| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 7 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 19 | | tagDensity | 0.368 | | leniency | 0.737 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 661 | | 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) | |
| 47.05% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 661 | | totalAiIsms | 7 | | found | | | highlights | | 0 | "porcelain" | | 1 | "weight" | | 2 | "silence" | | 3 | "pulse" | | 4 | "chilled" | | 5 | "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 | 0 | | narrationSentences | 63 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 63 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 75 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 22 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 650 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 5 | | unquotedAttributions | 0 | | matches | (empty) | |
| 94.03% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 28 | | wordCount | 536 | | uniqueNames | 15 | | maxNameDensity | 1.12 | | worstName | "Rory" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Rory" | | discoveredNames | | Rory | 6 | | Moreau | 1 | | Eva | 2 | | Ptolemy | 4 | | London | 2 | | University | 1 | | Cardiff | 1 | | Latin | 1 | | Lucien | 4 | | Brick | 1 | | Lane | 1 | | Dublin | 1 | | Middle | 1 | | French | 1 | | Provençal | 1 |
| | persons | | 0 | "Rory" | | 1 | "Moreau" | | 2 | "Eva" | | 3 | "Ptolemy" | | 4 | "Lucien" |
| | places | | 0 | "London" | | 1 | "Brick" | | 2 | "Lane" | | 3 | "Dublin" | | 4 | "Provençal" |
| | globalScore | 0.94 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 41 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 650 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 75 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 28 | | mean | 23.21 | | std | 14.8 | | cv | 0.638 | | sampleLengths | | 0 | 56 | | 1 | 5 | | 2 | 6 | | 3 | 51 | | 4 | 5 | | 5 | 24 | | 6 | 38 | | 7 | 41 | | 8 | 39 | | 9 | 21 | | 10 | 50 | | 11 | 3 | | 12 | 19 | | 13 | 31 | | 14 | 9 | | 15 | 6 | | 16 | 11 | | 17 | 10 | | 18 | 35 | | 19 | 27 | | 20 | 15 | | 21 | 21 | | 22 | 12 | | 23 | 34 | | 24 | 20 | | 25 | 19 | | 26 | 23 | | 27 | 19 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 63 | | matches | (empty) | |
| 0.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 3 | | totalVerbs | 89 | | matches | | 0 | "was getting" | | 1 | "wasn't thinking" | | 2 | "was thinking" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 5 | | semicolonCount | 0 | | flaggedSentences | 5 | | totalSentences | 75 | | ratio | 0.067 | | matches | | 0 | "She shouldered the door open—and froze." | | 1 | "\"Breaking and entering now, Luc? Classy.\" Rory dropped her keys in the chipped porcelain dish by the door—a nervous habit." | | 2 | "His gloves were new—butter-soft leather that probably cost more than her monthly rent." | | 3 | "Until she could smell his cologne—vetiver and something darker underneath." | | 4 | "Outside, London carried on—the honking taxis, the curry-scented air." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 546 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 19 | | adverbRatio | 0.0347985347985348 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.009157509157509158 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 75 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 75 | | mean | 8.67 | | std | 5.36 | | cv | 0.618 | | sampleLengths | | 0 | 20 | | 1 | 14 | | 2 | 13 | | 3 | 9 | | 4 | 5 | | 5 | 6 | | 6 | 17 | | 7 | 6 | | 8 | 20 | | 9 | 4 | | 10 | 4 | | 11 | 5 | | 12 | 4 | | 13 | 6 | | 14 | 14 | | 15 | 20 | | 16 | 7 | | 17 | 11 | | 18 | 13 | | 19 | 13 | | 20 | 15 | | 21 | 7 | | 22 | 22 | | 23 | 10 | | 24 | 14 | | 25 | 7 | | 26 | 6 | | 27 | 19 | | 28 | 7 | | 29 | 18 | | 30 | 3 | | 31 | 4 | | 32 | 2 | | 33 | 1 | | 34 | 5 | | 35 | 7 | | 36 | 17 | | 37 | 11 | | 38 | 3 | | 39 | 9 | | 40 | 6 | | 41 | 4 | | 42 | 4 | | 43 | 3 | | 44 | 10 | | 45 | 9 | | 46 | 1 | | 47 | 1 | | 48 | 16 | | 49 | 8 |
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| 79.56% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 2 | | diversityRatio | 0.49333333333333335 | | totalSentences | 75 | | uniqueOpeners | 37 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 54 | | matches | | 0 | "Just like she remembered." | | 1 | "Somewhere, Ptolemy yowled and darted" |
| | ratio | 0.037 | |
| 71.85% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 20 | | totalSentences | 54 | | matches | | 0 | "She paused with her key" | | 1 | "She shouldered the door open—and" | | 2 | "His cane rested against the" | | 3 | "He'd turned at the sound" | | 4 | "Her name in that goddamn" | | 5 | "He produced a brass one" | | 6 | "His gloves were new—butter—soft leather" | | 7 | "Her faded University of Cardiff" | | 8 | "She nudged a stack of" | | 9 | "It had been six months" | | 10 | "She should make tea." | | 11 | "He rose, cane in hand," | | 12 | "She folded her arms." | | 13 | "He took a step forward." | | 14 | "His glove brushed her forearm" | | 15 | "His nearness was a live" | | 16 | "His thumb grazed her scar" | | 17 | "His lips were warm against" | | 18 | "She didn't care." | | 19 | "She was thinking about the" |
| | ratio | 0.37 | |
| 34.07% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 46 | | totalSentences | 54 | | matches | | 0 | "The triple deadbolts rattled under" | | 1 | "The scent of cumin and" | | 2 | "She paused with her key" | | 3 | "The damn overqualified delivery girl" | | 4 | "The third bolt gave way." | | 5 | "She shouldered the door open—and" | | 6 | "Lucien Moreau stood in the" | | 7 | "His cane rested against the" | | 8 | "He'd turned at the sound" | | 9 | "Ptolemy purred like a traitor." | | 10 | "Her name in that goddamn" | | 11 | "The bastard hadn't even bothered" | | 12 | "Rory dropped her keys in" | | 13 | "The dish cracked further under" | | 14 | "He produced a brass one" | | 15 | "His gloves were new—butter—soft leather" | | 16 | "The lie rolled off his" | | 17 | "Rory dumped her bag by" | | 18 | "Her faded University of Cardiff" | | 19 | "She nudged a stack of" |
| | ratio | 0.852 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 54 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 22 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 7 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 97.37% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 2 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 19 | | tagDensity | 0.105 | | leniency | 0.211 | | rawRatio | 0.5 | | effectiveRatio | 0.105 | |