| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 31 | | adverbTagCount | 3 | | adverbTags | | 0 | "She stepped aside [aside]" | | 1 | "She swallowed hard [hard]" | | 2 | "he asked quietly [quietly]" |
| | dialogueSentences | 67 | | tagDensity | 0.463 | | leniency | 0.925 | | rawRatio | 0.097 | | effectiveRatio | 0.09 | |
| 82.15% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1961 | | totalAiIsmAdverbs | 7 | | found | | | highlights | | 0 | "very" | | 1 | "suddenly" | | 2 | "slowly" | | 3 | "slightly" | | 4 | "perfectly" |
| |
| 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) | |
| 31.16% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1961 | | totalAiIsms | 27 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | word | "down her spine" | | count | 1 |
| | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | | | 13 | | | 14 | | | 15 | | | 16 | | | 17 | | | 18 | |
| | highlights | | 0 | "familiar" | | 1 | "intensity" | | 2 | "lilt" | | 3 | "perfect" | | 4 | "silence" | | 5 | "flicked" | | 6 | "down her spine" | | 7 | "effortless" | | 8 | "stomach" | | 9 | "vibrated" | | 10 | "beacon" | | 11 | "traced" | | 12 | "trembled" | | 13 | "tracing" | | 14 | "pulse" | | 15 | "racing" | | 16 | "could feel" | | 17 | "whisper" | | 18 | "footsteps" |
| |
| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 1 |
|
| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 136 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 3 | | narrationSentences | 136 | | filterMatches | | | hedgeMatches | | 0 | "managed to" | | 1 | "seemed to" | | 2 | "began to" |
| |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 171 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 49 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1961 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 19 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 28 | | wordCount | 1394 | | uniqueNames | 10 | | maxNameDensity | 0.79 | | worstName | "Lucien" | | maxWindowNameDensity | 2 | | worstWindowName | "Lucien" | | discoveredNames | | Marseilles | 1 | | English | 1 | | Lucien | 11 | | Frenchman | 1 | | Aurora | 7 | | Cold | 1 | | Raw | 1 | | Eva | 1 | | Avaros | 1 | | Ptolemy | 3 |
| | persons | | 0 | "Lucien" | | 1 | "Frenchman" | | 2 | "Aurora" | | 3 | "Cold" | | 4 | "Eva" | | 5 | "Ptolemy" |
| | places | (empty) | | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 101 | | glossingSentenceCount | 2 | | matches | | 0 | "something like hunger" | | 1 | "something close to reverence" |
| |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1961 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 171 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 73 | | mean | 26.86 | | std | 17.79 | | cv | 0.662 | | sampleLengths | | 0 | 11 | | 1 | 58 | | 2 | 1 | | 3 | 59 | | 4 | 2 | | 5 | 20 | | 6 | 19 | | 7 | 13 | | 8 | 15 | | 9 | 38 | | 10 | 38 | | 11 | 3 | | 12 | 31 | | 13 | 50 | | 14 | 27 | | 15 | 25 | | 16 | 41 | | 17 | 3 | | 18 | 41 | | 19 | 31 | | 20 | 5 | | 21 | 45 | | 22 | 36 | | 23 | 23 | | 24 | 31 | | 25 | 27 | | 26 | 8 | | 27 | 48 | | 28 | 12 | | 29 | 1 | | 30 | 30 | | 31 | 43 | | 32 | 51 | | 33 | 34 | | 34 | 17 | | 35 | 50 | | 36 | 45 | | 37 | 45 | | 38 | 34 | | 39 | 12 | | 40 | 56 | | 41 | 8 | | 42 | 16 | | 43 | 29 | | 44 | 12 | | 45 | 53 | | 46 | 58 | | 47 | 1 | | 48 | 8 | | 49 | 36 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 136 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 245 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 171 | | ratio | 0 | | matches | (empty) | |
| 82.06% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1398 | | adjectiveStacks | 1 | | stackExamples | | | adverbCount | 75 | | adverbRatio | 0.0536480686695279 | | lyAdverbCount | 24 | | lyAdverbRatio | 0.017167381974248927 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 171 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 171 | | mean | 11.47 | | std | 7.62 | | cv | 0.665 | | sampleLengths | | 0 | 11 | | 1 | 21 | | 2 | 20 | | 3 | 17 | | 4 | 1 | | 5 | 14 | | 6 | 24 | | 7 | 21 | | 8 | 2 | | 9 | 8 | | 10 | 12 | | 11 | 14 | | 12 | 5 | | 13 | 10 | | 14 | 3 | | 15 | 10 | | 16 | 5 | | 17 | 3 | | 18 | 19 | | 19 | 6 | | 20 | 10 | | 21 | 11 | | 22 | 16 | | 23 | 11 | | 24 | 3 | | 25 | 8 | | 26 | 23 | | 27 | 9 | | 28 | 12 | | 29 | 29 | | 30 | 5 | | 31 | 8 | | 32 | 14 | | 33 | 17 | | 34 | 8 | | 35 | 19 | | 36 | 22 | | 37 | 3 | | 38 | 16 | | 39 | 4 | | 40 | 4 | | 41 | 17 | | 42 | 16 | | 43 | 13 | | 44 | 1 | | 45 | 1 | | 46 | 5 | | 47 | 17 | | 48 | 4 | | 49 | 8 |
| |
| 69.98% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 7 | | diversityRatio | 0.4444444444444444 | | totalSentences | 171 | | uniqueOpeners | 76 | |
| 79.37% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 126 | | matches | | 0 | "Instead she found herself leaning" | | 1 | "Instead Lucien walked her backwards" | | 2 | "Somewhere in the distance, heavy" |
| | ratio | 0.024 | |
| 45.40% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 55 | | totalSentences | 126 | | matches | | 0 | "Her bright blue eyes widened," | | 1 | "She did not move to" | | 2 | "Her fingers tightened on the" | | 3 | "He tapped the cane once" | | 4 | "She laughed, short and bitter" | | 5 | "She cut herself off, jaw" | | 6 | "He took one step forward," | | 7 | "She hated how easily he" | | 8 | "She stepped aside finally, but" | | 9 | "He filled the space like" | | 10 | "His gaze drifted down for" | | 11 | "He limped to the sofa" | | 12 | "She knew what hid inside" | | 13 | "He stretched one arm along" | | 14 | "She remained standing, refusing to" | | 15 | "His voice dropped" | | 16 | "She thought of the strange" | | 17 | "Her hand flew to her" | | 18 | "He did not raise his" | | 19 | "Her hands shook as she" |
| | ratio | 0.437 | |
| 43.33% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 105 | | totalSentences | 126 | | matches | | 0 | "The deadbolts rattled like old" | | 1 | "Aurora stood there in an" | | 2 | "The small crescent scar on" | | 3 | "Her bright blue eyes widened," | | 4 | "Lucien leant on his ivory-handled" | | 5 | "The scent of his cologne" | | 6 | "She did not move to" | | 7 | "Ptolemy the tabby cat wound" | | 8 | "Lucien observed, voice carrying that" | | 9 | "Her fingers tightened on the" | | 10 | "He tapped the cane once" | | 11 | "The silence stretched." | | 12 | "Scrolls covered the tiny kitchen" | | 13 | "A half-drunk mug of tea" | | 14 | "Aurora's gaze flicked to the" | | 15 | "She laughed, short and bitter" | | 16 | "She cut herself off, jaw" | | 17 | "He took one step forward," | | 18 | "Heat crawled up her neck." | | 19 | "She hated how easily he" |
| | ratio | 0.833 | |
| 39.68% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 126 | | matches | | 0 | "To that ridiculous platinum hair" |
| | ratio | 0.008 | |
| 80.20% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 57 | | technicalSentenceCount | 5 | | matches | | 0 | "Aurora stood there in an oversized jumper that slipped off one shoulder, her straight black hair still damp from the shower." | | 1 | "Lucien crouched despite the cane, scratching under the cat's chin with the sort of effortless grace that made Aurora want to scream." | | 2 | "Lucien's other hand came up to cup her face, the movement surprisingly gentle for a man who carried a sword in his walking stick." | | 3 | "A conversation that became a confession that became his mouth on hers and her legs wrapped around his waist right there against the kitchen counter." | | 4 | "He broke the kiss only to trail his mouth down her neck, finding the exact spot that made her arch against him." |
| |
| 60.48% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 31 | | uselessAdditionCount | 4 | | matches | | 0 | "Lucien observed, voice carrying that faint Marseilles lilt wrapped in perfect English" | | 1 | "She cut, jaw tight" | | 2 | "He stretched, the picture of casual elegance" | | 3 | "She remained, refusing to sit beside him" |
| |
| 75.37% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 6 | | fancyCount | 5 | | fancyTags | | 0 | "Lucien observed (observe)" | | 1 | "She laughed (laugh)" | | 2 | "she muttered (mutter)" | | 3 | "she whispered (whisper)" | | 4 | "he murmured (murmur)" |
| | dialogueSentences | 67 | | tagDensity | 0.09 | | leniency | 0.179 | | rawRatio | 0.833 | | effectiveRatio | 0.149 | |