| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 21 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 42 | | tagDensity | 0.5 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 87.83% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 822 | | totalAiIsmAdverbs | 2 | | found | | | highlights | | |
| 100.00% | AI-ism character names | Target: 0 AI-default names (16 tracked, −20% each) | | codexExemptions | | | found | (empty) | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 63.50% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 822 | | totalAiIsms | 6 | | found | | | highlights | | 0 | "tracing" | | 1 | "weight" | | 2 | "traced" | | 3 | "tension" | | 4 | "intensity" | | 5 | "unspoken" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "blood ran cold" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 43 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 43 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 64 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 32 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 820 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 10 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 13 | | wordCount | 555 | | uniqueNames | 8 | | maxNameDensity | 0.54 | | worstName | "London" | | maxWindowNameDensity | 1 | | worstWindowName | "London" | | discoveredNames | | Raven | 1 | | Nest | 1 | | London | 3 | | Silas | 3 | | Golden | 1 | | Empress | 1 | | Cardiff | 2 | | Prague | 1 |
| | persons | | 0 | "Raven" | | 1 | "Silas" | | 2 | "Empress" |
| | places | | 0 | "London" | | 1 | "Cardiff" | | 2 | "Prague" |
| | globalScore | 1 | | windowScore | 1 | |
| 87.50% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 40 | | glossingSentenceCount | 1 | | matches | | 0 | "felt like a marker of all the things I'" |
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| 78.05% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 1.22 | | wordCount | 820 | | matches | | 0 | "not understanding their importance but knowing they weren't meant for public eyes" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 64 | | matches | (empty) | |
| 94.54% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 32 | | mean | 25.63 | | std | 12.32 | | cv | 0.481 | | sampleLengths | | 0 | 49 | | 1 | 36 | | 2 | 20 | | 3 | 16 | | 4 | 27 | | 5 | 28 | | 6 | 21 | | 7 | 28 | | 8 | 26 | | 9 | 11 | | 10 | 27 | | 11 | 32 | | 12 | 25 | | 13 | 22 | | 14 | 29 | | 15 | 10 | | 16 | 36 | | 17 | 7 | | 18 | 18 | | 19 | 45 | | 20 | 19 | | 21 | 21 | | 22 | 21 | | 23 | 49 | | 24 | 8 | | 25 | 16 | | 26 | 30 | | 27 | 56 | | 28 | 14 | | 29 | 9 | | 30 | 23 | | 31 | 41 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 43 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 93 | | matches | (empty) | |
| 8.93% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 2 | | semicolonCount | 1 | | flaggedSentences | 3 | | totalSentences | 64 | | ratio | 0.047 | | matches | | 0 | "His hazel eyes caught the light as he inspected the contents—Golden Empress's special fried rice, extra chilli, no mushrooms." | | 1 | "The memory hit me like a physical blow—the day I'd found his hidden documents, not understanding their importance but knowing they weren't meant for public eyes." | | 2 | "The past wasn't just a country we'd left behind; it was a shadow that followed us into every new room." |
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| 99.13% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 561 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 23 | | adverbRatio | 0.040998217468805706 | | lyAdverbCount | 6 | | lyAdverbRatio | 0.0106951871657754 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 64 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 64 | | mean | 12.81 | | std | 7.59 | | cv | 0.592 | | sampleLengths | | 0 | 25 | | 1 | 24 | | 2 | 17 | | 3 | 19 | | 4 | 16 | | 5 | 4 | | 6 | 6 | | 7 | 10 | | 8 | 19 | | 9 | 8 | | 10 | 16 | | 11 | 12 | | 12 | 17 | | 13 | 4 | | 14 | 10 | | 15 | 18 | | 16 | 20 | | 17 | 6 | | 18 | 9 | | 19 | 2 | | 20 | 16 | | 21 | 11 | | 22 | 28 | | 23 | 4 | | 24 | 14 | | 25 | 11 | | 26 | 5 | | 27 | 17 | | 28 | 18 | | 29 | 11 | | 30 | 10 | | 31 | 15 | | 32 | 21 | | 33 | 4 | | 34 | 3 | | 35 | 12 | | 36 | 6 | | 37 | 26 | | 38 | 18 | | 39 | 1 | | 40 | 19 | | 41 | 12 | | 42 | 9 | | 43 | 11 | | 44 | 8 | | 45 | 2 | | 46 | 29 | | 47 | 20 | | 48 | 8 | | 49 | 12 |
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| 92.71% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 4 | | diversityRatio | 0.59375 | | totalSentences | 64 | | uniqueOpeners | 38 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 42 | | matches | (empty) | | ratio | 0 | |
| 0.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 29 | | totalSentences | 42 | | matches | | 0 | "I called out, sliding a" | | 1 | "His hazel eyes caught the" | | 2 | "His voice was deeper than" | | 3 | "I froze, my rag hovering" | | 4 | "He chuckled, a sound that" | | 5 | "I forced a smile, my" | | 6 | "He gestured to the stool" | | 7 | "I hesitated, weighing the risk" | | 8 | "His eyes searched my face," | | 9 | "I traced the crescent-shaped scar" | | 10 | "He swirled the whisky, the" | | 11 | "I met his gaze directly." | | 12 | "He leaned forward, his signet" | | 13 | "His gaze dropped to my" | | 14 | "My blood ran cold." | | 15 | "He smiled, but it didn't" | | 16 | "He'd caught me, of course," | | 17 | "I kept my voice even," | | 18 | "He took a slow sip" | | 19 | "I watched him move behind" |
| | ratio | 0.69 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 39 | | totalSentences | 42 | | matches | | 0 | "The bell above the door" | | 1 | "The distinctive green neon sign" | | 2 | "I called out, sliding a" | | 3 | "His hazel eyes caught the" | | 4 | "His voice was deeper than" | | 5 | "I froze, my rag hovering" | | 6 | "He chuckled, a sound that" | | 7 | "I forced a smile, my" | | 8 | "He gestured to the stool" | | 9 | "I hesitated, weighing the risk" | | 10 | "Silas poured two fingers of" | | 11 | "The name landed like a" | | 12 | "His eyes searched my face," | | 13 | "I traced the crescent-shaped scar" | | 14 | "He swirled the whisky, the" | | 15 | "I met his gaze directly." | | 16 | "He leaned forward, his signet" | | 17 | "The lie tasted metallic in" | | 18 | "His gaze dropped to my" | | 19 | "My blood ran cold." |
| | ratio | 0.929 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 42 | | matches | (empty) | | ratio | 0 | |
| 87.91% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 13 | | technicalSentenceCount | 1 | | matches | | 0 | "We were strangers who shared a history too dangerous to discuss in a place that wasn't really a bar at all." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 21 | | uselessAdditionCount | 7 | | matches | | 0 | "I forced, my fingers tightening on the damp rag" | | 1 | "But my feet moved, the worn leather creaking under my weight" | | 2 | "Silas poured, the ice clinking like distant bells" | | 3 | "He swirled, the liquid clinging to the glass like memories" | | 4 | "He leaned, his signet ring catching the neon light" | | 5 | "he asked, his tone carefully neutral" | | 6 | "I slid, my legs feeling unsteady" |
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| 78.57% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 5 | | fancyCount | 3 | | fancyTags | | 0 | "I called out (call out)" | | 1 | "He chuckled (chuckle)" | | 2 | "He didn't (do)" |
| | dialogueSentences | 42 | | tagDensity | 0.119 | | leniency | 0.238 | | rawRatio | 0.6 | | effectiveRatio | 0.143 | |