| 97.44% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 10 | | adverbTagCount | 2 | | adverbTags | | 0 | "Silas turned away [away]" | | 1 | "Rory said quietly [quietly]" |
| | dialogueSentences | 39 | | tagDensity | 0.256 | | leniency | 0.513 | | rawRatio | 0.2 | | effectiveRatio | 0.103 | |
| 96.57% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1459 | | totalAiIsmAdverbs | 1 | | found | | | highlights | | |
| 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) | |
| 31.46% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1459 | | totalAiIsms | 20 | | found | | | highlights | | 0 | "pulse" | | 1 | "reminder" | | 2 | "weight" | | 3 | "sanctuary" | | 4 | "scanned" | | 5 | "chaotic" | | 6 | "echoed" | | 7 | "potential" | | 8 | "etched" | | 9 | "stomach" | | 10 | "familiar" | | 11 | "comforting" | | 12 | "tension" | | 13 | "could feel" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "hung in the air" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 87 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 87 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 116 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 58 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1450 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 13 | | unquotedAttributions | 0 | | matches | (empty) | |
| 79.88% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 35 | | wordCount | 927 | | uniqueNames | 13 | | maxNameDensity | 1.4 | | worstName | "Silas" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Silas" | | discoveredNames | | Raven | 1 | | Nest | 1 | | Soho | 2 | | Golden | 1 | | Empress | 1 | | Silas | 13 | | Blackwood | 1 | | Lagavulin | 1 | | London | 1 | | Eva | 1 | | Rory | 10 | | Cardiff | 1 | | Windsor | 1 |
| | persons | | 0 | "Nest" | | 1 | "Silas" | | 2 | "Blackwood" | | 3 | "Eva" | | 4 | "Rory" |
| | places | | 0 | "Raven" | | 1 | "Soho" | | 2 | "London" | | 3 | "Cardiff" | | 4 | "Windsor" |
| | globalScore | 0.799 | | windowScore | 0.833 | |
| 75.37% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 67 | | glossingSentenceCount | 2 | | matches | | 0 | "leg tightened visibly" | | 1 | "felt like a seed growing in the soil of" |
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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 | 1450 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 116 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 44 | | mean | 32.95 | | std | 22.26 | | cv | 0.675 | | sampleLengths | | 0 | 71 | | 1 | 74 | | 2 | 39 | | 3 | 61 | | 4 | 19 | | 5 | 4 | | 6 | 68 | | 7 | 24 | | 8 | 7 | | 9 | 24 | | 10 | 6 | | 11 | 25 | | 12 | 30 | | 13 | 13 | | 14 | 45 | | 15 | 27 | | 16 | 5 | | 17 | 54 | | 18 | 21 | | 19 | 36 | | 20 | 18 | | 21 | 44 | | 22 | 4 | | 23 | 57 | | 24 | 32 | | 25 | 18 | | 26 | 48 | | 27 | 39 | | 28 | 10 | | 29 | 11 | | 30 | 76 | | 31 | 29 | | 32 | 10 | | 33 | 55 | | 34 | 28 | | 35 | 4 | | 36 | 85 | | 37 | 32 | | 38 | 5 | | 39 | 51 | | 40 | 44 | | 41 | 25 | | 42 | 14 | | 43 | 58 |
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| 89.13% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 4 | | totalSentences | 87 | | matches | | 0 | "was peppered" | | 1 | "being crumpled" | | 2 | "was gone" | | 3 | "was gone" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 151 | | matches | (empty) | |
| 68.97% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 3 | | semicolonCount | 1 | | flaggedSentences | 3 | | totalSentences | 116 | | ratio | 0.026 | | matches | | 0 | "Even after all these years, he hadn't lost that silhouette—the slight lean to the left shoulder, the way he centered his weight on his right leg with surgical precision." | | 1 | "The scar—the small crescent on her wrist that used to make her hide her hands while he lectured her on geopolitical history—was still there." | | 2 | "Regret was a heavy burden; he didn't need to add to hers." |
| |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 933 | | adjectiveStacks | 1 | | stackExamples | | 0 | "small, leather-bound notebook." |
| | adverbCount | 17 | | adverbRatio | 0.01822079314040729 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.0053590568060021436 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 116 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 116 | | mean | 12.5 | | std | 9.59 | | cv | 0.767 | | sampleLengths | | 0 | 22 | | 1 | 22 | | 2 | 11 | | 3 | 16 | | 4 | 9 | | 5 | 26 | | 6 | 7 | | 7 | 11 | | 8 | 21 | | 9 | 9 | | 10 | 11 | | 11 | 14 | | 12 | 5 | | 13 | 2 | | 14 | 29 | | 15 | 17 | | 16 | 13 | | 17 | 5 | | 18 | 14 | | 19 | 4 | | 20 | 6 | | 21 | 4 | | 22 | 24 | | 23 | 3 | | 24 | 10 | | 25 | 4 | | 26 | 17 | | 27 | 10 | | 28 | 7 | | 29 | 7 | | 30 | 7 | | 31 | 5 | | 32 | 7 | | 33 | 12 | | 34 | 6 | | 35 | 4 | | 36 | 10 | | 37 | 11 | | 38 | 19 | | 39 | 11 | | 40 | 13 | | 41 | 7 | | 42 | 8 | | 43 | 15 | | 44 | 5 | | 45 | 10 | | 46 | 5 | | 47 | 19 | | 48 | 3 | | 49 | 5 |
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| 44.83% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 6 | | diversityRatio | 0.29310344827586204 | | totalSentences | 116 | | uniqueOpeners | 34 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 83 | | matches | (empty) | | ratio | 0 | |
| 80.24% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 29 | | totalSentences | 83 | | matches | | 0 | "She rubbed her gloved hands" | | 1 | "She wasn't here for work," | | 2 | "She was here because she" | | 3 | "He scanned the room with" | | 4 | "He stopped at the bar." | | 5 | "His auburn hair was peppered" | | 6 | "He moved behind the mahogany" | | 7 | "His voice was a gravelly" | | 8 | "He didn't need to." | | 9 | "He reached behind the counter," | | 10 | "He slid it across the" | | 11 | "She watched the condensation drip" | | 12 | "She was a delivery vector." | | 13 | "He leaned against the counter," | | 14 | "He hadn't just helped hide" | | 15 | "He had watched the abuser," | | 16 | "He stopped a few feet" | | 17 | "He looked older than his" | | 18 | "He used to tower over" | | 19 | "It was the dominance of" |
| | ratio | 0.349 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 77 | | totalSentences | 83 | | matches | | 0 | "The green neon sign outside" | | 1 | "Rory dropped her carrier bag" | | 2 | "The bottles inside clinked, a" | | 3 | "She rubbed her gloved hands" | | 4 | "The Golden Empress delivery uniform" | | 5 | "She wasn't here for work," | | 6 | "The hour was too late," | | 7 | "She was here because she" | | 8 | "The bell above the door" | | 9 | "A man in a trench" | | 10 | "He scanned the room with" | | 11 | "He stopped at the bar." | | 12 | "His auburn hair was peppered" | | 13 | "He moved behind the mahogany" | | 14 | "His voice was a gravelly" | | 15 | "Silas didn't ask for an" | | 16 | "He didn't need to." | | 17 | "The scar—the small crescent on" | | 18 | "The bright blue had dulled" | | 19 | "The fire was gone." |
| | ratio | 0.928 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 83 | | matches | | 0 | "Even after all these years," | | 1 | "Now she was close to" |
| | ratio | 0.024 | |
| 0.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 35 | | technicalSentenceCount | 7 | | matches | | 0 | "Inside, the air was heavy, a damp blanket of stale tobacco and cheap gin that clung to the wool of her coat." | | 1 | "The Golden Empress delivery uniform felt wrong against her skin, scratchy and colored in reds and golds that clashed with the somber elegance of Silas’s sanctua…" | | 2 | "She was here because she needed the taste of something that burned, something that didn't remind her of the restaurant's fumes." | | 3 | "He scanned the room with eyes that missed nothing, hands tucked deep in pockets." | | 4 | "He moved behind the mahogany counter with a fluidity that defied his age." | | 5 | "The scar—the small crescent on her wrist that used to make her hide her hands while he lectured her on geopolitical history—was still there." | | 6 | "The girl who used to sit across from him with notebooks full of pre-law annotations was gone." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 10 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 5 | | fancyCount | 1 | | fancyTags | | 0 | "she whispered (whisper)" |
| | dialogueSentences | 39 | | tagDensity | 0.128 | | leniency | 0.256 | | rawRatio | 0.2 | | effectiveRatio | 0.051 | |