| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 17 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 136 | | tagDensity | 0.125 | | leniency | 0.25 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 97.69% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 2161 | | 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) | |
| 83.80% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 2161 | | totalAiIsms | 7 | | found | | | highlights | | 0 | "measured" | | 1 | "charm" | | 2 | "flicked" | | 3 | "silence" | | 4 | "stomach" | | 5 | "comforting" |
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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 | 146 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 146 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 267 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 45 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 2161 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 31 | | unquotedAttributions | 0 | | matches | (empty) | |
| 66.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 59 | | wordCount | 1283 | | uniqueNames | 13 | | maxNameDensity | 1.64 | | worstName | "Lucien" | | maxWindowNameDensity | 3 | | worstWindowName | "Lucien" | | discoveredNames | | Moreau | 1 | | Eva | 5 | | Lucien | 21 | | Bengali | 1 | | Marseille | 1 | | Mrs | 1 | | Basu | 1 | | Ptolemy | 4 | | Brick | 1 | | Lane | 1 | | Aurora | 20 | | Evan | 1 | | Whitechapel | 1 |
| | persons | | 0 | "Moreau" | | 1 | "Eva" | | 2 | "Lucien" | | 3 | "Mrs" | | 4 | "Basu" | | 5 | "Ptolemy" | | 6 | "Aurora" | | 7 | "Evan" |
| | places | | 0 | "Bengali" | | 1 | "Marseille" | | 2 | "Brick" | | 3 | "Lane" |
| | globalScore | 0.682 | | windowScore | 0.667 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 99 | | glossingSentenceCount | 1 | | matches | | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 2161 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 2 | | totalSentences | 267 | | matches | | 0 | "hated that memory" | | 1 | "hated that it" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 185 | | mean | 11.68 | | std | 13.14 | | cv | 1.125 | | sampleLengths | | 0 | 11 | | 1 | 19 | | 2 | 57 | | 3 | 6 | | 4 | 11 | | 5 | 1 | | 6 | 50 | | 7 | 2 | | 8 | 4 | | 9 | 8 | | 10 | 6 | | 11 | 16 | | 12 | 9 | | 13 | 38 | | 14 | 2 | | 15 | 5 | | 16 | 4 | | 17 | 52 | | 18 | 11 | | 19 | 4 | | 20 | 2 | | 21 | 27 | | 22 | 3 | | 23 | 15 | | 24 | 35 | | 25 | 2 | | 26 | 13 | | 27 | 7 | | 28 | 52 | | 29 | 18 | | 30 | 3 | | 31 | 1 | | 32 | 9 | | 33 | 6 | | 34 | 11 | | 35 | 34 | | 36 | 4 | | 37 | 3 | | 38 | 5 | | 39 | 14 | | 40 | 2 | | 41 | 19 | | 42 | 16 | | 43 | 8 | | 44 | 5 | | 45 | 17 | | 46 | 61 | | 47 | 6 | | 48 | 21 | | 49 | 4 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 146 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 224 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 1 | | flaggedSentences | 1 | | totalSentences | 267 | | ratio | 0.004 | | matches | | 0 | "One eye caught the yellow hall light in amber; the other held it without reflecting anything back." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 824 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 19 | | adverbRatio | 0.023058252427184466 | | lyAdverbCount | 4 | | lyAdverbRatio | 0.0048543689320388345 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 267 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 267 | | mean | 8.09 | | std | 6.76 | | cv | 0.836 | | sampleLengths | | 0 | 11 | | 1 | 19 | | 2 | 23 | | 3 | 9 | | 4 | 8 | | 5 | 17 | | 6 | 6 | | 7 | 11 | | 8 | 1 | | 9 | 8 | | 10 | 7 | | 11 | 5 | | 12 | 30 | | 13 | 2 | | 14 | 4 | | 15 | 8 | | 16 | 6 | | 17 | 7 | | 18 | 9 | | 19 | 9 | | 20 | 6 | | 21 | 14 | | 22 | 6 | | 23 | 12 | | 24 | 2 | | 25 | 5 | | 26 | 4 | | 27 | 8 | | 28 | 7 | | 29 | 3 | | 30 | 34 | | 31 | 4 | | 32 | 7 | | 33 | 4 | | 34 | 2 | | 35 | 27 | | 36 | 3 | | 37 | 15 | | 38 | 5 | | 39 | 15 | | 40 | 6 | | 41 | 9 | | 42 | 2 | | 43 | 3 | | 44 | 10 | | 45 | 7 | | 46 | 7 | | 47 | 45 | | 48 | 6 | | 49 | 12 |
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| 45.13% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 13 | | diversityRatio | 0.250936329588015 | | totalSentences | 267 | | uniqueOpeners | 67 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 126 | | matches | (empty) | | ratio | 0 | |
| 83.49% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 43 | | totalSentences | 126 | | matches | | 0 | "His charcoal suit looked pressed" | | 1 | "His mouth shifted, not quite" | | 2 | "He did not force it" | | 3 | "He only held it there," | | 4 | "She stared at his hand" | | 5 | "Her mind latched onto it" | | 6 | "She hated that memory." | | 7 | "She hated that it still" | | 8 | "She stepped back, not because" | | 9 | "He shut the door and" | | 10 | "His hand left the last" | | 11 | "He looked at the locks," | | 12 | "His amber eye dropped for" | | 13 | "She needed something to do" | | 14 | "His clean scent cut through" | | 15 | "He belonged nowhere in this" | | 16 | "She gave him a hard" | | 17 | "He drew in a breath" | | 18 | "He did not touch the" | | 19 | "She saw it in the" |
| | ratio | 0.341 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 120 | | totalSentences | 126 | | matches | | 0 | "The first deadbolt scraped back," | | 1 | "Aurora opened the door with" | | 2 | "Lucien Moreau stood in the" | | 3 | "His charcoal suit looked pressed" | | 4 | "Platinum hair lay slicked away" | | 5 | "Aurora stopped with the door" | | 6 | "The fork slipped from her" | | 7 | "Lucien looked past her shoulder" | | 8 | "Books formed crooked towers along" | | 9 | "Scrolls spilled from an armchair." | | 10 | "Ptolemy sat on the kitchen" | | 11 | "His mouth shifted, not quite" | | 12 | "Aurora pushed the door towards" | | 13 | "Lucien caught it before it" | | 14 | "He did not force it" | | 15 | "He only held it there," | | 16 | "She stared at his hand" | | 17 | "The knuckles showed pale beneath" | | 18 | "A ridiculous detail." | | 19 | "Her mind latched onto it" |
| | ratio | 0.952 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 126 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 47 | | technicalSentenceCount | 1 | | matches | | 0 | "She stepped back, not because she forgave him, not because his voice still carried that low Marseille roughness that snagged under her ribs, but because she ref…" |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 17 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 13 | | fancyCount | 2 | | fancyTags | | 0 | "Lucien murmured (murmur)" | | 1 | "Aurora added (add)" |
| | dialogueSentences | 136 | | tagDensity | 0.096 | | leniency | 0.191 | | rawRatio | 0.154 | | effectiveRatio | 0.029 | |