| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 23 | | adverbTagCount | 2 | | adverbTags | | 0 | "He stepped back [back]" | | 1 | "He moved then [then]" |
| | dialogueSentences | 57 | | tagDensity | 0.404 | | leniency | 0.807 | | rawRatio | 0.087 | | effectiveRatio | 0.07 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 910 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 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) | |
| 72.53% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 910 | | totalAiIsms | 5 | | found | | | highlights | | 0 | "stomach" | | 1 | "traced" | | 2 | "flickered" | | 3 | "ensure" | | 4 | "wavered" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "stomach dropped/sank" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 58 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 58 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 91 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 28 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 1 | | markdownWords | 4 | | totalWords | 903 | | ratio | 0.004 | | matches | | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 8 | | unquotedAttributions | 0 | | matches | (empty) | |
| 73.95% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 23 | | wordCount | 526 | | uniqueNames | 10 | | maxNameDensity | 1.52 | | worstName | "Aurora" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Aurora" | | discoveredNames | | Aurora | 8 | | Cardiff | 1 | | University | 1 | | Eva | 2 | | Ptolemy | 3 | | Business | 1 | | Kensington | 1 | | Lucien | 4 | | Heat | 1 | | Close | 1 |
| | persons | | 0 | "Aurora" | | 1 | "Eva" | | 2 | "Ptolemy" | | 3 | "Business" | | 4 | "Lucien" | | 5 | "Heat" |
| | places | | | globalScore | 0.74 | | windowScore | 0.833 | |
| 84.21% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 38 | | glossingSentenceCount | 1 | | matches | | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 903 | | matches | (empty) | |
| 93.41% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 2 | | totalSentences | 91 | | matches | | 0 | "had that effect" | | 1 | "chose that moment" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 46 | | mean | 19.63 | | std | 14.53 | | cv | 0.74 | | sampleLengths | | 0 | 8 | | 1 | 43 | | 2 | 22 | | 3 | 36 | | 4 | 7 | | 5 | 4 | | 6 | 34 | | 7 | 62 | | 8 | 21 | | 9 | 15 | | 10 | 4 | | 11 | 8 | | 12 | 22 | | 13 | 24 | | 14 | 5 | | 15 | 21 | | 16 | 9 | | 17 | 41 | | 18 | 18 | | 19 | 14 | | 20 | 2 | | 21 | 23 | | 22 | 6 | | 23 | 19 | | 24 | 10 | | 25 | 3 | | 26 | 42 | | 27 | 27 | | 28 | 11 | | 29 | 4 | | 30 | 23 | | 31 | 38 | | 32 | 6 | | 33 | 30 | | 34 | 16 | | 35 | 6 | | 36 | 37 | | 37 | 23 | | 38 | 8 | | 39 | 31 | | 40 | 10 | | 41 | 53 | | 42 | 12 | | 43 | 6 | | 44 | 4 | | 45 | 35 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 58 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 101 | | matches | (empty) | |
| 48.67% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 4 | | semicolonCount | 0 | | flaggedSentences | 3 | | totalSentences | 91 | | ratio | 0.033 | | matches | | 0 | "\"Bonsoir, chérie.\" His mismatched eyes—amber and black—swept over her ratty Cardiff University jumper and bare feet." | | 1 | "Something flickered across his expression—too quick to name." | | 2 | "He'd always had that effect—filling rooms, demanding attention without saying a word." |
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| 84.51% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 531 | | adjectiveStacks | 1 | | stackExamples | | 0 | "damned ivory-handled cane." |
| | adverbCount | 27 | | adverbRatio | 0.05084745762711865 | | lyAdverbCount | 4 | | lyAdverbRatio | 0.007532956685499058 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 91 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 91 | | mean | 9.92 | | std | 6.46 | | cv | 0.651 | | sampleLengths | | 0 | 8 | | 1 | 21 | | 2 | 9 | | 3 | 13 | | 4 | 16 | | 5 | 6 | | 6 | 15 | | 7 | 13 | | 8 | 8 | | 9 | 7 | | 10 | 4 | | 11 | 18 | | 12 | 16 | | 13 | 1 | | 14 | 1 | | 15 | 6 | | 16 | 7 | | 17 | 19 | | 18 | 28 | | 19 | 21 | | 20 | 11 | | 21 | 4 | | 22 | 4 | | 23 | 8 | | 24 | 8 | | 25 | 11 | | 26 | 3 | | 27 | 5 | | 28 | 13 | | 29 | 6 | | 30 | 5 | | 31 | 17 | | 32 | 4 | | 33 | 7 | | 34 | 2 | | 35 | 3 | | 36 | 12 | | 37 | 12 | | 38 | 10 | | 39 | 2 | | 40 | 2 | | 41 | 18 | | 42 | 9 | | 43 | 5 | | 44 | 2 | | 45 | 6 | | 46 | 17 | | 47 | 6 | | 48 | 5 | | 49 | 13 |
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| 86.45% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 8 | | diversityRatio | 0.5714285714285714 | | totalSentences | 91 | | uniqueOpeners | 52 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 52 | | matches | | 0 | "Instead she heard herself say," | | 1 | "Always kept it close." |
| | ratio | 0.038 | |
| 66.15% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 20 | | totalSentences | 52 | | matches | | 0 | "His mismatched eyes—amber and black—swept" | | 1 | "He tilted his head, rainwater" | | 2 | "He stepped back, rain immediately" | | 3 | "She should have said yes." | | 4 | "He paused on the threshold." | | 5 | "She moved aside." | | 6 | "He crossed into Eva's cramped" | | 7 | "He'd always had that effect—filling" | | 8 | "He glanced at the towers" | | 9 | "She barked a laugh" | | 10 | "She moved into the kitchenette," | | 11 | "She stopped, biting down on" | | 12 | "He set the cane against" | | 13 | "She grabbed two mugs from" | | 14 | "She turned, meeting his eyes" | | 15 | "His voice dropped, rougher than" | | 16 | "Her voice came out smaller" | | 17 | "He moved then, crossing the" | | 18 | "She held her ground" | | 19 | "He reached out, stopped just" |
| | ratio | 0.385 | |
| 56.15% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 42 | | totalSentences | 52 | | matches | | 0 | "The door swung open and" | | 1 | "Lucien stood in the threshold," | | 2 | "Rain had darkened the shoulders" | | 3 | "Water dripped from the platinum" | | 4 | "His mismatched eyes—amber and black—swept" | | 5 | "Aurora planted herself in the" | | 6 | "He tilted his head, rainwater" | | 7 | "A fixer and his temporarily" | | 8 | "Aurora kept her voice level" | | 9 | "Something flickered across his expression—too" | | 10 | "He stepped back, rain immediately" | | 11 | "She should have said yes." | | 12 | "He paused on the threshold." | | 13 | "The excuse sounded weak even" | | 14 | "Lucien's mouth curved, not quite" | | 15 | "She moved aside." | | 16 | "He crossed into Eva's cramped" | | 17 | "He'd always had that effect—filling" | | 18 | "Aurora engaged two of the" | | 19 | "He glanced at the towers" |
| | ratio | 0.808 | |
| 96.15% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 52 | | matches | | 0 | "Because that's all they'd ever" |
| | ratio | 0.019 | |
| 87.91% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 13 | | technicalSentenceCount | 1 | | matches | | 0 | "Lucien stood in the threshold, one hand still raised as if to knock again, the other gripping that damned ivory-handled cane." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 23 | | uselessAdditionCount | 1 | | matches | | 0 | "He tilted, rainwater sliding down his sharp cheekbone" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 2 | | fancyCount | 2 | | fancyTags | | 0 | "she heard (hear)" | | 1 | "She barked (bark)" |
| | dialogueSentences | 57 | | tagDensity | 0.035 | | leniency | 0.07 | | rawRatio | 1 | | effectiveRatio | 0.07 | |