| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 3 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 165 | | tagDensity | 0.018 | | leniency | 0.036 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 97.85% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 2330 | | 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) | |
| 84.98% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 2330 | | totalAiIsms | 7 | | found | | | highlights | | 0 | "lurched" | | 1 | "weight" | | 2 | "silence" | | 3 | "pulsed" | | 4 | "pulse" | | 5 | "desire" |
| |
| 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 | 146 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 146 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 308 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 71 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 2327 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 26 | | unquotedAttributions | 0 | | matches | (empty) | |
| 16.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 66 | | wordCount | 1330 | | uniqueNames | 13 | | maxNameDensity | 2.18 | | worstName | "Aurora" | | maxWindowNameDensity | 4.5 | | worstWindowName | "Aurora" | | discoveredNames | | Moreau | 1 | | Aurora | 29 | | Lucien | 19 | | Thin | 1 | | Eva | 3 | | Soho | 1 | | Whitechapel | 1 | | Rain | 2 | | St | 1 | | Pancras | 1 | | Sabine | 1 | | Blood | 3 | | Heat | 3 |
| | persons | | 0 | "Moreau" | | 1 | "Aurora" | | 2 | "Lucien" | | 3 | "Eva" | | 4 | "Rain" | | 5 | "Sabine" | | 6 | "Blood" | | 7 | "Heat" |
| | places | | 0 | "Thin" | | 1 | "Soho" | | 2 | "St" | | 3 | "Pancras" |
| | globalScore | 0.41 | | windowScore | 0.167 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 106 | | glossingSentenceCount | 2 | | matches | | 0 | "appeared beside his mouth" | | 1 | "felt like a door opening onto winter" |
| |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 2327 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 308 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 248 | | mean | 9.38 | | std | 10.81 | | cv | 1.152 | | sampleLengths | | 0 | 9 | | 1 | 38 | | 2 | 5 | | 3 | 3 | | 4 | 16 | | 5 | 3 | | 6 | 5 | | 7 | 13 | | 8 | 3 | | 9 | 8 | | 10 | 6 | | 11 | 5 | | 12 | 44 | | 13 | 5 | | 14 | 14 | | 15 | 3 | | 16 | 6 | | 17 | 3 | | 18 | 36 | | 19 | 6 | | 20 | 11 | | 21 | 24 | | 22 | 20 | | 23 | 3 | | 24 | 10 | | 25 | 5 | | 26 | 5 | | 27 | 21 | | 28 | 16 | | 29 | 3 | | 30 | 9 | | 31 | 35 | | 32 | 1 | | 33 | 8 | | 34 | 4 | | 35 | 5 | | 36 | 40 | | 37 | 3 | | 38 | 11 | | 39 | 34 | | 40 | 5 | | 41 | 18 | | 42 | 2 | | 43 | 4 | | 44 | 3 | | 45 | 18 | | 46 | 8 | | 47 | 1 | | 48 | 3 | | 49 | 3 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 146 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 220 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 3 | | semicolonCount | 1 | | flaggedSentences | 3 | | totalSentences | 308 | | ratio | 0.01 | | matches | | 0 | "His mismatched eyes found hers through the gap—one amber, one black, both cut sharp with pain." | | 1 | "Amber brightened; black swallowed the light." | | 2 | "Not much—a faint pull at the corner of his black eye—but Aurora had spent months studying his face across candlelit tables, learning how little he needed to conceal a great deal." |
| |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1340 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 21 | | adverbRatio | 0.015671641791044775 | | lyAdverbCount | 0 | | lyAdverbRatio | 0 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 308 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 308 | | mean | 7.56 | | std | 6.5 | | cv | 0.86 | | sampleLengths | | 0 | 9 | | 1 | 14 | | 2 | 16 | | 3 | 8 | | 4 | 5 | | 5 | 3 | | 6 | 16 | | 7 | 3 | | 8 | 5 | | 9 | 13 | | 10 | 3 | | 11 | 8 | | 12 | 6 | | 13 | 5 | | 14 | 8 | | 15 | 12 | | 16 | 7 | | 17 | 17 | | 18 | 5 | | 19 | 14 | | 20 | 3 | | 21 | 6 | | 22 | 3 | | 23 | 12 | | 24 | 18 | | 25 | 6 | | 26 | 6 | | 27 | 3 | | 28 | 8 | | 29 | 9 | | 30 | 10 | | 31 | 5 | | 32 | 20 | | 33 | 3 | | 34 | 10 | | 35 | 5 | | 36 | 5 | | 37 | 5 | | 38 | 16 | | 39 | 9 | | 40 | 7 | | 41 | 3 | | 42 | 9 | | 43 | 12 | | 44 | 23 | | 45 | 1 | | 46 | 8 | | 47 | 4 | | 48 | 5 | | 49 | 12 |
| |
| 47.73% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 7 | | diversityRatio | 0.29545454545454547 | | totalSentences | 308 | | uniqueOpeners | 91 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 143 | | matches | (empty) | | ratio | 0 | |
| 82.94% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 49 | | totalSentences | 143 | | matches | | 0 | "His ivory-handled cane hung from" | | 1 | "His mismatched eyes found hers" | | 2 | "She pushed the door shut." | | 3 | "His cane jammed across the" | | 4 | "His gaze snapped back to" | | 5 | "She drove all three deadbolts" | | 6 | "He pressed his bleeding hand" | | 7 | "His face had gone pale" | | 8 | "Her eyes lifted to his." | | 9 | "His thumb rested over the" | | 10 | "His mouth tightened." | | 11 | "He took the chalk from" | | 12 | "He reached for his cane" | | 13 | "His weight pulled her close," | | 14 | "She shoved him upright." | | 15 | "He lowered himself onto the" | | 16 | "His jaw shifted." | | 17 | "She opened his jacket." | | 18 | "Their edges shone black, as" | | 19 | "She looked up." |
| | ratio | 0.343 | |
| 5.45% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 130 | | totalSentences | 143 | | matches | | 0 | "The door opened as far" | | 1 | "Lucien Moreau stood beneath the" | | 2 | "Rain jewelled his slicked-back hair" | | 3 | "His ivory-handled cane hung from" | | 4 | "Blood glazed his white cuff." | | 5 | "Aurora stopped breathing." | | 6 | "His mismatched eyes found hers" | | 7 | "She pushed the door shut." | | 8 | "His cane jammed across the" | | 9 | "Something struck the front door" | | 10 | "Lucien lurched against it, his" | | 11 | "A wet scraping travelled along" | | 12 | "Lucien glanced over his shoulder." | | 13 | "His gaze snapped back to" | | 14 | "The scraping stopped." | | 15 | "Aurora slid the chain free" | | 16 | "Lucien stumbled over a stack" | | 17 | "She drove all three deadbolts" | | 18 | "A weight hit the other" | | 19 | "The frame shuddered." |
| | ratio | 0.909 | |
| 34.97% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 143 | | matches | | | ratio | 0.007 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 51 | | technicalSentenceCount | 1 | | matches | | 0 | "Lucien looked at her as if she had placed something precious in his palm." |
| |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 3 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 1 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 165 | | tagDensity | 0.006 | | leniency | 0.012 | | rawRatio | 1 | | effectiveRatio | 0.012 | |