| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 13 | | adverbTagCount | 1 | | adverbTags | | 0 | "she said softly [softly]" |
| | dialogueSentences | 40 | | tagDensity | 0.325 | | leniency | 0.65 | | rawRatio | 0.077 | | effectiveRatio | 0.05 | |
| 85.94% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1067 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | 0 | "quickly" | | 1 | "tightly" | | 2 | "softly" |
| |
| 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) | |
| 62.51% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1067 | | totalAiIsms | 8 | | found | | | highlights | | 0 | "shattered" | | 1 | "tracing" | | 2 | "footsteps" | | 3 | "flicked" | | 4 | "chill" | | 5 | "pulse" | | 6 | "echoed" |
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| 66.67% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 2 | | maxInWindow | 2 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 1 |
| | 1 | | label | "knuckles turned white" | | count | 1 |
|
| | highlights | | 0 | "eyes narrowed" | | 1 | "knuckles went white" |
| |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 86 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 86 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 113 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 38 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 2 | | markdownWords | 2 | | totalWords | 1054 | | ratio | 0.002 | | matches | | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 12 | | unquotedAttributions | 0 | | matches | (empty) | |
| 50.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 39 | | wordCount | 706 | | uniqueNames | 14 | | maxNameDensity | 1.98 | | worstName | "Aurora" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Silas" | | discoveredNames | | Raven | 1 | | Nest | 1 | | Aurora | 14 | | Carter | 1 | | Blackwood | 1 | | Sinatra | 1 | | March | 1 | | Jameson | 1 | | Evan | 1 | | Silas | 12 | | Prague | 2 | | Golden | 1 | | Empress | 1 | | Didn | 1 |
| | persons | | 0 | "Raven" | | 1 | "Aurora" | | 2 | "Carter" | | 3 | "Blackwood" | | 4 | "Sinatra" | | 5 | "March" | | 6 | "Jameson" | | 7 | "Evan" | | 8 | "Silas" |
| | places | | | globalScore | 0.508 | | windowScore | 0.5 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 47 | | 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 | 1054 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 113 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 43 | | mean | 24.51 | | std | 19.41 | | cv | 0.792 | | sampleLengths | | 0 | 52 | | 1 | 4 | | 2 | 61 | | 3 | 47 | | 4 | 56 | | 5 | 36 | | 6 | 23 | | 7 | 13 | | 8 | 18 | | 9 | 7 | | 10 | 7 | | 11 | 35 | | 12 | 39 | | 13 | 6 | | 14 | 37 | | 15 | 7 | | 16 | 13 | | 17 | 57 | | 18 | 8 | | 19 | 31 | | 20 | 62 | | 21 | 16 | | 22 | 8 | | 23 | 10 | | 24 | 5 | | 25 | 17 | | 26 | 53 | | 27 | 48 | | 28 | 8 | | 29 | 13 | | 30 | 38 | | 31 | 17 | | 32 | 20 | | 33 | 3 | | 34 | 50 | | 35 | 11 | | 36 | 22 | | 37 | 18 | | 38 | 3 | | 39 | 4 | | 40 | 3 | | 41 | 60 | | 42 | 8 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 86 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 138 | | matches | (empty) | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 13 | | semicolonCount | 0 | | flaggedSentences | 9 | | totalSentences | 113 | | ratio | 0.08 | | matches | | 0 | "Her boots—scuffed from a delivery run—paused mid-step." | | 1 | "The bar smelled of bourbon and old paper—the way it had since 1997, when he opened it." | | 2 | "His hazel eyes flicked over her—black hair shorter now, the scar on her wrist peeking out from a sleeve too thin for the March chill." | | 3 | "The bar’s usual patrons—a cluster of suited men arguing over a chessboard, a woman with a scarred knuckle tapping a cigarette—had gone still, their gazes fixed between them." | | 4 | "Silas glanced at his pocket watch—silver, old, never broken—before slipping it back into his coat." | | 5 | "She reached for her glass again, stopped by the way his hand rested near the tumbler—fingers curled too tightly, knuckles whitening." | | 6 | "A laugh escaped her—sharp, bitter." | | 7 | "Not hard—just enough to anchor her." | | 8 | "The scar on his knee—hidden beneath the table—itched like it was still in the mud of the Prague alley." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 721 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 24 | | adverbRatio | 0.033287101248266296 | | lyAdverbCount | 4 | | lyAdverbRatio | 0.005547850208044383 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 113 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 113 | | mean | 9.33 | | std | 7.29 | | cv | 0.782 | | sampleLengths | | 0 | 17 | | 1 | 7 | | 2 | 3 | | 3 | 13 | | 4 | 12 | | 5 | 4 | | 6 | 30 | | 7 | 16 | | 8 | 15 | | 9 | 6 | | 10 | 17 | | 11 | 18 | | 12 | 6 | | 13 | 4 | | 14 | 25 | | 15 | 18 | | 16 | 9 | | 17 | 5 | | 18 | 3 | | 19 | 28 | | 20 | 10 | | 21 | 3 | | 22 | 10 | | 23 | 3 | | 24 | 6 | | 25 | 4 | | 26 | 6 | | 27 | 5 | | 28 | 7 | | 29 | 7 | | 30 | 2 | | 31 | 5 | | 32 | 6 | | 33 | 13 | | 34 | 16 | | 35 | 6 | | 36 | 24 | | 37 | 9 | | 38 | 6 | | 39 | 5 | | 40 | 6 | | 41 | 12 | | 42 | 14 | | 43 | 7 | | 44 | 7 | | 45 | 6 | | 46 | 15 | | 47 | 18 | | 48 | 9 | | 49 | 15 |
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| 48.97% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 3 | | diversityRatio | 0.30973451327433627 | | totalSentences | 113 | | uniqueOpeners | 35 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 82 | | matches | | 0 | "Somewhere behind the bar, ice" | | 1 | "Just a missed call." | | 2 | "Somewhere, a clock ticked." |
| | ratio | 0.037 | |
| 98.05% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 25 | | totalSentences | 82 | | matches | | 0 | "Her boots—scuffed from a delivery" | | 1 | "He didn’t look up." | | 2 | "His voice was gravel wrapped" | | 3 | "She stepped forward, her scuffing" | | 4 | "His hazel eyes flicked over" | | 5 | "He gestured to the empty" | | 6 | "She slid onto the stool." | | 7 | "he said, clinking his glass" | | 8 | "Her throat burned as she" | | 9 | "He set his glass down." | | 10 | "He leaned closer, the scent" | | 11 | "She met his eyes" | | 12 | "His thumb brushed the signet" | | 13 | "He nodded at the woman" | | 14 | "She reached for her glass" | | 15 | "She’d been 23 then, drunk" | | 16 | "she said softly" | | 17 | "He gestured to her uniform," | | 18 | "She didn’t move to wipe" | | 19 | "She didn’t pull away." |
| | ratio | 0.305 | |
| 45.37% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 68 | | totalSentences | 82 | | matches | | 0 | "The clink of glass shattered" | | 1 | "Her boots—scuffed from a delivery" | | 2 | "Silas Blackwood, leaning on his" | | 3 | "The green neon sign above" | | 4 | "He didn’t look up." | | 5 | "His voice was gravel wrapped" | | 6 | "Aurora’s hand tightened on the" | | 7 | "The bar smelled of bourbon" | | 8 | "She stepped forward, her scuffing" | | 9 | "Silas finally glanced up." | | 10 | "His hazel eyes flicked over" | | 11 | "He gestured to the empty" | | 12 | "She slid onto the stool." | | 13 | "The leather creaked." | | 14 | "The bar’s usual patrons—a cluster" | | 15 | "Silas poured two fingers of" | | 16 | "he said, clinking his glass" | | 17 | "Aurora didn’t smile." | | 18 | "Her throat burned as she" | | 19 | "A muscle in his jaw" |
| | ratio | 0.829 | |
| 60.98% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 82 | | matches | | 0 | "Now, it was all auburn" |
| | ratio | 0.012 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 21 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 86.54% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 13 | | uselessAdditionCount | 1 | | matches | | 0 | "He leaned, the scent of oak and cigar smoke crowding her" |
| |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 5 | | fancyCount | 1 | | fancyTags | | 0 | "she whispered (whisper)" |
| | dialogueSentences | 40 | | tagDensity | 0.125 | | leniency | 0.25 | | rawRatio | 0.2 | | effectiveRatio | 0.05 | |