| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 9 | | adverbTagCount | 1 | | adverbTags | | 0 | "he said quietly [quietly]" |
| | dialogueSentences | 26 | | tagDensity | 0.346 | | leniency | 0.692 | | rawRatio | 0.111 | | effectiveRatio | 0.077 | |
| 89.70% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 971 | | 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) | |
| 53.66% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 971 | | totalAiIsms | 9 | | found | | 0 | | | 1 | | | 2 | | word | "down her spine" | | count | 1 |
| | 3 | | | 4 | | | 5 | | | 6 | | | 7 | |
| | highlights | | 0 | "pristine" | | 1 | "unreadable" | | 2 | "down her spine" | | 3 | "flicked" | | 4 | "silence" | | 5 | "pulse" | | 6 | "weight" | | 7 | "echoing" |
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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 | 58 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 58 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 75 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 46 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 2 | | markdownWords | 4 | | totalWords | 965 | | ratio | 0.004 | | matches | | 0 | "Divination for Beginners" | | 1 | "pleasure" |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 12 | | unquotedAttributions | 1 | | matches | | 0 | "Somewhere in the room, Ptolemy hissed." |
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| 81.92% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 28 | | wordCount | 661 | | uniqueNames | 12 | | maxNameDensity | 1.36 | | worstName | "Aurora" | | maxWindowNameDensity | 2 | | worstWindowName | "Aurora" | | discoveredNames | | Aurora | 9 | | Golden | 1 | | Empress | 1 | | Brick | 1 | | Lane | 1 | | Eva | 4 | | Ptolemy | 3 | | Moreau | 1 | | Paris | 1 | | Evan | 1 | | French | 1 | | Lucien | 4 |
| | persons | | 0 | "Aurora" | | 1 | "Eva" | | 2 | "Ptolemy" | | 3 | "Moreau" | | 4 | "Evan" | | 5 | "Lucien" |
| | places | | 0 | "Golden" | | 1 | "Brick" | | 2 | "Lane" | | 3 | "Paris" |
| | globalScore | 0.819 | | windowScore | 1 | |
| 87.50% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 40 | | glossingSentenceCount | 1 | | matches | | 0 | "felt like she’d been tapped over the he" |
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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 | 965 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 75 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 31 | | mean | 31.13 | | std | 20.88 | | cv | 0.671 | | sampleLengths | | 0 | 78 | | 1 | 4 | | 2 | 2 | | 3 | 61 | | 4 | 4 | | 5 | 69 | | 6 | 6 | | 7 | 42 | | 8 | 34 | | 9 | 35 | | 10 | 43 | | 11 | 20 | | 12 | 64 | | 13 | 67 | | 14 | 9 | | 15 | 11 | | 16 | 30 | | 17 | 50 | | 18 | 31 | | 19 | 32 | | 20 | 35 | | 21 | 20 | | 22 | 16 | | 23 | 45 | | 24 | 29 | | 25 | 4 | | 26 | 34 | | 27 | 33 | | 28 | 6 | | 29 | 28 | | 30 | 23 |
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| 93.16% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 58 | | matches | | 0 | "been tapped" | | 1 | "been trained" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 109 | | matches | (empty) | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 5 | | semicolonCount | 0 | | flaggedSentences | 5 | | totalSentences | 75 | | ratio | 0.067 | | matches | | 0 | "There was no guest—just Ptolemy lounging on the windowsill, tail flicking like a metronome." | | 1 | "The scent of sandalwood and something sharper hit her first—smoke, maybe, or blood." | | 2 | "His smirk didn’t reach his eyes—the amber one glinted, but the black one stayed flat, unreadable." | | 3 | "He’d always been like this—too sure, too far above the rules, always brushing against the danger she’d been trained to avoid." | | 4 | "The police report had been clean, the coroner’s findings unremarkable, but she’d seen the way the left side of Evan’s neck had healed—too fast, too smooth." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 668 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 26 | | adverbRatio | 0.038922155688622756 | | lyAdverbCount | 2 | | lyAdverbRatio | 0.0029940119760479044 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 75 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 75 | | mean | 12.87 | | std | 8.99 | | cv | 0.699 | | sampleLengths | | 0 | 27 | | 1 | 27 | | 2 | 24 | | 3 | 4 | | 4 | 2 | | 5 | 18 | | 6 | 14 | | 7 | 13 | | 8 | 16 | | 9 | 4 | | 10 | 13 | | 11 | 26 | | 12 | 30 | | 13 | 3 | | 14 | 3 | | 15 | 13 | | 16 | 14 | | 17 | 15 | | 18 | 16 | | 19 | 10 | | 20 | 8 | | 21 | 5 | | 22 | 21 | | 23 | 2 | | 24 | 7 | | 25 | 14 | | 26 | 29 | | 27 | 7 | | 28 | 13 | | 29 | 6 | | 30 | 46 | | 31 | 12 | | 32 | 16 | | 33 | 21 | | 34 | 11 | | 35 | 19 | | 36 | 3 | | 37 | 6 | | 38 | 3 | | 39 | 8 | | 40 | 6 | | 41 | 24 | | 42 | 10 | | 43 | 13 | | 44 | 9 | | 45 | 8 | | 46 | 10 | | 47 | 21 | | 48 | 10 | | 49 | 20 |
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| 58.67% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 1 | | diversityRatio | 0.36 | | totalSentences | 75 | | uniqueOpeners | 27 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 49 | | matches | | 0 | "Somewhere in the room, Ptolemy" | | 1 | "Somewhere downstairs, a car radio" |
| | ratio | 0.041 | |
| 64.90% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 19 | | totalSentences | 49 | | matches | | 0 | "She’d just dropped off a" | | 1 | "Her black hair hung limp," | | 2 | "She opened the door." | | 3 | "He looked her up and" | | 4 | "His smirk didn’t reach his" | | 5 | "He tapped the head of" | | 6 | "He stepped inside anyway, the" | | 7 | "His laugh had a brittle" | | 8 | "He flicked his fingers at" | | 9 | "She moved to block him," | | 10 | "He’d always been like this—too" | | 11 | "he said quietly" | | 12 | "He took a step closer," | | 13 | "She gestured at the room," | | 14 | "His jaw tightened, the demon" | | 15 | "It wasn’t something a human" | | 16 | "She reached for the door." | | 17 | "He leaned in then, so" | | 18 | "It took her a full" |
| | ratio | 0.388 | |
| 11.02% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 44 | | totalSentences | 49 | | matches | | 0 | "The door to the flat" | | 1 | "She’d just dropped off a" | | 2 | "The three deadbolts clicked open" | | 3 | "A knock followed immediately." | | 4 | "The flat was a warren" | | 5 | "Aurora crossed the room, her" | | 6 | "Her black hair hung limp," | | 7 | "She opened the door." | | 8 | "The scent of sandalwood and" | | 9 | "Lucien Moreau stood in the" | | 10 | "He looked her up and" | | 11 | "The cat meowed from the" | | 12 | "Aurora crossed her arms, feeling" | | 13 | "His smirk didn’t reach his" | | 14 | "He tapped the head of" | | 15 | "Ice slithered down her spine." | | 16 | "The name sliced through the" | | 17 | "He stepped inside anyway, the" | | 18 | "Aurora slammed the door shut" | | 19 | "His laugh had a brittle" |
| | ratio | 0.898 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 49 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 28 | | technicalSentenceCount | 1 | | matches | | 0 | "The name sliced through the cluttered room behind her, knocking over Eva’s notes, spilling the names of dead ends and half-truths." |
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| 69.44% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 9 | | uselessAdditionCount | 1 | | matches | | 0 | "Aurora mimicked, her voice cold" |
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| 34.62% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 6 | | fancyCount | 3 | | fancyTags | | 0 | "she snapped (snap)" | | 1 | "he interrupted (interrupt)" | | 2 | "he whispered (whisper)" |
| | dialogueSentences | 26 | | tagDensity | 0.231 | | leniency | 0.462 | | rawRatio | 0.5 | | effectiveRatio | 0.231 | |