| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 6 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 50 | | tagDensity | 0.12 | | leniency | 0.24 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 72.95% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1109 | | totalAiIsmAdverbs | 6 | | found | | | highlights | | 0 | "very" | | 1 | "completely" | | 2 | "suddenly" | | 3 | "really" | | 4 | "perfectly" |
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| 80.00% | AI-ism character names | Target: 0 AI-default names (16 tracked, −20% each) | |
| 80.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | | |
| 45.90% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1109 | | totalAiIsms | 12 | | found | | | highlights | | 0 | "scanning" | | 1 | "weight" | | 2 | "crystalline" | | 3 | "warmth" | | 4 | "throbbed" | | 5 | "tension" | | 6 | "mechanical" | | 7 | "familiar" | | 8 | "trembled" | | 9 | "absolutely" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "hung in the air" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 48 | | matches | (empty) | |
| 83.33% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 2 | | narrationSentences | 48 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 92 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 39 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1102 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 6 | | unquotedAttributions | 0 | | matches | (empty) | |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 40 | | wordCount | 674 | | uniqueNames | 10 | | maxNameDensity | 2.37 | | worstName | "Eva" | | maxWindowNameDensity | 5 | | worstWindowName | "Eva" | | discoveredNames | | Raven | 1 | | Nest | 1 | | October | 1 | | Silas | 2 | | Rory | 15 | | Thornfield | 1 | | Eva | 16 | | Macallan | 1 | | London | 1 | | Soho | 1 |
| | persons | | 0 | "Raven" | | 1 | "Nest" | | 2 | "Silas" | | 3 | "Rory" | | 4 | "Thornfield" | | 5 | "Eva" |
| | places | | | globalScore | 0.313 | | windowScore | 0 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 44 | | 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 | 1102 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 92 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 61 | | mean | 18.07 | | std | 16.77 | | cv | 0.928 | | sampleLengths | | 0 | 76 | | 1 | 2 | | 2 | 3 | | 3 | 37 | | 4 | 1 | | 5 | 67 | | 6 | 4 | | 7 | 2 | | 8 | 30 | | 9 | 3 | | 10 | 23 | | 11 | 2 | | 12 | 4 | | 13 | 22 | | 14 | 21 | | 15 | 5 | | 16 | 7 | | 17 | 12 | | 18 | 9 | | 19 | 2 | | 20 | 43 | | 21 | 2 | | 22 | 6 | | 23 | 7 | | 24 | 28 | | 25 | 18 | | 26 | 12 | | 27 | 31 | | 28 | 13 | | 29 | 2 | | 30 | 45 | | 31 | 12 | | 32 | 38 | | 33 | 1 | | 34 | 22 | | 35 | 21 | | 36 | 5 | | 37 | 11 | | 38 | 37 | | 39 | 3 | | 40 | 5 | | 41 | 20 | | 42 | 14 | | 43 | 6 | | 44 | 29 | | 45 | 3 | | 46 | 17 | | 47 | 2 | | 48 | 11 | | 49 | 44 |
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| 97.95% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 48 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 123 | | matches | (empty) | |
| 49.69% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 4 | | semicolonCount | 0 | | flaggedSentences | 3 | | totalSentences | 92 | | ratio | 0.033 | | matches | | 0 | "But it was the eyes that struck her most—the same green that used to sparkle with mischief now held a crystalline hardness." | | 1 | "Eva's manicured hand—when had Eva ever had a manicure?—wrapped around the glass." | | 2 | "The old photographs on the walls seemed to watch them—strangers frozen in moments of joy that felt impossible now." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 679 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 24 | | adverbRatio | 0.035346097201767304 | | lyAdverbCount | 7 | | lyAdverbRatio | 0.010309278350515464 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 92 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 92 | | mean | 11.98 | | std | 9.05 | | cv | 0.756 | | sampleLengths | | 0 | 29 | | 1 | 24 | | 2 | 23 | | 3 | 2 | | 4 | 3 | | 5 | 7 | | 6 | 16 | | 7 | 14 | | 8 | 1 | | 9 | 22 | | 10 | 23 | | 11 | 22 | | 12 | 4 | | 13 | 2 | | 14 | 16 | | 15 | 14 | | 16 | 3 | | 17 | 11 | | 18 | 12 | | 19 | 2 | | 20 | 4 | | 21 | 5 | | 22 | 12 | | 23 | 5 | | 24 | 8 | | 25 | 13 | | 26 | 5 | | 27 | 7 | | 28 | 12 | | 29 | 6 | | 30 | 3 | | 31 | 2 | | 32 | 17 | | 33 | 7 | | 34 | 19 | | 35 | 2 | | 36 | 6 | | 37 | 7 | | 38 | 8 | | 39 | 20 | | 40 | 15 | | 41 | 3 | | 42 | 7 | | 43 | 5 | | 44 | 8 | | 45 | 23 | | 46 | 13 | | 47 | 2 | | 48 | 22 | | 49 | 23 |
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| 59.42% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 7 | | diversityRatio | 0.40217391304347827 | | totalSentences | 92 | | uniqueOpeners | 37 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 47 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 6 | | totalSentences | 47 | | matches | | 0 | "She knew that voice, though" | | 1 | "She sipped the whiskey, her" | | 2 | "He took one look at" | | 3 | "They stared at each other" | | 4 | "She stood, leaving a twenty-pound" | | 5 | "She picked up Eva's glass," |
| | ratio | 0.128 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 45 | | totalSentences | 47 | | matches | | 0 | "The Raven's Nest hummed with" | | 1 | "Rory glanced up from wiping" | | 2 | "The woman who entered moved" | | 3 | "The voice hit like a" | | 4 | "Rory's hand froze on the" | | 5 | "She knew that voice, though" | | 6 | "Eva Thornfield stood framed against" | | 7 | "The bohemian scarves and vintage" | | 8 | "Eva slid onto a barstool," | | 9 | "The Eva she remembered moved" | | 10 | "Rory reached for the Macallan" | | 11 | "Eva's manicured hand—when had Eva" | | 12 | "Eva's laugh held no warmth." | | 13 | "She sipped the whiskey, her" | | 14 | "The words hung between them" | | 15 | "Rory's left wrist throbbed where" | | 16 | "Eva's grip tightened on her" | | 17 | "A group of bankers at" | | 18 | "Rory continued polishing glasses, each" | | 19 | "The old photographs on the" |
| | ratio | 0.957 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 47 | | matches | (empty) | | ratio | 0 | |
| 0.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 27 | | technicalSentenceCount | 9 | | matches | | 0 | "The Raven's Nest hummed with its usual evening crowd when the door chimed, letting in a gust of October air that carried the scent of rain and exhaust fumes." | | 1 | "The woman who entered moved with deliberate precision, scanning the dimly lit interior with practised eyes before her gaze locked onto Rory's face." | | 2 | "But it was the eyes that struck her most—the same green that used to sparkle with mischief now held a crystalline hardness." | | 3 | "Eva slid onto a barstool, her movements controlled in a way that made Rory's skin crawl." | | 4 | "The old photographs on the walls seemed to watch them—strangers frozen in moments of joy that felt impossible now." | | 5 | "Eva finished her whiskey in one smooth motion, the kind of practised gesture that spoke of too many client dinners and networking events." | | 6 | "The words fell between them like stones into still water, creating ripples that spread outward, disturbing everything." | | 7 | "Eva's hand trembled as she reached for her purse, the first crack in her armour that felt genuine." | | 8 | "Outside, London hummed on, indifferent to the small tragedy that had just played out in a dimly lit Soho bar, where old maps marked territories that no longer e…" |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 6 | | uselessAdditionCount | 2 | | matches | | 0 | "She sipped, her face revealing nothing" | | 1 | "Eva stopped, her composure cracking just enough to reveal something raw underneath" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |