| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 16 | | adverbTagCount | 1 | | adverbTags | | 0 | "The basket wailed again [again]" |
| | dialogueSentences | 81 | | tagDensity | 0.198 | | leniency | 0.395 | | rawRatio | 0.063 | | effectiveRatio | 0.025 | |
| 96.75% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1540 | | totalAiIsmAdverbs | 1 | | found | | | highlights | | |
| 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) | |
| 93.51% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1540 | | totalAiIsms | 2 | | found | | | highlights | | |
| 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 | 60 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 60 | | 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 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 56 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1543 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 16 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 9 | | wordCount | 694 | | uniqueNames | 7 | | maxNameDensity | 0.43 | | worstName | "Lucien" | | maxWindowNameDensity | 0.5 | | worstWindowName | "Lucien" | | discoveredNames | | Moreau | 1 | | French | 1 | | Silas | 1 | | Golden | 1 | | Empress | 1 | | Contracts | 1 | | Lucien | 3 |
| | persons | | 0 | "Moreau" | | 1 | "Silas" | | 2 | "Lucien" |
| | places | (empty) | | globalScore | 1 | | 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 | 1543 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 2 | | totalSentences | 125 | | matches | | 0 | "stopped that sentence" | | 1 | "walked that road" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 87 | | mean | 17.74 | | std | 17.64 | | cv | 0.995 | | sampleLengths | | 0 | 8 | | 1 | 44 | | 2 | 12 | | 3 | 13 | | 4 | 4 | | 5 | 14 | | 6 | 18 | | 7 | 26 | | 8 | 2 | | 9 | 18 | | 10 | 31 | | 11 | 5 | | 12 | 13 | | 13 | 7 | | 14 | 10 | | 15 | 86 | | 16 | 16 | | 17 | 9 | | 18 | 13 | | 19 | 2 | | 20 | 44 | | 21 | 25 | | 22 | 51 | | 23 | 4 | | 24 | 4 | | 25 | 7 | | 26 | 1 | | 27 | 26 | | 28 | 47 | | 29 | 9 | | 30 | 3 | | 31 | 1 | | 32 | 23 | | 33 | 35 | | 34 | 15 | | 35 | 4 | | 36 | 8 | | 37 | 32 | | 38 | 13 | | 39 | 2 | | 40 | 8 | | 41 | 43 | | 42 | 13 | | 43 | 2 | | 44 | 2 | | 45 | 4 | | 46 | 21 | | 47 | 4 | | 48 | 4 | | 49 | 89 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 60 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 120 | | matches | | |
| 5.71% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 2 | | semicolonCount | 5 | | flaggedSentences | 6 | | totalSentences | 125 | | ratio | 0.048 | | matches | | 0 | "Rain had beaten his collar; the rest of him stayed pressed charcoal and French." | | 1 | "Her hair still held the dent from the delivery helmet; she hadn't fixed it for him, and she never would." | | 2 | "Inside, the last of the bass had died out of Silas's floorboards an hour ago; now the sounds below were the till drawer and chairs going up on tables." | | 3 | "The black one had never given anything away in his life; the amber did all his feeling for him, and it was doing plenty now." | | 4 | "\"I could dress it up. I speak four languages; I could dress it up in all of them, and underneath it would still be yes.\"" | | 5 | "He went still — the stillness of somebody who knew not to frighten the thing in front of him — and she put her hand flat on his chest, felt the fine quick drum of him through the wool, and kissed him." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 696 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 17 | | adverbRatio | 0.02442528735632184 | | lyAdverbCount | 1 | | lyAdverbRatio | 0.0014367816091954023 | |
| 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 | 12.34 | | std | 10.69 | | cv | 0.866 | | sampleLengths | | 0 | 8 | | 1 | 21 | | 2 | 14 | | 3 | 9 | | 4 | 5 | | 5 | 7 | | 6 | 5 | | 7 | 8 | | 8 | 4 | | 9 | 14 | | 10 | 18 | | 11 | 26 | | 12 | 2 | | 13 | 10 | | 14 | 8 | | 15 | 20 | | 16 | 11 | | 17 | 5 | | 18 | 13 | | 19 | 7 | | 20 | 10 | | 21 | 29 | | 22 | 27 | | 23 | 4 | | 24 | 26 | | 25 | 16 | | 26 | 9 | | 27 | 13 | | 28 | 2 | | 29 | 27 | | 30 | 17 | | 31 | 19 | | 32 | 6 | | 33 | 35 | | 34 | 16 | | 35 | 4 | | 36 | 4 | | 37 | 7 | | 38 | 1 | | 39 | 14 | | 40 | 12 | | 41 | 47 | | 42 | 4 | | 43 | 5 | | 44 | 3 | | 45 | 1 | | 46 | 21 | | 47 | 2 | | 48 | 5 | | 49 | 5 |
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| 61.60% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 8 | | diversityRatio | 0.408 | | totalSentences | 125 | | uniqueOpeners | 51 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 60 | | matches | | 0 | "Then the tea, two mugs," | | 1 | "Then he nodded at her" |
| | ratio | 0.033 | |
| 0.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 39 | | totalSentences | 60 | | matches | | 0 | "She opened the door on" | | 1 | "She looked at the basket." | | 2 | "He shifted the basket to" | | 3 | "Her hair still held the" | | 4 | "She took the chain off" | | 5 | "He set it in her" | | 6 | "Her bike leaned against the" | | 7 | "She unclipped the basket." | | 8 | "She filled the kettle because" | | 9 | "He drew a folded slip" | | 10 | "She fixed him with the" | | 11 | "He set a single new" | | 12 | "She laughed once, at nothing," | | 13 | "He watched the cat." | | 14 | "She stopped that sentence and" | | 15 | "He looked at her then." | | 16 | "She was good at waiting." | | 17 | "She'd had worse teachers." | | 18 | "She drank her tea and" | | 19 | "She leaned a hip into" |
| | ratio | 0.65 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 56 | | totalSentences | 60 | | matches | | 0 | "She opened the door on" | | 1 | "Lucien Moreau stood on her" | | 2 | "Rain had beaten his collar;" | | 3 | "The basket wailed like a" | | 4 | "The basket wailed again" | | 5 | "She looked at the basket." | | 6 | "The basket looked back through" | | 7 | "He shifted the basket to" | | 8 | "Her hair still held the" | | 9 | "She took the chain off" | | 10 | "He set it in her" | | 11 | "Her bike leaned against the" | | 12 | "She unclipped the basket." | | 13 | "The tabby poured out of" | | 14 | "She filled the kettle because" | | 15 | "He drew a folded slip" | | 16 | "She fixed him with the" | | 17 | "He set a single new" | | 18 | "She laughed once, at nothing," | | 19 | "He watched the cat." |
| | ratio | 0.933 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 60 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 24 | | technicalSentenceCount | 1 | | matches | | 0 | "He went still — the stillness of somebody who knew not to frighten the thing in front of him — and she put her hand flat on his chest, felt the fine quick drum …" |
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| 62.50% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 16 | | uselessAdditionCount | 2 | | matches | | 0 | "He drew, his handwriting small and ruled-straight down the page" | | 1 | "She said, because the alternative was an orchestra" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 2 | | fancyCount | 1 | | fancyTags | | 0 | "The basket wailed again (wail)" |
| | dialogueSentences | 81 | | tagDensity | 0.025 | | leniency | 0.049 | | rawRatio | 0.5 | | effectiveRatio | 0.025 | |