| 76.92% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 29 | | adverbTagCount | 4 | | adverbTags | | 0 | "he said finally [finally]" | | 1 | "she offered instead [instead]" | | 2 | "green she had once [once]" | | 3 | "she said slowly [slowly]" |
| | dialogueSentences | 65 | | tagDensity | 0.446 | | leniency | 0.892 | | rawRatio | 0.138 | | effectiveRatio | 0.123 | |
| 90.08% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 2520 | | totalAiIsmAdverbs | 5 | | found | | | highlights | | 0 | "really" | | 1 | "softly" | | 2 | "slowly" |
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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) | |
| 58.33% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 2520 | | totalAiIsms | 21 | | found | | | highlights | | 0 | "scanned" | | 1 | "familiar" | | 2 | "stomach" | | 3 | "flicked" | | 4 | "measured" | | 5 | "pulse" | | 6 | "silence" | | 7 | "tension" | | 8 | "weight" | | 9 | "reminder" | | 10 | "traced" | | 11 | "echoed" | | 12 | "shattered" | | 13 | "silk" |
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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 | 1 | | narrationSentences | 172 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 172 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 208 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 42 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 2520 | | ratio | 0 | | matches | (empty) | |
| 97.22% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 18 | | unquotedAttributions | 2 | | matches | | 0 | "The Spymaster, they called him in certain circles." | | 1 | "Behind her, Evan called her name once." |
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| 83.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 63 | | wordCount | 1860 | | uniqueNames | 17 | | maxNameDensity | 0.91 | | worstName | "Evan" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Evan" | | discoveredNames | | Raven | 1 | | Nest | 1 | | Silas | 11 | | Golden | 1 | | Empress | 1 | | Yu-Fei | 3 | | Cheung | 3 | | London | 3 | | Cardiff | 3 | | Evan | 17 | | Eva | 2 | | Rory | 11 | | Neutral | 1 | | Welsh | 1 | | Spymaster | 1 | | Malphora | 1 | | Soho | 2 |
| | persons | | 0 | "Raven" | | 1 | "Silas" | | 2 | "Empress" | | 3 | "Yu-Fei" | | 4 | "Cheung" | | 5 | "Evan" | | 6 | "Eva" | | 7 | "Rory" | | 8 | "Spymaster" |
| | places | | 0 | "Golden" | | 1 | "London" | | 2 | "Cardiff" | | 3 | "Welsh" | | 4 | "Soho" |
| | globalScore | 1 | | windowScore | 0.833 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 135 | | glossingSentenceCount | 1 | | matches | | |
| 80.95% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 3 | | per1kWords | 1.19 | | wordCount | 2520 | | matches | | 0 | "Not the sharp fear of old, but something heavier, like sediment stirred from the bottom of" | | 1 | "not in passion but in possession" | | 2 | "not in childhood as the story went, but in the bathroom of their old flat while Evan raged in the ne" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 208 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 67 | | mean | 37.61 | | std | 20.39 | | cv | 0.542 | | sampleLengths | | 0 | 85 | | 1 | 36 | | 2 | 76 | | 3 | 39 | | 4 | 77 | | 5 | 44 | | 6 | 30 | | 7 | 63 | | 8 | 11 | | 9 | 23 | | 10 | 48 | | 11 | 7 | | 12 | 31 | | 13 | 37 | | 14 | 41 | | 15 | 41 | | 16 | 82 | | 17 | 31 | | 18 | 32 | | 19 | 39 | | 20 | 66 | | 21 | 21 | | 22 | 33 | | 23 | 26 | | 24 | 39 | | 25 | 35 | | 26 | 38 | | 27 | 38 | | 28 | 18 | | 29 | 73 | | 30 | 33 | | 31 | 75 | | 32 | 66 | | 33 | 9 | | 34 | 48 | | 35 | 62 | | 36 | 34 | | 37 | 36 | | 38 | 71 | | 39 | 26 | | 40 | 49 | | 41 | 31 | | 42 | 78 | | 43 | 24 | | 44 | 38 | | 45 | 8 | | 46 | 26 | | 47 | 64 | | 48 | 11 | | 49 | 16 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 172 | | matches | | 0 | "being asked" | | 1 | "were struck" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 303 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 208 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1497 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 56 | | adverbRatio | 0.03740814963259853 | | lyAdverbCount | 9 | | lyAdverbRatio | 0.006012024048096192 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 208 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 208 | | mean | 12.12 | | std | 7.35 | | cv | 0.607 | | sampleLengths | | 0 | 30 | | 1 | 18 | | 2 | 21 | | 3 | 16 | | 4 | 15 | | 5 | 7 | | 6 | 13 | | 7 | 1 | | 8 | 3 | | 9 | 19 | | 10 | 21 | | 11 | 22 | | 12 | 11 | | 13 | 24 | | 14 | 6 | | 15 | 9 | | 16 | 16 | | 17 | 21 | | 18 | 11 | | 19 | 16 | | 20 | 13 | | 21 | 24 | | 22 | 7 | | 23 | 5 | | 24 | 8 | | 25 | 7 | | 26 | 11 | | 27 | 12 | | 28 | 11 | | 29 | 10 | | 30 | 11 | | 31 | 17 | | 32 | 7 | | 33 | 7 | | 34 | 7 | | 35 | 4 | | 36 | 13 | | 37 | 10 | | 38 | 9 | | 39 | 13 | | 40 | 26 | | 41 | 4 | | 42 | 3 | | 43 | 13 | | 44 | 8 | | 45 | 10 | | 46 | 5 | | 47 | 32 | | 48 | 8 | | 49 | 5 |
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| 54.65% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 13 | | diversityRatio | 0.36538461538461536 | | totalSentences | 208 | | uniqueOpeners | 76 | |
| 40.16% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 166 | | matches | | 0 | "Instead, her gaze snagged on" | | 1 | "Instead she studied him, really" |
| | ratio | 0.012 | |
| 75.42% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 60 | | totalSentences | 166 | | matches | | 0 | "Her shift at Golden Empress" | | 1 | "She needed a quiet corner," | | 2 | "Her stomach twisted." | | 3 | "He had let his hair" | | 4 | "His voice carried across the" | | 5 | "He straightened but did not" | | 6 | "She crossed to him anyway," | | 7 | "His hazel eyes flicked toward" | | 8 | "She slid onto the stool" | | 9 | "She signalled Silas with a" | | 10 | "She wrapped her fingers around" | | 11 | "She kept her tone light," | | 12 | "His silver signet ring glinted" | | 13 | "He moved away with that" | | 14 | "She took a long pull" | | 15 | "She set her glass down" | | 16 | "His fingers tightened around his" | | 17 | "She wondered if he saw" | | 18 | "he said finally" | | 19 | "His gaze dropped to her" |
| | ratio | 0.361 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 153 | | totalSentences | 166 | | matches | | 0 | "Rory pushed through the heavy" | | 1 | "Rainwater dripped from her delivery" | | 2 | "Her shift at Golden Empress" | | 3 | "She needed a quiet corner," | | 4 | "The man lifted his head," | | 5 | "Her stomach twisted." | | 6 | "He had let his hair" | | 7 | "The boyish grin she once" | | 8 | "A small scar she did" | | 9 | "His voice carried across the" | | 10 | "He straightened but did not" | | 11 | "She crossed to him anyway," | | 12 | "The bar's walls pressed in" | | 13 | "Silas stood at the other" | | 14 | "His hazel eyes flicked toward" | | 15 | "The slight limp in his" | | 16 | "She slid onto the stool" | | 17 | "The same brand he had" | | 18 | "Some things refused to change." | | 19 | "Evan rotated his glass between" |
| | ratio | 0.922 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 166 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 69 | | technicalSentenceCount | 4 | | matches | | 0 | "He had let his hair grow longer, now streaked with premature silver that caught the green neon from the sign outside." | | 1 | "People who had not traded their past for anonymity above a Soho bar." | | 2 | "The weight of Yu-Fei Cheung's packet shifted inside, a reminder of choices that had nothing to do with law or love or the boy from Cardiff who used to write her…" | | 3 | "He signalled for another, movements sharp with the kind of decision that changes everything or nothing at all." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 29 | | uselessAdditionCount | 1 | | matches | | 0 | "She kept, though her pulse hammered against her throat" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 3 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 65 | | tagDensity | 0.046 | | leniency | 0.092 | | rawRatio | 0.333 | | effectiveRatio | 0.031 | |