| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 4 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 108 | | tagDensity | 0.037 | | leniency | 0.074 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 2188 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 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) | |
| 49.73% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 2188 | | totalAiIsms | 22 | | found | | | highlights | | 0 | "shattered" | | 1 | "flicked" | | 2 | "silence" | | 3 | "jaw clenched" | | 4 | "calculating" | | 5 | "eyebrow" | | 6 | "raced" | | 7 | "whisper" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "jaw/fists clenched" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 1 | | narrationSentences | 293 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 293 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 397 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 27 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 16 | | markdownWords | 34 | | totalWords | 2173 | | ratio | 0.016 | | matches | | 0 | "\"You.\"" | | 1 | "Evan" | | 2 | "I’ve made it" | | 3 | "Rory Carter." | | 4 | "How?" | | 5 | "both" | | 6 | "I’m dangerous" | | 7 | "Who the hell is this?" | | 8 | "How?" | | 9 | "both" | | 10 | "I’m dangerous" | | 11 | "Who the hell is this?" | | 12 | "How?" | | 13 | "both" | | 14 | "I’m dangerous" | | 15 | "Who the hell is this?" |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 22 | | unquotedAttributions | 0 | | matches | (empty) | |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 156 | | wordCount | 1699 | | uniqueNames | 8 | | maxNameDensity | 3.88 | | worstName | "Silas" | | maxWindowNameDensity | 6.5 | | worstWindowName | "Silas" | | discoveredNames | | Blackwood | 1 | | Silas | 66 | | Evan | 55 | | Golden | 4 | | Empress | 4 | | London | 1 | | Rory | 23 | | Carter | 2 |
| | persons | | 0 | "Blackwood" | | 1 | "Silas" | | 2 | "Evan" | | 3 | "Empress" | | 4 | "Rory" | | 5 | "Carter" |
| | places | | | globalScore | 0 | | windowScore | 0 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 102 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 2 | | per1kWords | 0.92 | | wordCount | 2173 | | matches | | 0 | "not in apology, but in recognition" | | 1 | "Not just in the way he dressed or carried himself, but in the way his eyes darted" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 397 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 203 | | mean | 10.7 | | std | 8.52 | | cv | 0.796 | | sampleLengths | | 0 | 1 | | 1 | 8 | | 2 | 45 | | 3 | 1 | | 4 | 14 | | 5 | 38 | | 6 | 7 | | 7 | 18 | | 8 | 31 | | 9 | 13 | | 10 | 13 | | 11 | 9 | | 12 | 51 | | 13 | 9 | | 14 | 5 | | 15 | 11 | | 16 | 10 | | 17 | 9 | | 18 | 11 | | 19 | 26 | | 20 | 8 | | 21 | 10 | | 22 | 14 | | 23 | 5 | | 24 | 46 | | 25 | 11 | | 26 | 16 | | 27 | 7 | | 28 | 6 | | 29 | 38 | | 30 | 8 | | 31 | 14 | | 32 | 10 | | 33 | 7 | | 34 | 12 | | 35 | 7 | | 36 | 16 | | 37 | 6 | | 38 | 12 | | 39 | 23 | | 40 | 33 | | 41 | 7 | | 42 | 9 | | 43 | 12 | | 44 | 29 | | 45 | 6 | | 46 | 7 | | 47 | 8 | | 48 | 6 | | 49 | 9 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 293 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 4 | | totalVerbs | 329 | | matches | | 0 | "was waiting" | | 1 | "was wearing" | | 2 | "was wearing" | | 3 | "was wearing" |
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| 27.71% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 18 | | semicolonCount | 0 | | flaggedSentences | 16 | | totalSentences | 397 | | ratio | 0.04 | | matches | | 0 | "The stranger’s face twisted—not in apology, but in recognition." | | 1 | "The man—*Evan*, if the name still fit—stilled." | | 2 | "His suit was expensive, the kind that screamed *I’ve made it*—but the cuffs were frayed at the edges, like he’d been rolling them up in a hurry." | | 3 | "Evan’s gaze flicked to the signet ring on Silas’s right hand—the silver band he never took off, not even to sleep." | | 4 | "This man was something else entirely—polished, dangerous, like a blade sharpened too fine." | | 5 | "Not just in the way he dressed or carried himself, but in the way his eyes darted—always checking, always calculating." | | 6 | "The girl who’d fled London after Evan had—" | | 7 | "She was wearing a delivery uniform—black pants, a white shirt, the Golden Empress logo pinned to her chest." | | 8 | "He knew the way she carried herself—like she was always one step ahead." | | 9 | "He knew the way she carried herself—like she was always one step ahead." | | 10 | "He knew the way she carried herself—like she was always one step ahead." | | 11 | "She was wearing a delivery uniform—black pants, a white shirt, the Golden Empress logo pinned to her chest." | | 12 | "He knew the way she carried herself—like she was always one step ahead." | | 13 | "The woman—Rory—stepped forward." | | 14 | "She was wearing a delivery uniform—black pants, a white shirt, the Golden Empress logo pinned to her chest." | | 15 | "He knew the way she carried herself—like she was always one step ahead." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1715 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 46 | | adverbRatio | 0.026822157434402333 | | lyAdverbCount | 2 | | lyAdverbRatio | 0.0011661807580174927 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 397 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 397 | | mean | 5.47 | | std | 3.72 | | cv | 0.68 | | sampleLengths | | 0 | 8 | | 1 | 20 | | 2 | 13 | | 3 | 9 | | 4 | 3 | | 5 | 1 | | 6 | 8 | | 7 | 4 | | 8 | 2 | | 9 | 7 | | 10 | 20 | | 11 | 5 | | 12 | 6 | | 13 | 2 | | 14 | 5 | | 15 | 3 | | 16 | 13 | | 17 | 2 | | 18 | 6 | | 19 | 6 | | 20 | 12 | | 21 | 7 | | 22 | 6 | | 23 | 3 | | 24 | 4 | | 25 | 4 | | 26 | 9 | | 27 | 4 | | 28 | 5 | | 29 | 2 | | 30 | 11 | | 31 | 7 | | 32 | 27 | | 33 | 4 | | 34 | 9 | | 35 | 4 | | 36 | 1 | | 37 | 6 | | 38 | 5 | | 39 | 3 | | 40 | 3 | | 41 | 4 | | 42 | 3 | | 43 | 6 | | 44 | 3 | | 45 | 6 | | 46 | 2 | | 47 | 21 | | 48 | 5 | | 49 | 4 |
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| 41.44% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 34 | | diversityRatio | 0.09571788413098237 | | totalSentences | 397 | | uniqueOpeners | 38 | |
| 48.48% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 4 | | totalSentences | 275 | | matches | | 0 | "Then he met Silas’s gaze." | | 1 | "Just for a second." | | 2 | "Then he straightened." | | 3 | "Then he nodded." |
| | ratio | 0.015 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 36 | | totalSentences | 275 | | matches | | 0 | "His jaw tightened." | | 1 | "He didn’t let go." | | 2 | "His dark eyes flicked over" | | 3 | "He looked at the back" | | 4 | "His suit was expensive, the" | | 5 | "He didn’t have to." | | 6 | "He went still." | | 7 | "He didn’t take a sip." | | 8 | "They clinked glasses." | | 9 | "She was wearing a delivery" | | 10 | "She didn’t smile." | | 11 | "She didn’t speak." | | 12 | "She just stood there." | | 13 | "He knew Rory." | | 14 | "He knew her quick mind," | | 15 | "He knew the way she" | | 16 | "He knew Rory." | | 17 | "He knew her." | | 18 | "He knew the way she" | | 19 | "He wore a black suit," |
| | ratio | 0.131 | |
| 9.09% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 248 | | totalSentences | 275 | | matches | | 0 | "The glass shattered before it" | | 1 | "Silas Blackwood’s hand snapped out," | | 2 | "The amber liquid splashed across" | | 3 | "The stranger’s face twisted—not in" | | 4 | "His jaw tightened." | | 5 | "Silas exhaled through his nose," | | 6 | "He didn’t let go." | | 7 | "The man—*Evan*, if the name" | | 8 | "His dark eyes flicked over" | | 9 | "The air between them thickened." | | 10 | "Silas released him." | | 11 | "Evan’s wrist burned where Silas’s" | | 12 | "The stool scraped against the" | | 13 | "Evan didn’t look at the" | | 14 | "He looked at the back" | | 15 | "The one that didn’t lead" | | 16 | "Silas poured himself a whiskey," | | 17 | "The ice clinked." | | 18 | "Evan’s laugh was dry." | | 19 | "Silas took a sip." |
| | ratio | 0.902 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 275 | | matches | (empty) | | ratio | 0 | |
| 99.13% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 49 | | technicalSentenceCount | 3 | | matches | | 0 | "Silas Blackwood’s hand snapped out, fingers curling around the wrist of the man who’d just hurled the drink at him." | | 1 | "*Rory Carter.* The girl who’d once worked part-time at the Golden Empress, delivering takeout while she avoided Evan like the plague." | | 2 | "The man who’d broken Rory’s heart and then broken her life." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 4 | | uselessAdditionCount | 1 | | matches | | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 4 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 108 | | tagDensity | 0.037 | | leniency | 0.074 | | rawRatio | 0 | | effectiveRatio | 0 | |