| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 20 | | adverbTagCount | 2 | | adverbTags | | 0 | "She gestured vaguely [vaguely]" | | 1 | "Aurora said smoothly [smoothly]" |
| | dialogueSentences | 50 | | tagDensity | 0.4 | | leniency | 0.8 | | rawRatio | 0.1 | | effectiveRatio | 0.08 | |
| 73.68% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1140 | | totalAiIsmAdverbs | 6 | | found | | | highlights | | 0 | "quickly" | | 1 | "carefully" | | 2 | "slightly" | | 3 | "suddenly" | | 4 | "really" | | 5 | "very" |
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| 100.00% | AI-ism character names | Target: 0 AI-default names (16 tracked, −20% each) | | codexExemptions | | | found | (empty) | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 21.05% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1140 | | totalAiIsms | 18 | | found | | | highlights | | 0 | "familiar" | | 1 | "weight" | | 2 | "constructed" | | 3 | "measured" | | 4 | "eyebrow" | | 5 | "flicker" | | 6 | "intricate" | | 7 | "silence" | | 8 | "unspoken" | | 9 | "reminder" | | 10 | "intensity" | | 11 | "chilling" | | 12 | "pang" | | 13 | "unreadable" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "weight of words/silence" | | count | 1 |
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| | highlights | | 0 | "The weight of her words" |
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| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 1 | | narrationSentences | 74 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 2 | | narrationSentences | 74 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 103 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 42 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1142 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 16 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 18 | | wordCount | 742 | | uniqueNames | 9 | | maxNameDensity | 0.81 | | worstName | "Aurora" | | maxWindowNameDensity | 2 | | worstWindowName | "Aurora" | | discoveredNames | | Raven | 1 | | Nest | 1 | | Silas | 5 | | Aurora | 6 | | Celtic | 1 | | Prague | 1 | | Nostalgia | 1 | | Pity | 1 | | Cheung | 1 |
| | persons | | 0 | "Raven" | | 1 | "Silas" | | 2 | "Aurora" | | 3 | "Cheung" |
| | places | | | globalScore | 1 | | windowScore | 1 | |
| 60.71% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 56 | | glossingSentenceCount | 2 | | matches | | 0 | "quite decipher – resentment" | | 1 | "something akin to fear" |
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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 | 1142 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 103 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 44 | | mean | 25.95 | | std | 19.02 | | cv | 0.733 | | sampleLengths | | 0 | 3 | | 1 | 66 | | 2 | 25 | | 3 | 5 | | 4 | 103 | | 5 | 18 | | 6 | 38 | | 7 | 26 | | 8 | 24 | | 9 | 26 | | 10 | 18 | | 11 | 41 | | 12 | 50 | | 13 | 9 | | 14 | 30 | | 15 | 8 | | 16 | 15 | | 17 | 3 | | 18 | 18 | | 19 | 58 | | 20 | 12 | | 21 | 18 | | 22 | 13 | | 23 | 33 | | 24 | 20 | | 25 | 19 | | 26 | 28 | | 27 | 17 | | 28 | 10 | | 29 | 40 | | 30 | 19 | | 31 | 15 | | 32 | 19 | | 33 | 41 | | 34 | 6 | | 35 | 18 | | 36 | 57 | | 37 | 9 | | 38 | 43 | | 39 | 24 | | 40 | 26 | | 41 | 17 | | 42 | 14 | | 43 | 40 |
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| 91.04% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 74 | | matches | | 0 | "been smoothed" | | 1 | "were clipped" | | 2 | "been lost" |
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| 96.64% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 129 | | matches | | 0 | "was reciting" | | 1 | "was realising" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 8 | | semicolonCount | 0 | | flaggedSentences | 7 | | totalSentences | 103 | | ratio | 0.068 | | matches | | 0 | "The girl he remembered – bright, sharp, all angles and nervous energy – had been smoothed, softened, sculpted into something…" | | 1 | "The severe black suit, the precise cut of her hair, the expensive weight of the silver bracelet circling her wrist – it all spoke of a life meticulously constructed, a far cry from the impulsive student who’d haunted his bar a decade ago." | | 2 | "A flicker of something – irritation, perhaps?" | | 3 | "– crossed her face, gone so quickly he almost missed it." | | 4 | "“Someone had to be, around you.” Her voice held a hint of something he couldn't quite decipher – resentment?" | | 5 | "His father, a man he hadn't spoken to in years, a man he’d long considered a distant ghost - suddenly caught in the crosshairs of Aurora’s…" | | 6 | "He saw it then - the chasm that had opened between them, widening with each passing year." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 739 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 26 | | adverbRatio | 0.035182679296346414 | | lyAdverbCount | 13 | | lyAdverbRatio | 0.017591339648173207 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 103 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 103 | | mean | 11.09 | | std | 7.55 | | cv | 0.681 | | sampleLengths | | 0 | 3 | | 1 | 26 | | 2 | 7 | | 3 | 27 | | 4 | 6 | | 5 | 13 | | 6 | 12 | | 7 | 5 | | 8 | 22 | | 9 | 13 | | 10 | 4 | | 11 | 20 | | 12 | 1 | | 13 | 43 | | 14 | 11 | | 15 | 7 | | 16 | 16 | | 17 | 22 | | 18 | 21 | | 19 | 5 | | 20 | 4 | | 21 | 20 | | 22 | 7 | | 23 | 11 | | 24 | 8 | | 25 | 10 | | 26 | 8 | | 27 | 11 | | 28 | 30 | | 29 | 2 | | 30 | 33 | | 31 | 15 | | 32 | 9 | | 33 | 12 | | 34 | 11 | | 35 | 7 | | 36 | 8 | | 37 | 8 | | 38 | 7 | | 39 | 3 | | 40 | 18 | | 41 | 3 | | 42 | 12 | | 43 | 26 | | 44 | 7 | | 45 | 10 | | 46 | 3 | | 47 | 9 | | 48 | 18 | | 49 | 6 |
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| 74.11% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 7 | | diversityRatio | 0.4854368932038835 | | totalSentences | 103 | | uniqueOpeners | 50 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 69 | | matches | (empty) | | ratio | 0 | |
| 22.90% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 34 | | totalSentences | 69 | | matches | | 0 | "He knew who was reciting" | | 1 | "He swirled his drink, the" | | 2 | "She ordered a dry martini," | | 3 | "She took a measured sip" | | 4 | "He raised an eyebrow." | | 5 | "He chuckled, a dry, rasping" | | 6 | "She gestured vaguely at the" | | 7 | "His gaze lingered on her" | | 8 | "She didn't elaborate" | | 9 | "He did know." | | 10 | "He’d chosen a different direction" | | 11 | "Her gaze sharpened." | | 12 | "She laughed, a short, dismissive" | | 13 | "He regretted the words instantly" | | 14 | "Her voice held a hint" | | 15 | "He ignored it." | | 16 | "It wasn't his place to" | | 17 | "She set her martini glass" | | 18 | "It hit him like a" | | 19 | "He narrowed his eyes, a" |
| | ratio | 0.493 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 66 | | totalSentences | 69 | | matches | | 0 | "The words hung in the" | | 1 | "Silas didn't look up, didn't" | | 2 | "He knew who was reciting" | | 3 | "The newcomer finally met his" | | 4 | "A ghost of a smile," | | 5 | "He swirled his drink, the" | | 6 | "A practiced pose, hiding the" | | 7 | "The girl he remembered –" | | 8 | "The severe black suit, the" | | 9 | "She ordered a dry martini," | | 10 | "Silas grunted, accepting the change" | | 11 | "She took a measured sip" | | 12 | "He raised an eyebrow." | | 13 | "A flicker of something –" | | 14 | "He chuckled, a dry, rasping" | | 15 | "Aurora said, her voice carefully" | | 16 | "She gestured vaguely at the" | | 17 | "His gaze lingered on her" | | 18 | "She didn't elaborate" | | 19 | "The silence that stretched between" |
| | ratio | 0.957 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 69 | | matches | (empty) | | ratio | 0 | |
| 87.91% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 26 | | technicalSentenceCount | 2 | | matches | | 0 | "The severe black suit, the precise cut of her hair, the expensive weight of the silver bracelet circling her wrist – it all spoke of a life meticulously constru…" | | 1 | "It was the look of someone who’d traded their soul for power." |
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| 50.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 20 | | uselessAdditionCount | 3 | | matches | | 0 | "Aurora said, her voice carefully neutral" | | 1 | "She met, her blue eyes glacial" | | 2 | "She stopped, her eyes widening as she took in Aurora's presence" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 6 | | fancyCount | 2 | | fancyTags | | 0 | "She ordered (order)" | | 1 | "He chuckled (chuckle)" |
| | dialogueSentences | 50 | | tagDensity | 0.12 | | leniency | 0.24 | | rawRatio | 0.333 | | effectiveRatio | 0.08 | |