| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 11 | | adverbTagCount | 1 | | adverbTags | | 0 | "He swallowed thickly [thickly]" |
| | dialogueSentences | 43 | | tagDensity | 0.256 | | leniency | 0.512 | | rawRatio | 0.091 | | effectiveRatio | 0.047 | |
| 96.10% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1283 | | 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) | |
| 49.34% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1283 | | totalAiIsms | 13 | | found | | | highlights | | 0 | "porcelain" | | 1 | "silence" | | 2 | "stomach" | | 3 | "weight" | | 4 | "unspoken" | | 5 | "eyebrow" | | 6 | "pang" | | 7 | "sense of" | | 8 | "glistening" | | 9 | "lurched" | | 10 | "thundered" |
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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 | 2 | | narrationSentences | 102 | | matches | | 0 | "y in love" | | 1 | "d with longing" |
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| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 102 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 134 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 37 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1279 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 7 | | unquotedAttributions | 0 | | matches | (empty) | |
| 33.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 38 | | wordCount | 814 | | uniqueNames | 6 | | maxNameDensity | 2.21 | | worstName | "Rory" | | maxWindowNameDensity | 4 | | worstWindowName | "Rory" | | discoveredNames | | Lucien | 15 | | Abruptly | 1 | | Rory | 18 | | Jesus | 1 | | Christ | 2 | | Butcher | 1 |
| | persons | | 0 | "Lucien" | | 1 | "Rory" | | 2 | "Jesus" | | 3 | "Christ" |
| | places | (empty) | | globalScore | 0.394 | | windowScore | 0.333 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 66 | | glossingSentenceCount | 1 | | matches | | 0 | "ave him, she'd apparently been conducting gho" |
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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 | 1279 | | matches | (empty) | |
| 92.04% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 3 | | totalSentences | 134 | | matches | | 0 | "Hated that she" | | 1 | "Hated that he relive that day" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 57 | | mean | 22.44 | | std | 14.59 | | cv | 0.65 | | sampleLengths | | 0 | 22 | | 1 | 38 | | 2 | 15 | | 3 | 24 | | 4 | 8 | | 5 | 51 | | 6 | 16 | | 7 | 6 | | 8 | 27 | | 9 | 36 | | 10 | 22 | | 11 | 21 | | 12 | 22 | | 13 | 13 | | 14 | 27 | | 15 | 23 | | 16 | 16 | | 17 | 9 | | 18 | 3 | | 19 | 16 | | 20 | 40 | | 21 | 36 | | 22 | 26 | | 23 | 23 | | 24 | 1 | | 25 | 24 | | 26 | 9 | | 27 | 19 | | 28 | 52 | | 29 | 4 | | 30 | 5 | | 31 | 17 | | 32 | 10 | | 33 | 51 | | 34 | 19 | | 35 | 24 | | 36 | 71 | | 37 | 11 | | 38 | 33 | | 39 | 32 | | 40 | 5 | | 41 | 31 | | 42 | 19 | | 43 | 61 | | 44 | 11 | | 45 | 21 | | 46 | 15 | | 47 | 12 | | 48 | 23 | | 49 | 32 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 102 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 163 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 2 | | semicolonCount | 0 | | flaggedSentences | 2 | | totalSentences | 134 | | ratio | 0.015 | | matches | | 0 | "Seeing her again, this woman who had eclipsed him so thoroughly—he'd wanted that, hadn't he?" | | 1 | "He'd give anything to carve out a different path, to tell Rory he'd been a coward, that he hadn't meant a word—no, that he'd meant every word, but out of fear." |
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| 89.44% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 557 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 29 | | adverbRatio | 0.05206463195691203 | | lyAdverbCount | 6 | | lyAdverbRatio | 0.010771992818671455 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 134 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 134 | | mean | 9.54 | | std | 6.82 | | cv | 0.714 | | sampleLengths | | 0 | 10 | | 1 | 12 | | 2 | 8 | | 3 | 14 | | 4 | 8 | | 5 | 7 | | 6 | 1 | | 7 | 10 | | 8 | 5 | | 9 | 5 | | 10 | 7 | | 11 | 12 | | 12 | 8 | | 13 | 14 | | 14 | 37 | | 15 | 4 | | 16 | 8 | | 17 | 4 | | 18 | 6 | | 19 | 10 | | 20 | 11 | | 21 | 6 | | 22 | 21 | | 23 | 15 | | 24 | 12 | | 25 | 10 | | 26 | 12 | | 27 | 9 | | 28 | 10 | | 29 | 5 | | 30 | 7 | | 31 | 8 | | 32 | 5 | | 33 | 5 | | 34 | 6 | | 35 | 16 | | 36 | 23 | | 37 | 10 | | 38 | 6 | | 39 | 9 | | 40 | 3 | | 41 | 16 | | 42 | 12 | | 43 | 5 | | 44 | 17 | | 45 | 6 | | 46 | 6 | | 47 | 21 | | 48 | 9 | | 49 | 4 |
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| 65.67% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 7 | | diversityRatio | 0.4253731343283582 | | totalSentences | 134 | | uniqueOpeners | 57 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 96 | | matches | | 0 | "Then, inexplicably, her gaze dropped" | | 1 | "Abruptly, he felt ill." | | 2 | "Barely registered when she started" |
| | ratio | 0.031 | |
| 78.33% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 34 | | totalSentences | 96 | | matches | | 0 | "His mind conjured a thousand" | | 1 | "Her hair a disheveled mess," | | 2 | "She squinted into the dim" | | 3 | "He should have been used" | | 4 | "he said, gesturing to the" | | 5 | "Her face flamed crimson." | | 6 | "She hastily stepped back, dragging" | | 7 | "She gasped, book and manila" | | 8 | "He leaned in close, inhaling" | | 9 | "She clutched the folder protectively." | | 10 | "He offered her a wry" | | 11 | "His eyes widened." | | 12 | "He ought to be bloody" | | 13 | "She gave him a hard" | | 14 | "He felt the weight of" | | 15 | "He straightened his tie, swallowing" | | 16 | "Her shoulders slumped." | | 17 | "She raised an eyebrow." | | 18 | "He winced at the condescension," | | 19 | "Her chin wobbled once, before" |
| | ratio | 0.354 | |
| 69.38% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 75 | | totalSentences | 96 | | matches | | 0 | "Lucien froze at the sound" | | 1 | "His mind conjured a thousand" | | 2 | "The door creaked inward, and" | | 3 | "Her hair a disheveled mess," | | 4 | "Porcelain skin drawn in alarm" | | 5 | "Eyes a crackle of ginger" | | 6 | "She squinted into the dim" | | 7 | "He should have been used" | | 8 | "he said, gesturing to the" | | 9 | "Lucien straightened, pinning her with" | | 10 | "Rory gaped, blinking rapidly." | | 11 | "Her face flamed crimson." | | 12 | "She hastily stepped back, dragging" | | 13 | "The gesture knocked the book" | | 14 | "Lucien noted the telltale tremble" | | 15 | "The barest hint of lavender" | | 16 | "Rory muttered, locking the deadbolts" | | 17 | "Lucien whirled, catching her by" | | 18 | "She gasped, book and manila" | | 19 | "He leaned in close, inhaling" |
| | ratio | 0.781 | |
| 52.08% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 96 | | matches | | 0 | "Because we are. Look, whatever" |
| | ratio | 0.01 | |
| 75.89% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 32 | | technicalSentenceCount | 3 | | matches | | 0 | "Lucien straightened, pinning her with a stare that had men twice her size quailing." | | 1 | "Lucien noted the telltale tremble of anger in her shoulders, but he strode past her as if she hadn't a care." | | 2 | "Lucien heaved a put-upon sigh that emerged as more of a grunt." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 11 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 3 | | fancyCount | 2 | | fancyTags | | 0 | "Rory muttered (mutter)" | | 1 | "he murmured (murmur)" |
| | dialogueSentences | 43 | | tagDensity | 0.07 | | leniency | 0.14 | | rawRatio | 0.667 | | effectiveRatio | 0.093 | |