 0 | "The third deadbolt clicked and" | | 1 | "Lucien stood in the corridor," | | 2 | "His ivory-handled cane hung crooked" | | 3 | "A fresh cut traced his" | | 4 | "Rory's grip tightened on the" | | 5 | "His voice scraped like gravel." | | 6 | "She noted the way he" | | 7 | "The heterochromatic eyes—one amber, one" | | 8 | "She moved to shut the" | | 9 | "His palm pressed against the" | | 10 | "The word cracked something in" | | 11 | "Ptolemy chose that moment to" | | 12 | "The tabby's tail brushed against" | | 13 | "Lucien's mouth twitched." | | 14 | "Rory stepped back and let" | | 15 | "He limped inside, his shoe" | | 16 | "The flat felt smaller with" | | 17 | "Every surface still overflowed with" | | 18 | "The smell of old paper" | | 19 | "Rory shut the door behind" |
| | ratio | 0.869 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 107 | | matches | (empty) | | ratio | 0 | |
| 79.37% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 45 | | technicalSentenceCount | 4 | | matches | | 0 | "The heterochromatic eyes—one amber, one black—held hers with an intensity that made her stomach twist." | | 1 | "She pulled a first-aid kit from beneath the sink—one benefit of having a best friend who attracted supernatural trouble like pigeons to breadcrumbs—and set it o…" | | 2 | "And beneath the ruined suit jacket, his white shirt bore a spreading stain that couldn't be anything but blood." | | 3 | "Her hands moved automatically, guided by months of patching up delivery drivers who'd taken spills on icy streets and, more recently, sewing shut the wounds tha…" |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 21 | | uselessAdditionCount | 1 | | matches | | 0 | "Rory said, not sorry at all" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 5 | | fancyCount | 2 | | fancyTags | | 0 | "Rory muttered (mutter)" | | 1 | "She snapped (snap)" |
| | dialogueSentences | 70 | | tagDensity | 0.071 | | leniency | 0.143 | | rawRatio | 0.4 | | effectiveRatio | 0.057 | |