| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 15 | | adverbTagCount | 2 | | adverbTags | | 0 | "she said quietly [quietly]" | | 1 | "Silas said quietly [quietly]" |
| | dialogueSentences | 81 | | tagDensity | 0.185 | | leniency | 0.37 | | rawRatio | 0.133 | | effectiveRatio | 0.049 | |
| 74.46% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1566 | | totalAiIsmAdverbs | 8 | | found | | | highlights | | 0 | "slowly" | | 1 | "slightly" | | 2 | "sharply" | | 3 | "carefully" | | 4 | "really" |
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| 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) | |
| 42.53% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1566 | | totalAiIsms | 18 | | found | | | highlights | | 0 | "flickered" | | 1 | "familiar" | | 2 | "scanned" | | 3 | "weight" | | 4 | "effortless" | | 5 | "warmth" | | 6 | "eyebrow" | | 7 | "silence" | | 8 | "traced" | | 9 | "echo" | | 10 | "pulse" | | 11 | "could feel" |
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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 | 0 | | narrationSentences | 139 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 139 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 206 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 32 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 2 | | markdownWords | 12 | | totalWords | 1556 | | ratio | 0.008 | | matches | | 0 | "Vivian, 1998" 1/1/1998, 12:00:00 AM | | 1 | "Come to London, Rory, you don’t have to go back." |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 24 | | unquotedAttributions | 0 | | matches | (empty) | |
| 33.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 41 | | wordCount | 1062 | | uniqueNames | 8 | | maxNameDensity | 2.07 | | worstName | "Silas" | | maxWindowNameDensity | 4 | | worstWindowName | "Silas" | | discoveredNames | | Rory | 10 | | Raven | 1 | | Nest | 1 | | London | 2 | | Cardiff | 2 | | Silas | 22 | | Eva | 2 | | Evan | 1 |
| | persons | | 0 | "Rory" | | 1 | "Raven" | | 2 | "Silas" | | 3 | "Eva" | | 4 | "Evan" |
| | places | | | globalScore | 0.464 | | windowScore | 0.333 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 69 | | glossingSentenceCount | 1 | | matches | | 0 | "sounded like an old joke" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.643 | | wordCount | 1556 | | matches | | 0 | "not touching her, but close enough she could feel the warmth radiating off him" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 206 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 123 | | mean | 12.65 | | std | 13.78 | | cv | 1.089 | | sampleLengths | | 0 | 50 | | 1 | 52 | | 2 | 4 | | 3 | 75 | | 4 | 68 | | 5 | 12 | | 6 | 3 | | 7 | 2 | | 8 | 2 | | 9 | 26 | | 10 | 21 | | 11 | 3 | | 12 | 44 | | 13 | 4 | | 14 | 28 | | 15 | 8 | | 16 | 13 | | 17 | 12 | | 18 | 60 | | 19 | 34 | | 20 | 5 | | 21 | 2 | | 22 | 3 | | 23 | 9 | | 24 | 6 | | 25 | 10 | | 26 | 7 | | 27 | 2 | | 28 | 43 | | 29 | 2 | | 30 | 5 | | 31 | 21 | | 32 | 12 | | 33 | 2 | | 34 | 11 | | 35 | 6 | | 36 | 2 | | 37 | 37 | | 38 | 6 | | 39 | 40 | | 40 | 5 | | 41 | 3 | | 42 | 9 | | 43 | 7 | | 44 | 13 | | 45 | 8 | | 46 | 11 | | 47 | 1 | | 48 | 23 | | 49 | 12 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 139 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 3 | | totalVerbs | 208 | | matches | | 0 | "was just passing" | | 1 | "was trying" | | 2 | "was piecing" |
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| 31.90% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 10 | | semicolonCount | 0 | | flaggedSentences | 8 | | totalSentences | 206 | | ratio | 0.039 | | matches | | 0 | "The scent of aged whiskey and cigarette smoke hit her first—thick, familiar, ancient." | | 1 | "The bar hummed with the low thrum of hushed conversation and clinking glasses, the usual evening crowd—locals drowning their quiet sorrows or celebrating loud victories." | | 2 | "His back was turned, shoulders broader than she remembered, but the limp was unmistakable—the slight drag in his step as he shifted his weight." | | 3 | "Time had been a sculptor with Silas—unrelenting, precise." | | 4 | "Not of who she was—but of why she was here." | | 5 | "A customer at the bar—a broad-shouldered man in a leather jacket—glanced between them, then melted back into the haze of drink and smoke." | | 6 | "She unzipped her jacket slowly, revealing a fitted black turtleneck beneath—simple, no nonsense." | | 7 | "A name was carved there—*Vivian, 1998*—her finger traced the grooves without thinking." |
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| 90.57% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 965 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 49 | | adverbRatio | 0.05077720207253886 | | lyAdverbCount | 10 | | lyAdverbRatio | 0.010362694300518135 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 206 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 206 | | mean | 7.55 | | std | 5.99 | | cv | 0.794 | | sampleLengths | | 0 | 18 | | 1 | 13 | | 2 | 19 | | 3 | 25 | | 4 | 20 | | 5 | 7 | | 6 | 4 | | 7 | 16 | | 8 | 17 | | 9 | 24 | | 10 | 18 | | 11 | 2 | | 12 | 15 | | 13 | 8 | | 14 | 6 | | 15 | 19 | | 16 | 18 | | 17 | 12 | | 18 | 3 | | 19 | 2 | | 20 | 2 | | 21 | 6 | | 22 | 8 | | 23 | 10 | | 24 | 2 | | 25 | 2 | | 26 | 19 | | 27 | 3 | | 28 | 15 | | 29 | 6 | | 30 | 23 | | 31 | 4 | | 32 | 8 | | 33 | 6 | | 34 | 14 | | 35 | 8 | | 36 | 9 | | 37 | 4 | | 38 | 12 | | 39 | 15 | | 40 | 13 | | 41 | 2 | | 42 | 6 | | 43 | 10 | | 44 | 14 | | 45 | 8 | | 46 | 22 | | 47 | 4 | | 48 | 5 | | 49 | 2 |
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| 50.00% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 7 | | diversityRatio | 0.32038834951456313 | | totalSentences | 206 | | uniqueOpeners | 66 | |
| 62.31% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 107 | | matches | | 0 | "Then she saw him." | | 1 | "Instead, he reached under the" |
| | ratio | 0.019 | |
| 55.51% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 44 | | totalSentences | 107 | | matches | | 0 | "She exhaled the evening’s damp" | | 1 | "His auburn hair, now threaded" | | 2 | "His back was turned, shoulders" | | 3 | "She watched as he reached" | | 4 | "She hadn’t planned to come" | | 5 | "She was just passing, heading" | | 6 | "Their eyes locked." | | 7 | "His hand stilled on the" | | 8 | "Her fingers curled into her" | | 9 | "She walked forward." | | 10 | "It sounded like an old" | | 11 | "She unzipped her jacket slowly," | | 12 | "She exhaled through her nose." | | 13 | "His hazel eyes sharpened, like" | | 14 | "He didn’t flinch." | | 15 | "she said quietly" | | 16 | "She lifted her head." | | 17 | "Her best friend." | | 18 | "He never did." | | 19 | "He poured two fingers of" |
| | ratio | 0.411 | |
| 48.79% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 88 | | totalSentences | 107 | | matches | | 0 | "The green sign flickered like" | | 1 | "The scent of aged whiskey" | | 2 | "She exhaled the evening’s damp" | | 3 | "The bar hummed with the" | | 4 | "Rory scanned the faces, half-expecting" | | 5 | "Silas stood behind the counter," | | 6 | "His auburn hair, now threaded" | | 7 | "His back was turned, shoulders" | | 8 | "She watched as he reached" | | 9 | "The years had carved new" | | 10 | "Time had been a sculptor" | | 11 | "She hadn’t planned to come" | | 12 | "She was just passing, heading" | | 13 | "Silas glanced up, as if" | | 14 | "Their eyes locked." | | 15 | "His hand stilled on the" | | 16 | "Her fingers curled into her" | | 17 | "She walked forward." | | 18 | "The floorboards creaked under her" | | 19 | "Silas set the glass down" |
| | ratio | 0.822 | |
| 46.73% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 107 | | matches | | 0 | "Now she dressed like she" |
| | ratio | 0.009 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 43 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 15 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 15 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 81 | | tagDensity | 0.185 | | leniency | 0.37 | | rawRatio | 0.067 | | effectiveRatio | 0.025 | |