| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 5 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 43 | | tagDensity | 0.116 | | leniency | 0.233 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 85.55% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1384 | | totalAiIsmAdverbs | 4 | | 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) | |
| 38.58% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1384 | | totalAiIsms | 17 | | found | | | highlights | | 0 | "trembled" | | 1 | "traced" | | 2 | "shattered" | | 3 | "weight" | | 4 | "flickered" | | 5 | "eyebrow" | | 6 | "flicked" | | 7 | "charged" | | 8 | "could feel" | | 9 | "silence" | | 10 | "footsteps" | | 11 | "tracing" | | 12 | "throbbed" |
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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 | 104 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 104 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 141 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 40 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1377 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 8 | | unquotedAttributions | 0 | | matches | (empty) | |
| 66.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 35 | | wordCount | 1183 | | uniqueNames | 4 | | maxNameDensity | 1.44 | | worstName | "Silas" | | maxWindowNameDensity | 3 | | worstWindowName | "Silas" | | discoveredNames | | | persons | | | places | (empty) | | globalScore | 0.781 | | windowScore | 0.667 | |
| 13.01% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 73 | | glossingSentenceCount | 4 | | matches | | 0 | "smelled like him—cedar and old paper and s" | | 1 | "as if expecting someone to come bursting through it" | | 2 | "n’t react, not visibly, but she saw the wa" | | 3 | "as if carrying something heavy" | | 4 | "as if waiting for something" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.726 | | wordCount | 1377 | | matches | | 0 | "not visibly, but she saw the way his jaw tightened, the way his eyes flicked" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 141 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 64 | | mean | 21.52 | | std | 18.96 | | cv | 0.881 | | sampleLengths | | 0 | 68 | | 1 | 65 | | 2 | 4 | | 3 | 45 | | 4 | 33 | | 5 | 43 | | 6 | 55 | | 7 | 7 | | 8 | 10 | | 9 | 80 | | 10 | 32 | | 11 | 36 | | 12 | 1 | | 13 | 10 | | 14 | 6 | | 15 | 9 | | 16 | 22 | | 17 | 2 | | 18 | 39 | | 19 | 11 | | 20 | 43 | | 21 | 2 | | 22 | 19 | | 23 | 6 | | 24 | 3 | | 25 | 35 | | 26 | 30 | | 27 | 2 | | 28 | 1 | | 29 | 46 | | 30 | 37 | | 31 | 6 | | 32 | 13 | | 33 | 5 | | 34 | 17 | | 35 | 50 | | 36 | 5 | | 37 | 16 | | 38 | 12 | | 39 | 25 | | 40 | 36 | | 41 | 32 | | 42 | 7 | | 43 | 37 | | 44 | 4 | | 45 | 29 | | 46 | 33 | | 47 | 52 | | 48 | 15 | | 49 | 8 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 104 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 217 | | matches | | |
| 82.07% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 4 | | semicolonCount | 0 | | flaggedSentences | 3 | | totalSentences | 141 | | ratio | 0.021 | | matches | | 0 | "He studied her face, his hazel eyes sharp, missing nothing—the way her breath hitched, the way her fingers trembled just slightly against the bar top." | | 1 | "It smelled like him—cedar and old paper and something faintly metallic, like gun oil." | | 2 | "Instead, she picked up the bottle of whiskey—the good stuff, the kind he kept under the counter—and poured herself another glass." |
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| 96.76% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1190 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 52 | | adverbRatio | 0.043697478991596636 | | lyAdverbCount | 12 | | lyAdverbRatio | 0.010084033613445379 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 141 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 141 | | mean | 9.77 | | std | 7.63 | | cv | 0.781 | | sampleLengths | | 0 | 11 | | 1 | 21 | | 2 | 3 | | 3 | 33 | | 4 | 4 | | 5 | 20 | | 6 | 16 | | 7 | 25 | | 8 | 4 | | 9 | 3 | | 10 | 22 | | 11 | 8 | | 12 | 10 | | 13 | 2 | | 14 | 17 | | 15 | 8 | | 16 | 8 | | 17 | 3 | | 18 | 10 | | 19 | 14 | | 20 | 12 | | 21 | 4 | | 22 | 2 | | 23 | 29 | | 24 | 5 | | 25 | 19 | | 26 | 2 | | 27 | 5 | | 28 | 2 | | 29 | 5 | | 30 | 3 | | 31 | 40 | | 32 | 21 | | 33 | 19 | | 34 | 26 | | 35 | 6 | | 36 | 5 | | 37 | 21 | | 38 | 9 | | 39 | 1 | | 40 | 1 | | 41 | 6 | | 42 | 4 | | 43 | 4 | | 44 | 2 | | 45 | 9 | | 46 | 18 | | 47 | 4 | | 48 | 2 | | 49 | 7 |
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| 45.74% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 6 | | diversityRatio | 0.2695035460992908 | | totalSentences | 141 | | uniqueOpeners | 38 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 8 | | totalSentences | 93 | | matches | | 0 | "Instead, she picked up the" | | 1 | "Then he reached for the" | | 2 | "Instead, he reached into his" | | 3 | "Somewhere, a clock ticked." | | 4 | "Finally, Silas turned to go." | | 5 | "Then she crossed the room" | | 6 | "Somewhere in the distance, a" | | 7 | "Then, just as suddenly as" |
| | ratio | 0.086 | |
| 82.37% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 32 | | totalSentences | 93 | | matches | | 0 | "She watched the liquid pool" | | 1 | "His signet ring glinted under" | | 2 | "He studied her face, his" | | 3 | "She pressed her thumb against" | | 4 | "He held it out, but" | | 5 | "She took it." | | 6 | "It smelled like him—cedar and" | | 7 | "She pressed it against her" | | 8 | "His auburn hair was more" | | 9 | "He shifted his weight, just" | | 10 | "It came out sharp, brittle." | | 11 | "She didn’t answer right away." | | 12 | "She set the glass down" | | 13 | "He exhaled through his nose," | | 14 | "His fingers were steady, but" | | 15 | "She folded it neatly, then" | | 16 | "She met his eyes." | | 17 | "Her voice was steady, but" | | 18 | "She curled them into fists," | | 19 | "He slid them across the" |
| | ratio | 0.344 | |
| 19.14% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 82 | | totalSentences | 93 | | matches | | 0 | "The glass slipped from her" | | 1 | "Whiskey splashed across the bar," | | 2 | "Rory didn’t flinch." | | 3 | "She watched the liquid pool" | | 4 | "Silas didn’t move either." | | 5 | "His signet ring glinted under" | | 6 | "The silver band had always" | | 7 | "He studied her face, his" | | 8 | "Rory looked down." | | 9 | "A thin red line traced" | | 10 | "The glass must’ve nicked her" | | 11 | "She pressed her thumb against" | | 12 | "Silas reached into his pocket" | | 13 | "He held it out, but" | | 14 | "She took it." | | 15 | "The fabric was soft, worn" | | 16 | "It smelled like him—cedar and" | | 17 | "She pressed it against her" | | 18 | "His auburn hair was more" | | 19 | "The limp was worse, too." |
| | ratio | 0.882 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 93 | | matches | (empty) | | ratio | 0 | |
| 80.20% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 57 | | technicalSentenceCount | 5 | | matches | | 0 | "She watched the liquid pool around the boots of the man standing in front of her, the way it seeped into the cracks between the floorboards, as if the bar itsel…" | | 1 | "His auburn hair was more grey than she remembered, the lines around his mouth deeper, as if someone had taken a knife to his face and carved them there." | | 2 | "The bar was quiet, the kind of quiet that settled in the small hours of the morning, when the last of the drunks had stumbled home and the only people left were…" | | 3 | "Silas didn’t react, not visibly, but she saw the way his jaw tightened, the way his eyes flicked to the door, as if expecting someone to come bursting through i…" | | 4 | "Rory watched him go, the way his shoulders hunched just slightly, as if carrying something heavy." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 5 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 2 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 43 | | tagDensity | 0.047 | | leniency | 0.093 | | rawRatio | 0 | | effectiveRatio | 0 | |