| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 23 | | adverbTagCount | 1 | | adverbTags | | 0 | "she said finally [finally]" |
| | dialogueSentences | 59 | | tagDensity | 0.39 | | leniency | 0.78 | | rawRatio | 0.043 | | effectiveRatio | 0.034 | |
| 86.23% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1452 | | totalAiIsmAdverbs | 4 | | found | | | highlights | | 0 | "slightly" | | 1 | "suddenly" | | 2 | "really" |
| |
| 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) | |
| 41.46% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1452 | | totalAiIsms | 17 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | word | "carried the weight" | | count | 1 |
| | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | | | 13 | | | 14 | | | 15 | | word | "down her spine" | | count | 1 |
|
| | highlights | | 0 | "reminder" | | 1 | "pulse" | | 2 | "charged" | | 3 | "stomach" | | 4 | "carried the weight" | | 5 | "familiar" | | 6 | "traced" | | 7 | "throbbed" | | 8 | "tension" | | 9 | "scanning" | | 10 | "raced" | | 11 | "dance" | | 12 | "variable" | | 13 | "trembled" | | 14 | "unreadable" | | 15 | "down her spine" |
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| 66.67% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 3 | | maxInWindow | 2 | | found | | 0 | | label | "stomach dropped/sank" | | count | 1 |
| | 1 | | label | "sent a shiver through" | | count | 2 |
|
| | highlights | | 0 | "stomach dropped" | | 1 | "sent a jolt through" | | 2 | "sent a shiver down" |
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| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 117 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 117 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 153 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 34 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1445 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 20 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 33 | | wordCount | 1168 | | uniqueNames | 8 | | maxNameDensity | 0.86 | | worstName | "Rory" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Rory" | | discoveredNames | | Rory | 10 | | Eva | 5 | | Three | 1 | | Moreau | 1 | | French | 1 | | Ptolemy | 4 | | Lucien | 10 | | Christmas | 1 |
| | persons | | 0 | "Rory" | | 1 | "Eva" | | 2 | "Three" | | 3 | "Moreau" | | 4 | "Ptolemy" | | 5 | "Lucien" |
| | places | (empty) | | globalScore | 1 | | windowScore | 1 | |
| 56.25% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 80 | | glossingSentenceCount | 3 | | matches | | 0 | "something like gunpowder, trailing in his wa" | | 1 | "as if resisting the urge to reach down" | | 2 | "felt like a negotiation, a dance" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1445 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 3 | | totalSentences | 153 | | matches | | 0 | "chose that moment" | | 1 | "chose that moment" | | 2 | "unguarded, that she’d" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 64 | | mean | 22.58 | | std | 17.32 | | cv | 0.767 | | sampleLengths | | 0 | 61 | | 1 | 77 | | 2 | 9 | | 3 | 25 | | 4 | 63 | | 5 | 31 | | 6 | 26 | | 7 | 5 | | 8 | 43 | | 9 | 13 | | 10 | 42 | | 11 | 42 | | 12 | 22 | | 13 | 8 | | 14 | 36 | | 15 | 10 | | 16 | 17 | | 17 | 5 | | 18 | 27 | | 19 | 24 | | 20 | 7 | | 21 | 2 | | 22 | 64 | | 23 | 33 | | 24 | 2 | | 25 | 15 | | 26 | 14 | | 27 | 26 | | 28 | 4 | | 29 | 31 | | 30 | 44 | | 31 | 13 | | 32 | 29 | | 33 | 36 | | 34 | 28 | | 35 | 32 | | 36 | 6 | | 37 | 13 | | 38 | 15 | | 39 | 11 | | 40 | 6 | | 41 | 5 | | 42 | 52 | | 43 | 7 | | 44 | 6 | | 45 | 40 | | 46 | 6 | | 47 | 10 | | 48 | 26 | | 49 | 25 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 117 | | matches | (empty) | |
| 47.79% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 5 | | totalVerbs | 219 | | matches | | 0 | "was wiping" | | 1 | "was looking" | | 2 | "was referring" | | 3 | "was looking" | | 4 | "was watching" |
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| 12.14% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 8 | | semicolonCount | 0 | | flaggedSentences | 7 | | totalSentences | 153 | | ratio | 0.046 | | matches | | 0 | "No one visited Eva’s flat unannounced—not without calling first, not with the way the building’s stairs groaned underfoot like a warning." | | 1 | "The flat was a mess—scrolls unspooled across the coffee table, a half-empty cup of cold tea beside them, Eva’s latest research on demonic sigils splayed open like a fan of tarot cards." | | 2 | "But the way he was looking at her—like she was a puzzle he’d been trying to solve for years—made her step aside." | | 3 | "She knew what he was referring to—the night she’d carved a sigil into her own wrist to break a binding spell, the night she’d nearly bled out on Eva’s floor." | | 4 | "There were notes in the margins in Lucien’s precise script—corrections, suggestions, the occasional sharp remark." | | 5 | "But the truth was, she’d missed this—the way her mind raced when he was near, the way every word between them felt like a negotiation, a dance." | | 6 | "Not for himself—for his people." |
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| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1183 | | adjectiveStacks | 1 | | stackExamples | | 0 | "small, leather-bound book." |
| | adverbCount | 42 | | adverbRatio | 0.03550295857988166 | | lyAdverbCount | 12 | | lyAdverbRatio | 0.01014370245139476 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 153 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 153 | | mean | 9.44 | | std | 6.8 | | cv | 0.72 | | sampleLengths | | 0 | 24 | | 1 | 7 | | 2 | 21 | | 3 | 6 | | 4 | 3 | | 5 | 15 | | 6 | 10 | | 7 | 32 | | 8 | 10 | | 9 | 10 | | 10 | 9 | | 11 | 12 | | 12 | 13 | | 13 | 21 | | 14 | 19 | | 15 | 14 | | 16 | 7 | | 17 | 2 | | 18 | 3 | | 19 | 7 | | 20 | 21 | | 21 | 6 | | 22 | 10 | | 23 | 10 | | 24 | 4 | | 25 | 1 | | 26 | 2 | | 27 | 16 | | 28 | 25 | | 29 | 6 | | 30 | 7 | | 31 | 4 | | 32 | 16 | | 33 | 22 | | 34 | 18 | | 35 | 18 | | 36 | 6 | | 37 | 10 | | 38 | 12 | | 39 | 3 | | 40 | 5 | | 41 | 12 | | 42 | 16 | | 43 | 8 | | 44 | 5 | | 45 | 5 | | 46 | 13 | | 47 | 4 | | 48 | 3 | | 49 | 2 |
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| 48.37% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 6 | | diversityRatio | 0.3137254901960784 | | totalSentences | 153 | | uniqueOpeners | 48 | |
| 32.68% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 102 | | matches | | | ratio | 0.01 | |
| 31.76% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 48 | | totalSentences | 102 | | matches | | 0 | "She froze, the dish towel" | | 1 | "She smoothed her hair back," | | 2 | "she muttered, flipping the deadbolts" | | 3 | "He leaned slightly on his" | | 4 | "Her pulse jumped." | | 5 | "She hadn’t seen him in" | | 6 | "he said, voice low, accented" | | 7 | "She crossed her arms." | | 8 | "He tilted his head, just" | | 9 | "She should say no." | | 10 | "She should slam the door" | | 11 | "He took in the flat" | | 12 | "He turned to face her" | | 13 | "Her stomach dropped." | | 14 | "His voice was quiet, but" | | 15 | "He stopped, jaw tightening" | | 16 | "She looked away, heat creeping" | | 17 | "He reached into his coat" | | 18 | "She reached for it, but" | | 19 | "His fingers brushed hers, and" |
| | ratio | 0.471 | |
| 38.43% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 86 | | totalSentences | 102 | | matches | | 0 | "The first knock came just" | | 1 | "She froze, the dish towel" | | 2 | "The second knock was firmer," | | 3 | "A man’s knock." | | 4 | "Ptolemy, the tabby cat, lifted" | | 5 | "Rory exhaled through her nose" | | 6 | "The flat was a mess—scrolls" | | 7 | "She smoothed her hair back," | | 8 | "The black strands had escaped" | | 9 | "The third knock came before" | | 10 | "she muttered, flipping the deadbolts" | | 11 | "Lucien Moreau stood in the" | | 12 | "The amber and black of" | | 13 | "He leaned slightly on his" | | 14 | "The cane was a prop," | | 15 | "Her pulse jumped." | | 16 | "She hadn’t seen him in" | | 17 | "he said, voice low, accented" | | 18 | "French, but not the kind" | | 19 | "This was the kind that" |
| | ratio | 0.843 | |
| 49.02% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 102 | | matches | | 0 | "As if any ground between" |
| | ratio | 0.01 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 48 | | technicalSentenceCount | 1 | | matches | | 0 | "The half-demon didn’t flinch, though his fingers twitched, as if resisting the urge to reach down." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 23 | | uselessAdditionCount | 6 | | matches | | 0 | "he said, voice low, accented" | | 1 | "He stopped, jaw tightening" | | 2 | "she said, stupidly" | | 3 | "he replied, as if that explained everything" | | 4 | "he said, as if that made sense" | | 5 | "He held out, the picture of old-world chivalry" |
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| 99.15% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 15 | | fancyCount | 3 | | fancyTags | | 0 | "she muttered (mutter)" | | 1 | "he agreed (agree)" | | 2 | "she muttered (mutter)" |
| | dialogueSentences | 59 | | tagDensity | 0.254 | | leniency | 0.508 | | rawRatio | 0.2 | | effectiveRatio | 0.102 | |