| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 17 | | adverbTagCount | 1 | | adverbTags | | 0 | "The word tasted like [like]" |
| | dialogueSentences | 31 | | tagDensity | 0.548 | | leniency | 1 | | rawRatio | 0.059 | | effectiveRatio | 0.059 | |
| 84.14% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 946 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | 0 | "suddenly" | | 1 | "slowly" | | 2 | "very" |
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| 100.00% | AI-ism character names | Target: 0 AI-default names (17 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 52.43% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 946 | | totalAiIsms | 9 | | found | | | highlights | | 0 | "silence" | | 1 | "glinting" | | 2 | "gloom" | | 3 | "flicked" | | 4 | "gleaming" | | 5 | "stomach" | | 6 | "pulse" | | 7 | "traced" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "stomach dropped/sank" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 65 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 65 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 94.49% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 77 | | gibberishSentences | 1 | | adjustedGibberishSentences | 1 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 31 | | ratio | 0.013 | | matches | | 0 | "“—And second, I欠你 a life debt.” He switched to Mandarin, the words rolling off him like a second skin." |
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| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 12 | | markdownWords | 33 | | totalWords | 938 | | ratio | 0.035 | | matches | | 0 | "Uncontrolled. Unsafe." | | 1 | "Stop touching it. You’re not a child." | | 2 | "goodbye" | | 3 | "Find me if you survive" | | 4 | "My" | | 5 | "I owe you a life debt." | | 6 | "Soon, Rory" | | 7 | "Camden Locks" | | 8 | "fixers" | | 9 | "avoiding my calls" | | 10 | "thing" | | 11 | "ma lionne" |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 8 | | unquotedAttributions | 0 | | matches | (empty) | |
| 98.76% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 31 | | wordCount | 683 | | uniqueNames | 16 | | maxNameDensity | 1.02 | | worstName | "Lucien" | | maxWindowNameDensity | 2 | | worstWindowName | "Lucien" | | discoveredNames | | French | 1 | | Victorian | 1 | | Ptolemy | 3 | | Habit | 1 | | Brick | 1 | | Lane | 1 | | Marseille | 1 | | Aurora | 6 | | Empress | 1 | | Yu-Fei | 2 | | Mandarin | 1 | | English | 1 | | Lila | 2 | | Lucien | 7 | | East | 1 | | London | 1 |
| | persons | | 0 | "Ptolemy" | | 1 | "Aurora" | | 2 | "Yu-Fei" | | 3 | "Lila" | | 4 | "Lucien" |
| | places | | 0 | "Brick" | | 1 | "Lane" | | 2 | "Marseille" | | 3 | "Mandarin" | | 4 | "English" | | 5 | "East" | | 6 | "London" |
| | globalScore | 0.988 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 50 | | 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 | 938 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 77 | | matches | (empty) | |
| 90.75% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 28 | | mean | 33.5 | | std | 15.67 | | cv | 0.468 | | sampleLengths | | 0 | 69 | | 1 | 22 | | 2 | 34 | | 3 | 40 | | 4 | 49 | | 5 | 46 | | 6 | 19 | | 7 | 46 | | 8 | 20 | | 9 | 41 | | 10 | 48 | | 11 | 22 | | 12 | 39 | | 13 | 2 | | 14 | 25 | | 15 | 47 | | 16 | 17 | | 17 | 57 | | 18 | 40 | | 19 | 22 | | 20 | 25 | | 21 | 25 | | 22 | 40 | | 23 | 52 | | 24 | 7 | | 25 | 35 | | 26 | 10 | | 27 | 39 |
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| 99.87% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 65 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 112 | | matches | (empty) | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 8 | | semicolonCount | 0 | | flaggedSentences | 5 | | totalSentences | 77 | | ratio | 0.065 | | matches | | 0 | "He tilted his head, the strange eyes—amber and obsidian—glinting in the gloom." | | 1 | "The flat’s cluttered disorder—a stack of takeaway menus, a half-read notebook on Victorian law—felt suddenly like a taunt." | | 2 | "The memory rose unbidden—storm-lit nights in a Marseille safehouse, his hands warm on her bare skin as she’d scrawled *Find me if you survive* before vanishing into the dark." | | 3 | "The old code between them—the one that had started as flirtation, curdled into desperation." | | 4 | "The paper was thick, ink smudged at the edges—the kind Yu-Fei used for formal invoices." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 701 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 16 | | adverbRatio | 0.02282453637660485 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.007132667617689016 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 77 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 77 | | mean | 12.18 | | std | 6.74 | | cv | 0.553 | | sampleLengths | | 0 | 25 | | 1 | 30 | | 2 | 14 | | 3 | 8 | | 4 | 14 | | 5 | 12 | | 6 | 15 | | 7 | 7 | | 8 | 7 | | 9 | 9 | | 10 | 18 | | 11 | 1 | | 12 | 5 | | 13 | 25 | | 14 | 12 | | 15 | 9 | | 16 | 3 | | 17 | 21 | | 18 | 1 | | 19 | 13 | | 20 | 3 | | 21 | 8 | | 22 | 12 | | 23 | 7 | | 24 | 16 | | 25 | 8 | | 26 | 18 | | 27 | 4 | | 28 | 13 | | 29 | 7 | | 30 | 4 | | 31 | 29 | | 32 | 8 | | 33 | 9 | | 34 | 15 | | 35 | 24 | | 36 | 3 | | 37 | 15 | | 38 | 4 | | 39 | 19 | | 40 | 20 | | 41 | 2 | | 42 | 19 | | 43 | 6 | | 44 | 14 | | 45 | 22 | | 46 | 11 | | 47 | 17 | | 48 | 17 | | 49 | 15 |
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| 90.48% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 2 | | diversityRatio | 0.5584415584415584 | | totalSentences | 77 | | uniqueOpeners | 43 | |
| 55.56% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 60 | | matches | | 0 | "Somewhere outside, a church bell" |
| | ratio | 0.017 | |
| 60.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 24 | | totalSentences | 60 | | matches | | 0 | "she said, voice flat as" | | 1 | "Her left hand twitched toward" | | 2 | "He tilted his head, the" | | 3 | "His French accent was lighter" | | 4 | "She widened the door, arms" | | 5 | "He stepped inside without invitation," | | 6 | "She crossed her arms, the" | | 7 | "You’re not a child.*" | | 8 | "He turned slowly, the sleeves" | | 9 | "He reached into his jacket," | | 10 | "Her lungs went tight." | | 11 | "He flicked open his cane," | | 12 | "He took a step closer," | | 13 | "He switched to Mandarin, the" | | 14 | "*I owe you a life" | | 15 | "She remembered the feverish nights" | | 16 | "she said in English, though" | | 17 | "His thumb brushed the scar" | | 18 | "She snatched her hand back." | | 19 | "His eyes darkened." |
| | ratio | 0.4 | |
| 51.67% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 49 | | totalSentences | 60 | | matches | | 0 | "Aurora froze with her hand" | | 1 | "The man leaning against it" | | 2 | "she said, voice flat as" | | 3 | "Her left hand twitched toward" | | 4 | "He tilted his head, the" | | 5 | "His French accent was lighter" | | 6 | "The jab struck truer than" | | 7 | "She widened the door, arms" | | 8 | "The flat’s cluttered disorder—a stack" | | 9 | "He stepped inside without invitation," | | 10 | "Ptolemy’s tail flicked from the" | | 11 | "Lucien paused, fingers brushing the" | | 12 | "Aurora shut the door, but" | | 13 | "She crossed her arms, the" | | 14 | "You’re not a child.*" | | 15 | "He turned slowly, the sleeves" | | 16 | "The words clipped out sharper" | | 17 | "Lucien’s gaze dipped to her" | | 18 | "He reached into his jacket," | | 19 | "Her lungs went tight." |
| | ratio | 0.817 | |
| 83.33% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 60 | | matches | | 0 | "Before she could protest, he" |
| | ratio | 0.017 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 27 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 17 | | uselessAdditionCount | 6 | | matches | | 0 | "she said, voice flat as a blade" | | 1 | "He stepped, the cane tapping once against the warped floorboard" | | 2 | "He flicked, the blade gleaming faintly" | | 3 | "He switched, the words rolling off him like a second skin" | | 4 | "she said, though her pulse was a traitor, drumming harder" | | 5 | "She stopped, cheeks burning" |
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| 85.48% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 5 | | fancyCount | 2 | | fancyTags | | 0 | "she could (could)" | | 1 | "Lucien murmured (murmur)" |
| | dialogueSentences | 31 | | tagDensity | 0.161 | | leniency | 0.323 | | rawRatio | 0.4 | | effectiveRatio | 0.129 | |