| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 11 | | adverbTagCount | 2 | | adverbTags | | 0 | "she said quietly [quietly]" | | 1 | "His thumb moved just [just]" |
| | dialogueSentences | 44 | | tagDensity | 0.25 | | leniency | 0.5 | | rawRatio | 0.182 | | effectiveRatio | 0.091 | |
| 86.76% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1511 | | totalAiIsmAdverbs | 4 | | found | | | highlights | | 0 | "slowly" | | 1 | "perfectly" | | 2 | "slightly" |
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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) | |
| 63.60% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1511 | | totalAiIsms | 11 | | found | | | highlights | | 0 | "could feel" | | 1 | "intensity" | | 2 | "stomach" | | 3 | "unsettled" | | 4 | "flicker" | | 5 | "pulse" | | 6 | "warmth" | | 7 | "traced" |
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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 | 82 | | matches | (empty) | |
| 73.17% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 3 | | narrationSentences | 82 | | filterMatches | | | hedgeMatches | | 0 | "managed to" | | 1 | "tend to" | | 2 | "started to" |
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| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 114 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 72 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1511 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 17 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 42 | | wordCount | 1012 | | uniqueNames | 15 | | maxNameDensity | 0.89 | | worstName | "Rory" | | maxWindowNameDensity | 2 | | worstWindowName | "Eva" | | discoveredNames | | Rory | 9 | | Cardiff | 1 | | Bay | 1 | | Moreau | 2 | | Eva | 6 | | Tuesday | 1 | | November | 1 | | London | 1 | | Ptolemy | 3 | | Lucien | 8 | | Silas | 1 | | French | 1 | | Evan | 3 | | Golden | 2 | | Empress | 2 |
| | persons | | 0 | "Rory" | | 1 | "Moreau" | | 2 | "Eva" | | 3 | "Ptolemy" | | 4 | "Lucien" | | 5 | "Silas" | | 6 | "Evan" |
| | places | | 0 | "Cardiff" | | 1 | "Bay" | | 2 | "London" | | 3 | "French" | | 4 | "Golden" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 53 | | glossingSentenceCount | 1 | | matches | | 0 | "as though cataloguing changes since his last visit" |
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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 | 1511 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 114 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 58 | | mean | 26.05 | | std | 22.94 | | cv | 0.88 | | sampleLengths | | 0 | 48 | | 1 | 20 | | 2 | 60 | | 3 | 1 | | 4 | 37 | | 5 | 3 | | 6 | 7 | | 7 | 43 | | 8 | 55 | | 9 | 8 | | 10 | 3 | | 11 | 3 | | 12 | 54 | | 13 | 22 | | 14 | 61 | | 15 | 5 | | 16 | 54 | | 17 | 48 | | 18 | 10 | | 19 | 46 | | 20 | 4 | | 21 | 2 | | 22 | 32 | | 23 | 15 | | 24 | 27 | | 25 | 19 | | 26 | 74 | | 27 | 17 | | 28 | 3 | | 29 | 39 | | 30 | 53 | | 31 | 16 | | 32 | 5 | | 33 | 52 | | 34 | 3 | | 35 | 4 | | 36 | 45 | | 37 | 33 | | 38 | 42 | | 39 | 10 | | 40 | 88 | | 41 | 3 | | 42 | 66 | | 43 | 4 | | 44 | 20 | | 45 | 18 | | 46 | 75 | | 47 | 14 | | 48 | 22 | | 49 | 4 |
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| 96.71% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 82 | | matches | | 0 | "get tangled" | | 1 | "was complicated" |
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| 41.27% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 4 | | totalVerbs | 168 | | matches | | 0 | "was standing" | | 1 | "was still running" | | 2 | "was stacking" | | 3 | "were just discussing" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 114 | | ratio | 0 | | matches | (empty) | |
| 95.31% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1014 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 46 | | adverbRatio | 0.045364891518737675 | | lyAdverbCount | 14 | | lyAdverbRatio | 0.013806706114398421 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 114 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 114 | | mean | 13.25 | | std | 11.99 | | cv | 0.905 | | sampleLengths | | 0 | 9 | | 1 | 3 | | 2 | 15 | | 3 | 21 | | 4 | 20 | | 5 | 16 | | 6 | 27 | | 7 | 3 | | 8 | 2 | | 9 | 12 | | 10 | 1 | | 11 | 3 | | 12 | 2 | | 13 | 18 | | 14 | 14 | | 15 | 3 | | 16 | 7 | | 17 | 28 | | 18 | 15 | | 19 | 23 | | 20 | 6 | | 21 | 26 | | 22 | 8 | | 23 | 3 | | 24 | 3 | | 25 | 12 | | 26 | 34 | | 27 | 6 | | 28 | 2 | | 29 | 22 | | 30 | 8 | | 31 | 2 | | 32 | 7 | | 33 | 44 | | 34 | 3 | | 35 | 2 | | 36 | 4 | | 37 | 1 | | 38 | 32 | | 39 | 17 | | 40 | 25 | | 41 | 23 | | 42 | 4 | | 43 | 6 | | 44 | 17 | | 45 | 9 | | 46 | 6 | | 47 | 14 | | 48 | 4 | | 49 | 2 |
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| 41.52% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 21 | | diversityRatio | 0.35964912280701755 | | totalSentences | 114 | | uniqueOpeners | 41 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 4 | | totalSentences | 70 | | matches | | 0 | "Then the second." | | 1 | "Just her name." | | 2 | "Somewhere behind her, Ptolemy meowed" | | 3 | "Instead she leaned forward, just" |
| | ratio | 0.057 | |
| 48.57% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 30 | | totalSentences | 70 | | matches | | 0 | "She could feel it the" | | 1 | "She pulled open the door" | | 2 | "He smiled, just barely, a" | | 3 | "He'd done that the first" | | 4 | "She should have walked away" | | 5 | "Her own jacket thrown over" | | 6 | "She stepped back." | | 7 | "He'd been here before." | | 8 | "She crossed her arms." | | 9 | "It wasn't a question" | | 10 | "His jaw tightened, a flicker" | | 11 | "He set the cane against" | | 12 | "He took a step closer" | | 13 | "She could smell him now," | | 14 | "She could feel the small" | | 15 | "she said quietly" | | 16 | "She looked at him." | | 17 | "His thumb moved, just slightly," | | 18 | "Her throat closed." | | 19 | "She could feel the warmth" |
| | ratio | 0.429 | |
| 52.86% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 57 | | totalSentences | 70 | | matches | | 0 | "The first deadbolt slid back" | | 1 | "She could feel it the" | | 2 | "She pulled open the door" | | 3 | "Lucien Moreau leaned against the" | | 4 | "The charcoal suit was immaculate," | | 5 | "Both fixed on her with" | | 6 | "The audacity of him made" | | 7 | "The curry house downstairs was" | | 8 | "Rory stared at Lucien's left" | | 9 | "He smiled, just barely, a" | | 10 | "He'd done that the first" | | 11 | "She should have walked away" | | 12 | "Rory glanced over her shoulder" | | 13 | "Scrolls spread across Eva's tiny" | | 14 | "Her own jacket thrown over" | | 15 | "She stepped back." | | 16 | "He'd been here before." | | 17 | "The first time Eva had" | | 18 | "The second time Eva had" | | 19 | "Ptolemy wound between Lucien's ankles," |
| | ratio | 0.814 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 70 | | matches | | 0 | "By the time the third" | | 1 | "Because of what that eye" |
| | ratio | 0.029 | |
| 86.47% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 38 | | technicalSentenceCount | 3 | | matches | | 0 | "The charcoal suit was immaculate, as always, the platinum hair slicked back from his face in that way that made his cheekbones look carved from something expens…" | | 1 | "Lucien straightened, his gaze moving slowly around the flat as though cataloguing changes since his last visit." | | 2 | "She could smell him now, sandalwood and something underneath it that was warmer, almost metallic, something that wasn't entirely human." |
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| 79.55% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 11 | | uselessAdditionCount | 1 | | matches | | 0 | "she said, but her voice had lost its edge" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 7 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 44 | | tagDensity | 0.159 | | leniency | 0.318 | | rawRatio | 0.143 | | effectiveRatio | 0.045 | |