| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 12 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 27 | | tagDensity | 0.444 | | leniency | 0.889 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 89.24% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 929 | | totalAiIsmAdverbs | 2 | | found | | | highlights | | |
| 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) | |
| 8.50% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 929 | | totalAiIsms | 17 | | found | | | highlights | | 0 | "scanned" | | 1 | "amidst" | | 2 | "pulsed" | | 3 | "sanctuary" | | 4 | "predator" | | 5 | "rhythmic" | | 6 | "whisper" | | 7 | "warmth" | | 8 | "eyebrow" | | 9 | "velvet" | | 10 | "reminder" | | 11 | "intricate" | | 12 | "intensity" | | 13 | "charged" | | 14 | "pounding" | | 15 | "calculating" |
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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 | 72 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 72 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 86 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 29 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 1 | | markdownWords | 6 | | totalWords | 916 | | ratio | 0.007 | | matches | | 0 | "Meet me. Now. At the source." |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 16 | | unquotedAttributions | 0 | | matches | (empty) | |
| 96.60% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 24 | | wordCount | 749 | | uniqueNames | 11 | | maxNameDensity | 1.07 | | worstName | "Aurora" | | maxWindowNameDensity | 2 | | worstWindowName | "Aurora" | | discoveredNames | | Carter | 1 | | Rory | 1 | | Laila | 1 | | Eva | 1 | | Lucien | 6 | | Moreau | 2 | | Ptolemy | 1 | | Aurora | 8 | | London | 1 | | Evan | 1 | | Avaros | 1 |
| | persons | | 0 | "Carter" | | 1 | "Rory" | | 2 | "Laila" | | 3 | "Eva" | | 4 | "Lucien" | | 5 | "Moreau" | | 6 | "Ptolemy" | | 7 | "Aurora" | | 8 | "Evan" |
| | places | | | globalScore | 0.966 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 54 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 0.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 3 | | per1kWords | 3.275 | | wordCount | 916 | | matches | | 0 | "not from exertion, but from the sudden, unwelcome pressure of Lucien Moreau’s prese" | | 1 | "not just from Evan, but from the demons" | | 2 | "not from his words, but from the memory of his touch" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 86 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 23 | | mean | 39.83 | | std | 24.1 | | cv | 0.605 | | sampleLengths | | 0 | 98 | | 1 | 68 | | 2 | 77 | | 3 | 19 | | 4 | 67 | | 5 | 14 | | 6 | 58 | | 7 | 50 | | 8 | 54 | | 9 | 19 | | 10 | 35 | | 11 | 6 | | 12 | 28 | | 13 | 39 | | 14 | 15 | | 15 | 53 | | 16 | 56 | | 17 | 13 | | 18 | 21 | | 19 | 25 | | 20 | 27 | | 21 | 14 | | 22 | 60 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 72 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 122 | | matches | | |
| 9.97% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 5 | | semicolonCount | 0 | | flaggedSentences | 4 | | totalSentences | 86 | | ratio | 0.047 | | matches | | 0 | "The flat was a tomb of books—tomes on demonology, faded maps, and journals filled with Aurora’s frantic scrawl." | | 1 | "The scent of his expensive cologne—cinnamon and smoke—filled the air." | | 2 | "Inside lay a silver locket, engraved with a single, intricate symbol—the same one that had haunted her dreams for months." | | 3 | "The world narrowed to the space between them, charged with the electricity of their history—attraction, hurt, and things left unsaid." |
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| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 760 | | adjectiveStacks | 1 | | stackExamples | | 0 | "small, velvet-lined box." |
| | adverbCount | 16 | | adverbRatio | 0.021052631578947368 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.006578947368421052 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 86 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 86 | | mean | 10.65 | | std | 6.04 | | cv | 0.567 | | sampleLengths | | 0 | 7 | | 1 | 15 | | 2 | 28 | | 3 | 20 | | 4 | 4 | | 5 | 20 | | 6 | 1 | | 7 | 3 | | 8 | 3 | | 9 | 2 | | 10 | 17 | | 11 | 14 | | 12 | 18 | | 13 | 14 | | 14 | 4 | | 15 | 4 | | 16 | 13 | | 17 | 13 | | 18 | 9 | | 19 | 10 | | 20 | 17 | | 21 | 7 | | 22 | 14 | | 23 | 5 | | 24 | 3 | | 25 | 4 | | 26 | 19 | | 27 | 16 | | 28 | 13 | | 29 | 12 | | 30 | 11 | | 31 | 3 | | 32 | 15 | | 33 | 10 | | 34 | 20 | | 35 | 4 | | 36 | 4 | | 37 | 5 | | 38 | 10 | | 39 | 16 | | 40 | 14 | | 41 | 10 | | 42 | 13 | | 43 | 17 | | 44 | 9 | | 45 | 15 | | 46 | 16 | | 47 | 3 | | 48 | 7 | | 49 | 23 |
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| 51.55% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 9 | | diversityRatio | 0.37209302325581395 | | totalSentences | 86 | | uniqueOpeners | 32 | |
| 48.31% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 69 | | matches | | 0 | "Just waited, every muscle coiled," |
| | ratio | 0.014 | |
| 40.29% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 31 | | totalSentences | 69 | | matches | | 0 | "Her breath hitched, not from" | | 1 | "She’d known he’d come." | | 2 | "She didn’t turn." | | 3 | "He hovered in the threshold," | | 4 | "His platinum hair, slicked back" | | 5 | "His tailored charcoal suit looked" | | 6 | "His voice was a low" | | 7 | "She’d fled London then, not" | | 8 | "she said, her voice cool," | | 9 | "He stepped fully into the" | | 10 | "He didn’t look at the" | | 11 | "He looked at her." | | 12 | "His amber eye narrowed." | | 13 | "He moved with unsettling grace," | | 14 | "His ivory-handled cane tapped the" | | 15 | "he murmured, his voice dropping" | | 16 | "He’d left her broken, a" | | 17 | "she retorted, forcing a smile" | | 18 | "His laugh was dry, devoid" | | 19 | "He gestured at the flat" |
| | ratio | 0.449 | |
| 17.97% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 61 | | totalSentences | 69 | | matches | | 0 | "Thedeadbolt scraped like a fingernail" | | 1 | "Aurora Carter, alias Rory, alias" | | 2 | "Her breath hitched, not from" | | 3 | "She’d known he’d come." | | 4 | "The scent of expensive leather" | | 5 | "She didn’t turn." | | 6 | "The tabby cat, Ptolemy, blinked" | | 7 | "The flat was a tomb" | | 8 | "The air hung thick with" | | 9 | "The door groaned open." | | 10 | "Lucien Moreau didn’t enter." | | 11 | "He hovered in the threshold," | | 12 | "His platinum hair, slicked back" | | 13 | "The other, black as a" | | 14 | "His tailored charcoal suit looked" | | 15 | "A faint, amused curve touched" | | 16 | "His voice was a low" | | 17 | "Aurora didn’t move." | | 18 | "The scar on her wrist" | | 19 | "She’d fled London then, not" |
| | ratio | 0.884 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 69 | | matches | | 0 | "Now he stood in her" | | 1 | "Now he stood before her," |
| | ratio | 0.029 | |
| 99.57% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 33 | | technicalSentenceCount | 2 | | matches | | 0 | "The scar on her wrist pulsed, a ghost of a childhood accident that had nearly cost her her leg." | | 1 | "Aurora stared into his heterochromatic eyes, the amber one burning with an intensity that mirrored the black." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 12 | | uselessAdditionCount | 8 | | matches | | 0 | "she said, her voice cool, controlled" | | 1 | "he murmured, his voice dropping to a whisper that brushed her ear" | | 2 | "she whispered, her voice trembling" | | 3 | "he said, his voice hardening" | | 4 | "He closed, his breath hot against her skin" | | 5 | "she breathed, her voice barely a whisper" | | 6 | "he murmured, his lips brushing hers" | | 7 | "she said, her voice tight" |
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| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 9 | | fancyCount | 6 | | fancyTags | | 0 | "he murmured (murmur)" | | 1 | "she retorted (retort)" | | 2 | "she snapped (snap)" | | 3 | "she whispered (whisper)" | | 4 | "she breathed (breathe)" | | 5 | "he murmured (murmur)" |
| | dialogueSentences | 27 | | tagDensity | 0.333 | | leniency | 0.667 | | rawRatio | 0.667 | | effectiveRatio | 0.444 | |