| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 14 | | adverbTagCount | 1 | | adverbTags | | 0 | "he replied softly [softly]" |
| | dialogueSentences | 40 | | tagDensity | 0.35 | | leniency | 0.7 | | rawRatio | 0.071 | | effectiveRatio | 0.05 | |
| 64.07% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 974 | | totalAiIsmAdverbs | 7 | | found | | | highlights | | 0 | "quickly" | | 1 | "lightly" | | 2 | "really" | | 3 | "slowly" | | 4 | "suddenly" | | 5 | "softly" |
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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) | |
| 23.00% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 974 | | totalAiIsms | 15 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | word | "down her spine" | | count | 1 |
| | 8 | | | 9 | | | 10 | | | 11 | | | 12 | | | 13 | |
| | highlights | | 0 | "pounding" | | 1 | "solace" | | 2 | "lurched" | | 3 | "familiar" | | 4 | "whisper" | | 5 | "weight" | | 6 | "throbbed" | | 7 | "down her spine" | | 8 | "treacherous" | | 9 | "silence" | | 10 | "quickened" | | 11 | "measured" | | 12 | "unspoken" | | 13 | "eyebrow" |
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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 | 1 | | narrationSentences | 61 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 61 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 84 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 26 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 964 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 16 | | unquotedAttributions | 0 | | matches | (empty) | |
| 83.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 22 | | wordCount | 680 | | uniqueNames | 8 | | maxNameDensity | 1.32 | | worstName | "Rory" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Lucien" | | discoveredNames | | Aurora | 1 | | Poe | 1 | | Rory | 9 | | Eva | 1 | | Trust | 1 | | London | 1 | | Hurt | 1 | | Lucien | 7 |
| | persons | | 0 | "Aurora" | | 1 | "Poe" | | 2 | "Rory" | | 3 | "Eva" | | 4 | "Trust" | | 5 | "Hurt" | | 6 | "Lucien" |
| | places | | | globalScore | 0.838 | | windowScore | 0.833 | |
| 93.18% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 44 | | glossingSentenceCount | 1 | | matches | | 0 | "felt like old times, a dangerous famili" |
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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 | 964 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 84 | | matches | | |
| 99.18% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 40 | | mean | 24.1 | | std | 11.98 | | cv | 0.497 | | sampleLengths | | 0 | 55 | | 1 | 43 | | 2 | 10 | | 3 | 31 | | 4 | 17 | | 5 | 48 | | 6 | 30 | | 7 | 29 | | 8 | 42 | | 9 | 30 | | 10 | 34 | | 11 | 15 | | 12 | 16 | | 13 | 16 | | 14 | 26 | | 15 | 32 | | 16 | 30 | | 17 | 19 | | 18 | 27 | | 19 | 14 | | 20 | 7 | | 21 | 9 | | 22 | 37 | | 23 | 18 | | 24 | 16 | | 25 | 22 | | 26 | 28 | | 27 | 28 | | 28 | 16 | | 29 | 14 | | 30 | 28 | | 31 | 46 | | 32 | 6 | | 33 | 13 | | 34 | 8 | | 35 | 16 | | 36 | 17 | | 37 | 14 | | 38 | 20 | | 39 | 37 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 61 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 126 | | matches | | |
| 6.80% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 6 | | semicolonCount | 0 | | flaggedSentences | 4 | | totalSentences | 84 | | ratio | 0.048 | | matches | | 0 | "Her mind scrambled—could it be Eva?" | | 1 | "The heterochromatic stare—one eye amber, the other black—was penetrating as ever." | | 2 | "Rory bristled at his tone, recalling the last time she had seen those eyes lit with a similar amusement—before everything between them had gone awry." | | 3 | "Lucien took a step closer, the scent of his cologne—spiced cedar and something darker—flooded her senses." |
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| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 689 | | adjectiveStacks | 1 | | stackExamples | | 0 | "small crescent-shaped scar" |
| | adverbCount | 25 | | adverbRatio | 0.036284470246734396 | | lyAdverbCount | 13 | | lyAdverbRatio | 0.018867924528301886 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 84 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 84 | | mean | 11.48 | | std | 6.04 | | cv | 0.526 | | sampleLengths | | 0 | 23 | | 1 | 3 | | 2 | 7 | | 3 | 22 | | 4 | 6 | | 5 | 5 | | 6 | 6 | | 7 | 1 | | 8 | 25 | | 9 | 10 | | 10 | 20 | | 11 | 11 | | 12 | 13 | | 13 | 4 | | 14 | 7 | | 15 | 13 | | 16 | 11 | | 17 | 17 | | 18 | 15 | | 19 | 15 | | 20 | 16 | | 21 | 13 | | 22 | 17 | | 23 | 25 | | 24 | 8 | | 25 | 14 | | 26 | 8 | | 27 | 25 | | 28 | 9 | | 29 | 15 | | 30 | 9 | | 31 | 7 | | 32 | 10 | | 33 | 6 | | 34 | 11 | | 35 | 15 | | 36 | 16 | | 37 | 16 | | 38 | 18 | | 39 | 12 | | 40 | 3 | | 41 | 16 | | 42 | 11 | | 43 | 16 | | 44 | 11 | | 45 | 3 | | 46 | 3 | | 47 | 4 | | 48 | 3 | | 49 | 6 |
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| 81.35% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 0 | | diversityRatio | 0.4880952380952381 | | totalSentences | 84 | | uniqueOpeners | 41 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 56 | | matches | (empty) | | ratio | 0 | |
| 20.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 28 | | totalSentences | 56 | | matches | | 0 | "Her heart lurched." | | 1 | "Her mind scrambled—could it be" | | 2 | "His name slipped from her" | | 3 | "He stood there, impeccably dressed" | | 4 | "he replied, the tiniest smirk" | | 5 | "She stepped aside, the door" | | 6 | "He entered the flat with" | | 7 | "she asked, closing the door" | | 8 | "he replied, the nonchalance in" | | 9 | "His amber eye glinted with" | | 10 | "He exhaled slowly, his eyes" | | 11 | "She scoffed, more out of" | | 12 | "he finished for her, his" | | 13 | "Her eyes narrowed, scrutinizing every" | | 14 | "She paused, the truth behind" | | 15 | "she finally asked" | | 16 | "His face tightened." | | 17 | "Their eyes locked, a battle" | | 18 | "Her voice rose" | | 19 | "he replied softly" |
| | ratio | 0.5 | |
| 31.43% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 48 | | totalSentences | 56 | | matches | | 0 | "The frantic pounding on Aurora's" | | 1 | "Her heart lurched." | | 2 | "Her mind scrambled—could it be" | | 3 | "Yu-Fei needing an emergency shift" | | 4 | "The door swung open to" | | 5 | "His name slipped from her" | | 6 | "He stood there, impeccably dressed" | | 7 | "The heterochromatic stare—one eye amber," | | 8 | "he replied, the tiniest smirk" | | 9 | "The request sounded more rhetorical" | | 10 | "She stepped aside, the door" | | 11 | "He entered the flat with" | | 12 | "she asked, closing the door" | | 13 | "The weight of their history" | | 14 | "he replied, the nonchalance in" | | 15 | "His amber eye glinted with" | | 16 | "Rory bristled at his tone," | | 17 | "Rory said, crossing her arms" | | 18 | "The small crescent-shaped scar on" | | 19 | "Lucien glanced around the flat," |
| | ratio | 0.857 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 56 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 28 | | technicalSentenceCount | 1 | | matches | | 0 | "Rory's heartbeat quickened, memories of nights spent entwined, confessions whispered in the dark, and the inevitable fracture that had torn them apart flooding …" |
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| 53.57% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 14 | | uselessAdditionCount | 2 | | matches | | 0 | "he finished, his tone suddenly serious" | | 1 | "she pressed, the unspoken question lingering between them: What happens to us" |
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| 50.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 11 | | fancyCount | 4 | | fancyTags | | 0 | "he conceded (concede)" | | 1 | "she snapped (snap)" | | 2 | "she pressed (press)" | | 3 | "he teased (tease)" |
| | dialogueSentences | 40 | | tagDensity | 0.275 | | leniency | 0.55 | | rawRatio | 0.364 | | effectiveRatio | 0.2 | |