| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 23 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 62 | | tagDensity | 0.371 | | leniency | 0.742 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 90.88% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1644 | | totalAiIsmAdverbs | 3 | | 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) | |
| 78.71% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1644 | | totalAiIsms | 7 | | found | | | highlights | | 0 | "intensity" | | 1 | "stomach" | | 2 | "familiar" | | 3 | "silence" | | 4 | "footsteps" | | 5 | "pulse" |
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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 | 142 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 2 | | narrationSentences | 142 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 178 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 53 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1636 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 27 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 46 | | wordCount | 1108 | | uniqueNames | 17 | | maxNameDensity | 0.99 | | worstName | "Rory" | | maxWindowNameDensity | 2 | | worstWindowName | "Rory" | | discoveredNames | | Eva | 5 | | Ptolemy | 4 | | Edinburgh | 1 | | Brick | 2 | | Lane | 2 | | Moreau | 1 | | Mayfair | 1 | | Lucien | 8 | | Oxford | 1 | | Rory | 11 | | Silas | 1 | | Evan | 2 | | Welsh | 1 | | Spitalfields | 1 | | Fae | 1 | | Camden | 1 | | Like | 3 |
| | persons | | 0 | "Eva" | | 1 | "Ptolemy" | | 2 | "Moreau" | | 3 | "Lucien" | | 4 | "Rory" | | 5 | "Silas" | | 6 | "Evan" |
| | places | | 0 | "Edinburgh" | | 1 | "Brick" | | 2 | "Lane" | | 3 | "Mayfair" | | 4 | "Oxford" | | 5 | "Camden" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 72 | | 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 | 1636 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 2 | | totalSentences | 178 | | matches | | 0 | "recognise that silhouette" | | 1 | "do that a" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 81 | | mean | 20.2 | | std | 17.57 | | cv | 0.87 | | sampleLengths | | 0 | 69 | | 1 | 37 | | 2 | 7 | | 3 | 2 | | 4 | 65 | | 5 | 12 | | 6 | 32 | | 7 | 24 | | 8 | 10 | | 9 | 6 | | 10 | 12 | | 11 | 46 | | 12 | 12 | | 13 | 40 | | 14 | 7 | | 15 | 40 | | 16 | 13 | | 17 | 20 | | 18 | 4 | | 19 | 20 | | 20 | 5 | | 21 | 61 | | 22 | 7 | | 23 | 9 | | 24 | 14 | | 25 | 23 | | 26 | 5 | | 27 | 41 | | 28 | 4 | | 29 | 20 | | 30 | 4 | | 31 | 4 | | 32 | 1 | | 33 | 59 | | 34 | 11 | | 35 | 48 | | 36 | 19 | | 37 | 21 | | 38 | 15 | | 39 | 24 | | 40 | 30 | | 41 | 9 | | 42 | 16 | | 43 | 11 | | 44 | 8 | | 45 | 26 | | 46 | 34 | | 47 | 33 | | 48 | 7 | | 49 | 5 |
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| 97.85% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 142 | | matches | | 0 | "was undone" | | 1 | "was covered" | | 2 | "was covered" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 200 | | matches | | |
| 46.55% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 7 | | semicolonCount | 0 | | flaggedSentences | 6 | | totalSentences | 178 | | ratio | 0.034 | | matches | | 0 | "And she’d told herself it was for the best—that a half-demon fixer and a woman running from an abusive ex couldn’t mix without leaving scorch marks." | | 1 | "He looked different—thinner in the face, shadows under his good eye." | | 2 | "The top page was covered in cramped handwriting—translations of a medieval Welsh grimoire." | | 3 | "She looked down at his hand—the fine bones, the silver ring on his thumb, the faint calluses from fighting things that shouldn’t exist." | | 4 | "Rory laughed—a surprised, wet sound—and Lucien’s smile widened." | | 5 | "She turned and grabbed a spare blanket from the cupboard—frayed, floral, something Eva had thrifted in Camden." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1117 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 37 | | adverbRatio | 0.03312444046553268 | | lyAdverbCount | 7 | | lyAdverbRatio | 0.006266786034019696 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 178 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 178 | | mean | 9.19 | | std | 7.77 | | cv | 0.846 | | sampleLengths | | 0 | 17 | | 1 | 17 | | 2 | 5 | | 3 | 17 | | 4 | 13 | | 5 | 10 | | 6 | 15 | | 7 | 2 | | 8 | 4 | | 9 | 6 | | 10 | 7 | | 11 | 2 | | 12 | 7 | | 13 | 24 | | 14 | 4 | | 15 | 2 | | 16 | 2 | | 17 | 26 | | 18 | 12 | | 19 | 5 | | 20 | 3 | | 21 | 7 | | 22 | 17 | | 23 | 11 | | 24 | 13 | | 25 | 4 | | 26 | 6 | | 27 | 6 | | 28 | 6 | | 29 | 6 | | 30 | 3 | | 31 | 11 | | 32 | 13 | | 33 | 13 | | 34 | 2 | | 35 | 4 | | 36 | 12 | | 37 | 4 | | 38 | 13 | | 39 | 7 | | 40 | 16 | | 41 | 7 | | 42 | 5 | | 43 | 14 | | 44 | 15 | | 45 | 5 | | 46 | 1 | | 47 | 10 | | 48 | 3 | | 49 | 8 |
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| 41.01% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 16 | | diversityRatio | 0.2640449438202247 | | totalSentences | 178 | | uniqueOpeners | 47 | |
| 60.61% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 110 | | matches | | 0 | "Then the second." | | 1 | "Then he stepped over the" |
| | ratio | 0.018 | |
| 38.18% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 50 | | totalSentences | 110 | | matches | | 0 | "She’d put them there herself" | | 1 | "She crossed the creaking floorboards" | | 2 | "She hadn’t seen him in" | | 3 | "He’d let her go." | | 4 | "She pulled the first bolt." | | 5 | "She opened the door a" | | 6 | "His voice was low, a" | | 7 | "She didn’t smile" | | 8 | "She let the word sit" | | 9 | "His jaw tightened." | | 10 | "He looked different—thinner in the" | | 11 | "His suit was charcoal, immaculate" | | 12 | "She unchained the door and" | | 13 | "He didn’t move right away." | | 14 | "He stood there, cane planted," | | 15 | "He set the cane against" | | 16 | "He took off his jacket," | | 17 | "She’d seen him do that" | | 18 | "It felt like trespass." | | 19 | "She hadn’t had a working" |
| | ratio | 0.455 | |
| 37.27% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 93 | | totalSentences | 110 | | matches | | 0 | "The knock came at half" | | 1 | "Rory looked up from the" | | 2 | "The deadbolts were all thrown." | | 3 | "She’d put them there herself" | | 4 | "She crossed the creaking floorboards" | | 5 | "The fisheye lens distorted the" | | 6 | "Platinum hair slicked back." | | 7 | "The curve of an ivory" | | 8 | "Rory’s hand froze on the" | | 9 | "She hadn’t seen him in" | | 10 | "He’d let her go." | | 11 | "She pulled the first bolt." | | 12 | "The third slid with a" | | 13 | "She opened the door a" | | 14 | "His voice was low, a" | | 15 | "The way it always sounded" | | 16 | "She didn’t smile" | | 17 | "She let the word sit" | | 18 | "His jaw tightened." | | 19 | "He looked different—thinner in the" |
| | ratio | 0.845 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 110 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 45 | | technicalSentenceCount | 1 | | matches | | 0 | "She looked down at his hand—the fine bones, the silver ring on his thumb, the faint calluses from fighting things that shouldn’t exist." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 23 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 15 | | fancyCount | 2 | | fancyTags | | 0 | "Lucien continued (continue)" | | 1 | "she whispered (whisper)" |
| | dialogueSentences | 62 | | tagDensity | 0.242 | | leniency | 0.484 | | rawRatio | 0.133 | | effectiveRatio | 0.065 | |