| 27.59% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 25 | | adverbTagCount | 5 | | adverbTags | | 0 | "Lucien Moreau leaned heavily [heavily]" | | 1 | "Lucien corrected smoothly [smoothly]" | | 2 | "Lucien said finally [finally]" | | 3 | "Eva said softly [softly]" | | 4 | "Lucien said softly [softly]" |
| | dialogueSentences | 58 | | tagDensity | 0.431 | | leniency | 0.862 | | rawRatio | 0.2 | | effectiveRatio | 0.172 | |
| 64.79% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1278 | | totalAiIsmAdverbs | 9 | | found | | | highlights | | 0 | "really" | | 1 | "suddenly" | | 2 | "lightly" | | 3 | "softly" | | 4 | "very" | | 5 | "slightly" | | 6 | "completely" |
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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) | |
| 41.31% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1278 | | totalAiIsms | 15 | | found | | | highlights | | 0 | "velvet" | | 1 | "chaotic" | | 2 | "fascinating" | | 3 | "throbbed" | | 4 | "gleaming" | | 5 | "charged" | | 6 | "unreadable" | | 7 | "flicked" | | 8 | "facade" | | 9 | "warmth" | | 10 | "silence" | | 11 | "silk" | | 12 | "whisper" | | 13 | "shattered" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "clenched jaw/fists" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 58 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 58 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 91 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 38 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 1 | | markdownWords | 2 | | totalWords | 1278 | | ratio | 0.002 | | matches | | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 18 | | unquotedAttributions | 0 | | matches | (empty) | |
| 55.42% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 35 | | wordCount | 793 | | uniqueNames | 12 | | maxNameDensity | 1.89 | | worstName | "Lucien" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Lucien" | | discoveredNames | | Moreau | 1 | | Lucien | 15 | | Ptolemy | 2 | | Eva | 9 | | Persian | 1 | | One | 1 | | Brick | 1 | | Lane | 1 | | Mercedes | 1 | | London | 1 | | Silence | 1 | | Bengali | 1 |
| | persons | | 0 | "Moreau" | | 1 | "Lucien" | | 2 | "Ptolemy" | | 3 | "Eva" | | 4 | "Mercedes" | | 5 | "Silence" |
| | places | | 0 | "Brick" | | 1 | "Lane" | | 2 | "London" | | 3 | "Bengali" |
| | globalScore | 0.554 | | windowScore | 0.833 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 52 | | 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 | 1278 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 91 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 43 | | mean | 29.72 | | std | 17.07 | | cv | 0.574 | | sampleLengths | | 0 | 15 | | 1 | 32 | | 2 | 37 | | 3 | 56 | | 4 | 29 | | 5 | 23 | | 6 | 57 | | 7 | 40 | | 8 | 30 | | 9 | 56 | | 10 | 35 | | 11 | 30 | | 12 | 28 | | 13 | 43 | | 14 | 3 | | 15 | 2 | | 16 | 50 | | 17 | 14 | | 18 | 25 | | 19 | 24 | | 20 | 10 | | 21 | 49 | | 22 | 63 | | 23 | 25 | | 24 | 25 | | 25 | 45 | | 26 | 33 | | 27 | 8 | | 28 | 42 | | 29 | 35 | | 30 | 5 | | 31 | 66 | | 32 | 4 | | 33 | 8 | | 34 | 3 | | 35 | 39 | | 36 | 29 | | 37 | 22 | | 38 | 49 | | 39 | 11 | | 40 | 19 | | 41 | 31 | | 42 | 28 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 58 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 119 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 1 | | flaggedSentences | 1 | | totalSentences | 91 | | ratio | 0.011 | | matches | | 0 | "One eye shone bright amber in the dim light of the floor lamp; the other remained a deep, bottomless black." |
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| 70.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 802 | | adjectiveStacks | 5 | | stackExamples | | 0 | "burned behind thick black frames," | | 1 | "ancient bone-handled athame." | | 2 | "distinct, sharp metallic clicks." | | 3 | "heavy, iron-bound tomb" | | 4 | "small, silver-bound ledger" |
| | adverbCount | 24 | | adverbRatio | 0.029925187032418952 | | lyAdverbCount | 15 | | lyAdverbRatio | 0.018703241895261846 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 91 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 91 | | mean | 14.04 | | std | 6.65 | | cv | 0.474 | | sampleLengths | | 0 | 15 | | 1 | 16 | | 2 | 16 | | 3 | 22 | | 4 | 15 | | 5 | 14 | | 6 | 26 | | 7 | 16 | | 8 | 12 | | 9 | 17 | | 10 | 15 | | 11 | 8 | | 12 | 24 | | 13 | 19 | | 14 | 14 | | 15 | 13 | | 16 | 20 | | 17 | 7 | | 18 | 20 | | 19 | 10 | | 20 | 18 | | 21 | 20 | | 22 | 18 | | 23 | 16 | | 24 | 19 | | 25 | 12 | | 26 | 15 | | 27 | 3 | | 28 | 7 | | 29 | 12 | | 30 | 9 | | 31 | 19 | | 32 | 11 | | 33 | 13 | | 34 | 3 | | 35 | 2 | | 36 | 18 | | 37 | 27 | | 38 | 5 | | 39 | 14 | | 40 | 20 | | 41 | 5 | | 42 | 16 | | 43 | 8 | | 44 | 10 | | 45 | 18 | | 46 | 8 | | 47 | 23 | | 48 | 5 | | 49 | 18 |
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| 72.53% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 4 | | diversityRatio | 0.46153846153846156 | | totalSentences | 91 | | uniqueOpeners | 42 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 56 | | matches | (empty) | | ratio | 0 | |
| 55.71% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 23 | | totalSentences | 56 | | matches | | 0 | "Her dark eyes burned behind" | | 1 | "I stood squeezed between them" | | 2 | "I said, stepping past Lucien" | | 3 | "He took in the chaotic" | | 4 | "My left wrist throbbed with" | | 5 | "She looked at Lucien, really" | | 6 | "His cane made a dull" | | 7 | "I said, leaning my back" | | 8 | "My lungs still felt tight" | | 9 | "He took a single, quiet" | | 10 | "I whispered, holding my ground" | | 11 | "His black eye stayed locked" | | 12 | "He smelled of rain, expensive" | | 13 | "It was a scent that" | | 14 | "I pressed my hand against" | | 15 | "She dropped onto the sofa," | | 16 | "My voice cracked, sharp and" | | 17 | "I crossed the room before" | | 18 | "He down at me, his" | | 19 | "He gripped his cane so" |
| | ratio | 0.411 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 53 | | totalSentences | 56 | | matches | | 0 | "A brass blade pressed directly" | | 1 | "Her dark eyes burned behind" | | 2 | "Lucien Moreau leaned heavily on" | | 3 | "The bone blade lowered half" | | 4 | "I stood squeezed between them" | | 5 | "Downstairs, the kitchen hummed, but" | | 6 | "Eva shifted her glare to" | | 7 | "I said, stepping past Lucien" | | 8 | "Ptolemy, Eva's fat tabby cat," | | 9 | "Books covered every square inch" | | 10 | "Scrolls tied with faded red" | | 11 | "Lucien limped into the flat," | | 12 | "He took in the chaotic" | | 13 | "Eva snapped, bolting all three" | | 14 | "Lucien smoothed the front of" | | 15 | "My left wrist throbbed with" | | 16 | "Eva froze, the athame slipping" | | 17 | "She looked at Lucien, really" | | 18 | "Lucien corrected smoothly" | | 19 | "His cane made a dull" |
| | ratio | 0.946 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 56 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 29 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 25 | | uselessAdditionCount | 7 | | matches | | 0 | "Lucien Moreau leaned heavily, not even flinching at the sharp edge scraping his collar" | | 1 | "Eva shifted, her voice dropping an octave" | | 2 | "Eva froze, the athame slipping into a sheath at her waist" | | 3 | "Lucien turned, the amber eye catching the light, gleaming like polished gold" | | 4 | "Lucien said finally, his rich accent sliding over the syllables like oil" | | 5 | "Eva said softly, her face draining of color" | | 6 | "I asked, my voice barely a whisper" |
| |
| 46.55% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 14 | | fancyCount | 6 | | fancyTags | | 0 | "Eva spat (spit)" | | 1 | "Eva snapped (snap)" | | 2 | "Lucien corrected smoothly (correct)" | | 3 | "I whispered (whisper)" | | 4 | "I pressed (press)" | | 5 | "Lucien murmured (murmur)" |
| | dialogueSentences | 58 | | tagDensity | 0.241 | | leniency | 0.483 | | rawRatio | 0.429 | | effectiveRatio | 0.207 | |