| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 8 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 41 | | tagDensity | 0.195 | | leniency | 0.39 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 95.01% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1003 | | totalAiIsmAdverbs | 1 | | 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) | |
| 0.00% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1003 | | totalAiIsms | 21 | | found | | | highlights | | 0 | "otherworldly" | | 1 | "intensity" | | 2 | "familiar" | | 3 | "silk" | | 4 | "eyebrow" | | 5 | "tension" | | 6 | "warmth" | | 7 | "silence" | | 8 | "unreadable" | | 9 | "measured" | | 10 | "racing" | | 11 | "tracing" | | 12 | "palpable" | | 13 | "sense of" | | 14 | "glint" | | 15 | "weight" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 48 | | matches | (empty) | |
| 53.57% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 3 | | narrationSentences | 48 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 81 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 31 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 996 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 12 | | unquotedAttributions | 0 | | matches | (empty) | |
| 47.26% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 26 | | wordCount | 584 | | uniqueNames | 6 | | maxNameDensity | 2.05 | | worstName | "Aurora" | | maxWindowNameDensity | 3 | | worstWindowName | "Aurora" | | discoveredNames | | Eva | 2 | | Golden | 1 | | Empress | 1 | | Lucien | 9 | | Ptolemy | 1 | | Aurora | 12 |
| | persons | | 0 | "Eva" | | 1 | "Empress" | | 2 | "Lucien" | | 3 | "Ptolemy" | | 4 | "Aurora" |
| | places | | | globalScore | 0.473 | | windowScore | 0.667 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 41 | | 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 | 996 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 81 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 39 | | mean | 25.54 | | std | 14.58 | | cv | 0.571 | | sampleLengths | | 0 | 76 | | 1 | 36 | | 2 | 15 | | 3 | 23 | | 4 | 31 | | 5 | 11 | | 6 | 22 | | 7 | 35 | | 8 | 21 | | 9 | 26 | | 10 | 30 | | 11 | 18 | | 12 | 47 | | 13 | 16 | | 14 | 20 | | 15 | 10 | | 16 | 45 | | 17 | 27 | | 18 | 5 | | 19 | 31 | | 20 | 17 | | 21 | 26 | | 22 | 22 | | 23 | 31 | | 24 | 48 | | 25 | 17 | | 26 | 20 | | 27 | 1 | | 28 | 15 | | 29 | 18 | | 30 | 14 | | 31 | 61 | | 32 | 23 | | 33 | 27 | | 34 | 17 | | 35 | 17 | | 36 | 22 | | 37 | 14 | | 38 | 41 |
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| 97.95% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 48 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 100 | | matches | (empty) | |
| 72.31% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 3 | | semicolonCount | 0 | | flaggedSentences | 2 | | totalSentences | 81 | | ratio | 0.025 | | matches | | 0 | "His slicked-back platinum blond hair glistened under the dim hallway light, and his heterochromatic eyes—amber and black—seemed to burn with an otherworldly intensity." | | 1 | "His heterochromatic eyes held hers, and for a moment, she saw something there—something raw and honest." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 590 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 16 | | adverbRatio | 0.02711864406779661 | | lyAdverbCount | 3 | | lyAdverbRatio | 0.005084745762711864 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 81 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 81 | | mean | 12.3 | | std | 6.86 | | cv | 0.558 | | sampleLengths | | 0 | 17 | | 1 | 24 | | 2 | 12 | | 3 | 23 | | 4 | 11 | | 5 | 25 | | 6 | 8 | | 7 | 7 | | 8 | 19 | | 9 | 4 | | 10 | 20 | | 11 | 11 | | 12 | 9 | | 13 | 2 | | 14 | 11 | | 15 | 11 | | 16 | 15 | | 17 | 20 | | 18 | 11 | | 19 | 10 | | 20 | 26 | | 21 | 9 | | 22 | 21 | | 23 | 7 | | 24 | 11 | | 25 | 9 | | 26 | 22 | | 27 | 7 | | 28 | 9 | | 29 | 9 | | 30 | 7 | | 31 | 9 | | 32 | 11 | | 33 | 9 | | 34 | 1 | | 35 | 20 | | 36 | 19 | | 37 | 6 | | 38 | 12 | | 39 | 15 | | 40 | 3 | | 41 | 2 | | 42 | 31 | | 43 | 8 | | 44 | 9 | | 45 | 26 | | 46 | 6 | | 47 | 16 | | 48 | 10 | | 49 | 21 |
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| 58.85% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 4 | | diversityRatio | 0.38271604938271603 | | totalSentences | 81 | | uniqueOpeners | 31 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 46 | | matches | (empty) | | ratio | 0 | |
| 37.39% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 21 | | totalSentences | 46 | | matches | | 0 | "His presence, as ever, was" | | 1 | "His slicked-back platinum blond hair" | | 2 | "She shifted the takeout bag" | | 3 | "he greeted, his voice smooth" | | 4 | "she retorted, unlocking the door" | | 5 | "he said, his tone serious" | | 6 | "He took a step closer," | | 7 | "She crossed her arms, her" | | 8 | "She couldn’t deny the old" | | 9 | "she admitted, her voice softening" | | 10 | "He extended his hand, his" | | 11 | "She hesitated, her gaze flicking" | | 12 | "They settled into an uneasy" | | 13 | "he began, his tone measured" | | 14 | "She sighed, setting down the" | | 15 | "She remembered the last time" | | 16 | "She looked up, meeting his" | | 17 | "His heterochromatic eyes held hers," | | 18 | "They spent the next few" | | 19 | "She met his gaze, a" |
| | ratio | 0.457 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 45 | | totalSentences | 46 | | matches | | 0 | "The front door of Eva’s" | | 1 | "Aurora, hands full with a" | | 2 | "His presence, as ever, was" | | 3 | "His slicked-back platinum blond hair" | | 4 | "Aurora muttered, the word a" | | 5 | "She shifted the takeout bag" | | 6 | "he greeted, his voice smooth" | | 7 | "she retorted, unlocking the door" | | 8 | "The flat, already cluttered with" | | 9 | "The tabby cat, Ptolemy, meowed" | | 10 | "he said, his tone serious" | | 11 | "Aurora raised an eyebrow, setting" | | 12 | "He took a step closer," | | 13 | "Rory sighed, running a hand" | | 14 | "She crossed her arms, her" | | 15 | "Lucien’s lips twisted into a" | | 16 | "Aurora felt a familiar heat" | | 17 | "She couldn’t deny the old" | | 18 | "she admitted, her voice softening" | | 19 | "He extended his hand, his" |
| | ratio | 0.978 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 46 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 25 | | technicalSentenceCount | 1 | | matches | | 0 | "They spent the next few hours poring over the research notes scattered across the table, their hands brushing against each other more than once." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 8 | | uselessAdditionCount | 5 | | matches | | 0 | "Aurora muttered, the word a mix of surprise and irritation" | | 1 | "he greeted, his voice smooth as silk" | | 2 | "he said, his tone serious" | | 3 | "she admitted, her voice softening" | | 4 | "he began, his tone measured" |
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| 28.05% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 6 | | fancyCount | 5 | | fancyTags | | 0 | "Aurora muttered (mutter)" | | 1 | "she retorted (retort)" | | 2 | "she admitted (admit)" | | 3 | "he insisted (insist)" | | 4 | "she whispered (whisper)" |
| | dialogueSentences | 41 | | tagDensity | 0.146 | | leniency | 0.293 | | rawRatio | 0.833 | | effectiveRatio | 0.244 | |