| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 11 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 35 | | tagDensity | 0.314 | | leniency | 0.629 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1062 | | 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) | |
| 76.46% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1062 | | totalAiIsms | 5 | | found | | | highlights | | 0 | "pulse" | | 1 | "weight" | | 2 | "stomach" | | 3 | "unreadable" | | 4 | "flicked" |
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| 66.67% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 2 | | maxInWindow | 2 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 1 |
| | 1 | | label | "stomach dropped/sank" | | count | 1 |
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| | highlights | | 0 | "eyes narrowed" | | 1 | "stomach dropped" |
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| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 102 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 102 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 125 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 34 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 5 | | markdownWords | 7 | | totalWords | 1056 | | ratio | 0.007 | | matches | | 0 | "thunk" | | 1 | "\"Aurora. Open up.\"" | | 2 | "him" | | 3 | "thud" | | 4 | "my" |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 10 | | unquotedAttributions | 0 | | matches | (empty) | |
| 50.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 36 | | wordCount | 883 | | uniqueNames | 8 | | maxNameDensity | 1.36 | | worstName | "Rory" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Lucien" | | discoveredNames | | Rory | 12 | | Eva | 2 | | Ptolemy | 4 | | Moreau | 1 | | Marseille | 1 | | Soho | 1 | | Lucien | 12 | | Should | 3 |
| | persons | | 0 | "Rory" | | 1 | "Eva" | | 2 | "Ptolemy" | | 3 | "Moreau" | | 4 | "Lucien" | | 5 | "Should" |
| | places | | | globalScore | 0.82 | | windowScore | 0.5 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 61 | | glossingSentenceCount | 1 | | matches | | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.947 | | wordCount | 1056 | | matches | | 0 | "No one knew that knock but" |
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| 86.67% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 3 | | totalSentences | 125 | | matches | | 0 | "knew that knock" | | 1 | "chose that moment" | | 2 | "chose that moment" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 59 | | mean | 17.9 | | std | 14.81 | | cv | 0.827 | | sampleLengths | | 0 | 71 | | 1 | 10 | | 2 | 30 | | 3 | 22 | | 4 | 8 | | 5 | 33 | | 6 | 27 | | 7 | 3 | | 8 | 27 | | 9 | 52 | | 10 | 18 | | 11 | 6 | | 12 | 9 | | 13 | 12 | | 14 | 10 | | 15 | 30 | | 16 | 21 | | 17 | 9 | | 18 | 15 | | 19 | 50 | | 20 | 6 | | 21 | 48 | | 22 | 5 | | 23 | 30 | | 24 | 6 | | 25 | 7 | | 26 | 20 | | 27 | 25 | | 28 | 3 | | 29 | 5 | | 30 | 10 | | 31 | 21 | | 32 | 13 | | 33 | 16 | | 34 | 57 | | 35 | 12 | | 36 | 8 | | 37 | 10 | | 38 | 29 | | 39 | 24 | | 40 | 8 | | 41 | 45 | | 42 | 23 | | 43 | 13 | | 44 | 10 | | 45 | 18 | | 46 | 13 | | 47 | 4 | | 48 | 3 | | 49 | 4 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 102 | | matches | (empty) | |
| 6.20% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 5 | | totalVerbs | 172 | | matches | | 0 | "was reaching" | | 1 | "was doing" | | 2 | "was slipping" | | 3 | "was waiting" | | 4 | "was watching" |
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| 28.57% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 5 | | semicolonCount | 0 | | flaggedSentences | 5 | | totalSentences | 125 | | ratio | 0.04 | | matches | | 0 | "The flat smelled of lavender and old paper—Eva’s signature scent, sharp with the faint metallic tang of Ptolemy’s favourite tuna treats left scattered on the kitchen counter." | | 1 | "She’d locked them after the last time—after *him*." | | 2 | "Should’ve—" | | 3 | "She remembered the first time she’d met him—Eva dragging her into some back-alley bar in Soho, introducing her to a man with a smile like a blade and a reputation for trouble." | | 4 | "The way he said her name—like it was a prayer." |
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| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 888 | | adjectiveStacks | 1 | | stackExamples | | 0 | "small, leather-bound book." |
| | adverbCount | 22 | | adverbRatio | 0.024774774774774775 | | lyAdverbCount | 3 | | lyAdverbRatio | 0.0033783783783783786 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 125 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 125 | | mean | 8.45 | | std | 6.6 | | cv | 0.781 | | sampleLengths | | 0 | 20 | | 1 | 24 | | 2 | 27 | | 3 | 10 | | 4 | 10 | | 5 | 9 | | 6 | 3 | | 7 | 8 | | 8 | 2 | | 9 | 15 | | 10 | 3 | | 11 | 2 | | 12 | 2 | | 13 | 3 | | 14 | 3 | | 15 | 21 | | 16 | 12 | | 17 | 17 | | 18 | 6 | | 19 | 4 | | 20 | 3 | | 21 | 3 | | 22 | 2 | | 23 | 8 | | 24 | 14 | | 25 | 11 | | 26 | 23 | | 27 | 18 | | 28 | 6 | | 29 | 12 | | 30 | 6 | | 31 | 6 | | 32 | 3 | | 33 | 8 | | 34 | 4 | | 35 | 5 | | 36 | 4 | | 37 | 1 | | 38 | 13 | | 39 | 17 | | 40 | 5 | | 41 | 7 | | 42 | 9 | | 43 | 5 | | 44 | 4 | | 45 | 12 | | 46 | 3 | | 47 | 9 | | 48 | 9 | | 49 | 14 |
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| 42.80% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 9 | | diversityRatio | 0.28 | | totalSentences | 125 | | uniqueOpeners | 35 | |
| 36.63% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 91 | | matches | | 0 | "Instead, he reached into his" |
| | ratio | 0.011 | |
| 88.13% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 30 | | totalSentences | 91 | | matches | | 0 | "She’d just stepped out of" | | 1 | "She was reaching for the" | | 2 | "Her pulse jumped." | | 3 | "She didn’t move." | | 4 | "She knew it like she" | | 5 | "She crouched, scratching behind his" | | 6 | "She’d locked them after the" | | 7 | "His platinum hair was damp" | | 8 | "His amber eye locked onto" | | 9 | "She should’ve slammed the door." | | 10 | "he said, stepping over the" | | 11 | "His gaze was still on" | | 12 | "His voice dropped, rough at" | | 13 | "He took another step forward," | | 14 | "He tossed it onto the" | | 15 | "It landed with a soft" | | 16 | "His voice was quiet now," | | 17 | "She knew what that meant." | | 18 | "She crossed her arms, the" | | 19 | "His gaze flicked to her" |
| | ratio | 0.33 | |
| 58.90% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 73 | | totalSentences | 91 | | matches | | 0 | "The third deadbolt clicked shut" | | 1 | "She’d just stepped out of" | | 2 | "The flat smelled of lavender" | | 3 | "She was reaching for the" | | 4 | "This was three sharp raps," | | 5 | "Her pulse jumped." | | 6 | "The towel slipped lower, exposing" | | 7 | "She didn’t move." | | 8 | "The voice was smooth, accented," | | 9 | "She knew it like she" | | 10 | "Ptolemy chose that moment to" | | 11 | "She crouched, scratching behind his" | | 12 | "The doorknob turned." | | 13 | "Rory’s stomach dropped." | | 14 | "She’d locked them after the" | | 15 | "Lucien Moreau stood there, filling" | | 16 | "His platinum hair was damp" | | 17 | "The cane leaned against the" | | 18 | "His amber eye locked onto" | | 19 | "The black one stayed fixed" |
| | ratio | 0.802 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 91 | | matches | (empty) | | ratio | 0 | |
| 95.24% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 30 | | technicalSentenceCount | 2 | | matches | | 0 | "Ptolemy chose that moment to wind himself around her ankles, purring, his tail flicking against her shin." | | 1 | "The door clicked shut behind him, the deadbolts engaging with a finality that made her skin prickle." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 11 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 4 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 35 | | tagDensity | 0.114 | | leniency | 0.229 | | rawRatio | 0.25 | | effectiveRatio | 0.057 | |