| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 8 | | adverbTagCount | 2 | | adverbTags | | 0 | "He turned back [back]" | | 1 | "Lucien’s fingers closed around [around]" |
| | dialogueSentences | 94 | | tagDensity | 0.085 | | leniency | 0.17 | | rawRatio | 0.25 | | effectiveRatio | 0.043 | |
| 97.09% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1716 | | 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) | |
| 91.26% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1716 | | totalAiIsms | 3 | | found | | | highlights | | 0 | "flickered" | | 1 | "pulse" | | 2 | "grave" |
| |
| 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 | 133 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 133 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 219 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 33 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1716 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 16 | | unquotedAttributions | 0 | | matches | (empty) | |
| 43.80% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 62 | | wordCount | 1177 | | uniqueNames | 10 | | maxNameDensity | 2.12 | | worstName | "Lucien" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Aurora" | | discoveredNames | | Ptolemy | 6 | | Eva | 3 | | Moreau | 1 | | Brick | 1 | | Lane | 1 | | Aurora | 22 | | Lucien | 25 | | Soho | 1 | | Marseille | 1 | | French | 1 |
| | persons | | 0 | "Ptolemy" | | 1 | "Eva" | | 2 | "Moreau" | | 3 | "Aurora" | | 4 | "Lucien" |
| | places | | 0 | "Brick" | | 1 | "Lane" | | 2 | "Soho" | | 3 | "Marseille" |
| | globalScore | 0.438 | | windowScore | 0.5 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 91 | | 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 | 1716 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 219 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 160 | | mean | 10.73 | | std | 11.39 | | cv | 1.062 | | sampleLengths | | 0 | 29 | | 1 | 13 | | 2 | 56 | | 3 | 8 | | 4 | 6 | | 5 | 6 | | 6 | 16 | | 7 | 7 | | 8 | 4 | | 9 | 16 | | 10 | 1 | | 11 | 4 | | 12 | 2 | | 13 | 16 | | 14 | 26 | | 15 | 6 | | 16 | 4 | | 17 | 4 | | 18 | 41 | | 19 | 7 | | 20 | 5 | | 21 | 10 | | 22 | 11 | | 23 | 22 | | 24 | 7 | | 25 | 5 | | 26 | 6 | | 27 | 4 | | 28 | 6 | | 29 | 5 | | 30 | 10 | | 31 | 4 | | 32 | 9 | | 33 | 44 | | 34 | 20 | | 35 | 2 | | 36 | 3 | | 37 | 3 | | 38 | 4 | | 39 | 1 | | 40 | 18 | | 41 | 6 | | 42 | 6 | | 43 | 15 | | 44 | 15 | | 45 | 9 | | 46 | 1 | | 47 | 35 | | 48 | 6 | | 49 | 31 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 133 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 191 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 1 | | flaggedSentences | 1 | | totalSentences | 219 | | ratio | 0.005 | | matches | | 0 | "One eye caught the hall light in molten amber; the other looked black enough to swallow it." |
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| 88.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1181 | | adjectiveStacks | 2 | | stackExamples | | 0 | "lay slick against his" | | 1 | "black-red against charcoal" |
| | adverbCount | 40 | | adverbRatio | 0.03386960203217612 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.004233700254022015 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 219 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 219 | | mean | 7.84 | | std | 6.08 | | cv | 0.775 | | sampleLengths | | 0 | 5 | | 1 | 3 | | 2 | 21 | | 3 | 13 | | 4 | 24 | | 5 | 7 | | 6 | 8 | | 7 | 17 | | 8 | 8 | | 9 | 6 | | 10 | 6 | | 11 | 16 | | 12 | 7 | | 13 | 4 | | 14 | 9 | | 15 | 7 | | 16 | 1 | | 17 | 4 | | 18 | 2 | | 19 | 16 | | 20 | 5 | | 21 | 6 | | 22 | 15 | | 23 | 6 | | 24 | 4 | | 25 | 4 | | 26 | 9 | | 27 | 32 | | 28 | 7 | | 29 | 5 | | 30 | 7 | | 31 | 3 | | 32 | 11 | | 33 | 9 | | 34 | 7 | | 35 | 6 | | 36 | 7 | | 37 | 5 | | 38 | 6 | | 39 | 4 | | 40 | 6 | | 41 | 5 | | 42 | 10 | | 43 | 4 | | 44 | 6 | | 45 | 3 | | 46 | 5 | | 47 | 12 | | 48 | 27 | | 49 | 20 |
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| 46.35% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 8 | | diversityRatio | 0.2237442922374429 | | totalSentences | 219 | | uniqueOpeners | 49 | |
| 78.74% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 127 | | matches | | 0 | "Then the second." | | 1 | "Then something moved in the" | | 2 | "Then she remembered waking in" |
| | ratio | 0.024 | |
| 97.17% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 39 | | totalSentences | 127 | | matches | | 0 | "His platinum hair lay slick" | | 1 | "His ivory-handled cane rested against" | | 2 | "She shut the door." | | 3 | "He kept his hand in" | | 4 | "His mouth shifted, not quite" | | 5 | "She glanced over her shoulder." | | 6 | "Her hand froze on the" | | 7 | "He looked down the stairwell" | | 8 | "His jaw tightened." | | 9 | "She nearly shut the door" | | 10 | "His grip slid down to" | | 11 | "It had run down onto" | | 12 | "She glared until he crossed" | | 13 | "He placed the cane across" | | 14 | "His fingers stayed curled around" | | 15 | "Her black hair had slipped" | | 16 | "She shoved it behind one" | | 17 | "His eyes lifted to hers." | | 18 | "His mouth against her temple" | | 19 | "She seized his wrist." |
| | ratio | 0.307 | |
| 7.24% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 115 | | totalSentences | 127 | | matches | | 0 | "The first deadbolt scraped back." | | 1 | "Aurora kept one hand on" | | 2 | "Lucien Moreau stood in the" | | 3 | "Water darkened the shoulders of" | | 4 | "His platinum hair lay slick" | | 5 | "His ivory-handled cane rested against" | | 6 | "Aurora’s fingers tightened around the" | | 7 | "Lucien looked past her, into" | | 8 | "She shut the door." | | 9 | "The cane tip struck wood" | | 10 | "Lucien’s gloved hand pressed into" | | 11 | "The door shuddered between them." | | 12 | "Lucien did not force it" | | 13 | "He kept his hand in" | | 14 | "A laugh came out of" | | 15 | "His mouth shifted, not quite" | | 16 | "The words struck harder than" | | 17 | "Lucien’s amber eye lowered for" | | 18 | "The other stayed fixed on" | | 19 | "She glanced over her shoulder." |
| | ratio | 0.906 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 127 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 39 | | technicalSentenceCount | 1 | | matches | | 0 | "Lucien Moreau stood in the stairwell beneath the weak yellow bulb, immaculate in a charcoal suit that had no business surviving Brick Lane’s rain." |
| |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 8 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 3 | | fancyCount | 3 | | fancyTags | | 0 | "she repeated (repeat)" | | 1 | "he murmured (murmur)" | | 2 | "he continued (continue)" |
| | dialogueSentences | 94 | | tagDensity | 0.032 | | leniency | 0.064 | | rawRatio | 1 | | effectiveRatio | 0.064 | |