| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 16 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 92 | | tagDensity | 0.174 | | leniency | 0.348 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 95.48% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1105 | | 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) | |
| 68.33% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1105 | | totalAiIsms | 7 | | found | | | highlights | | 0 | "weight" | | 1 | "silence" | | 2 | "fluttered" | | 3 | "warmth" | | 4 | "perfect" | | 5 | "whisper" |
| |
| 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 | 96 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 2 | | narrationSentences | 96 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 173 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 42 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1105 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 30 | | unquotedAttributions | 0 | | matches | (empty) | |
| 87.79% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 30 | | wordCount | 643 | | uniqueNames | 15 | | maxNameDensity | 1.24 | | worstName | "Aurora" | | maxWindowNameDensity | 2 | | worstWindowName | "Aurora" | | discoveredNames | | Eva | 1 | | Lucien | 6 | | Moreau | 1 | | Brick | 1 | | Lane | 1 | | Aurora | 8 | | Yu-Fei | 1 | | Cheung | 1 | | Golden | 1 | | Empress | 1 | | Cardiff | 1 | | Brendan | 1 | | Jennifer | 1 | | Pre-Law | 1 | | Ptolemy | 4 |
| | persons | | 0 | "Eva" | | 1 | "Lucien" | | 2 | "Moreau" | | 3 | "Aurora" | | 4 | "Yu-Fei" | | 5 | "Cheung" | | 6 | "Empress" | | 7 | "Brendan" | | 8 | "Jennifer" | | 9 | "Ptolemy" |
| | places | | 0 | "Brick" | | 1 | "Lane" | | 2 | "Cardiff" |
| | globalScore | 0.878 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 42 | | 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 | 1105 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 173 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 109 | | mean | 10.14 | | std | 10.66 | | cv | 1.051 | | sampleLengths | | 0 | 8 | | 1 | 78 | | 2 | 20 | | 3 | 3 | | 4 | 6 | | 5 | 25 | | 6 | 2 | | 7 | 39 | | 8 | 3 | | 9 | 3 | | 10 | 39 | | 11 | 19 | | 12 | 7 | | 13 | 13 | | 14 | 2 | | 15 | 1 | | 16 | 22 | | 17 | 13 | | 18 | 4 | | 19 | 3 | | 20 | 11 | | 21 | 15 | | 22 | 8 | | 23 | 2 | | 24 | 18 | | 25 | 12 | | 26 | 12 | | 27 | 17 | | 28 | 4 | | 29 | 4 | | 30 | 8 | | 31 | 7 | | 32 | 6 | | 33 | 15 | | 34 | 5 | | 35 | 6 | | 36 | 35 | | 37 | 8 | | 38 | 1 | | 39 | 15 | | 40 | 5 | | 41 | 15 | | 42 | 7 | | 43 | 4 | | 44 | 14 | | 45 | 11 | | 46 | 4 | | 47 | 4 | | 48 | 11 | | 49 | 11 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 96 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 130 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 173 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 565 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 18 | | adverbRatio | 0.03185840707964602 | | lyAdverbCount | 1 | | lyAdverbRatio | 0.0017699115044247787 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 173 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 173 | | mean | 6.39 | | std | 5.13 | | cv | 0.803 | | sampleLengths | | 0 | 8 | | 1 | 17 | | 2 | 18 | | 3 | 24 | | 4 | 7 | | 5 | 12 | | 6 | 17 | | 7 | 3 | | 8 | 3 | | 9 | 6 | | 10 | 21 | | 11 | 4 | | 12 | 2 | | 13 | 4 | | 14 | 5 | | 15 | 9 | | 16 | 7 | | 17 | 14 | | 18 | 3 | | 19 | 3 | | 20 | 3 | | 21 | 4 | | 22 | 8 | | 23 | 12 | | 24 | 8 | | 25 | 4 | | 26 | 12 | | 27 | 7 | | 28 | 7 | | 29 | 3 | | 30 | 7 | | 31 | 3 | | 32 | 2 | | 33 | 1 | | 34 | 8 | | 35 | 10 | | 36 | 4 | | 37 | 8 | | 38 | 5 | | 39 | 4 | | 40 | 3 | | 41 | 4 | | 42 | 7 | | 43 | 8 | | 44 | 3 | | 45 | 4 | | 46 | 8 | | 47 | 2 | | 48 | 9 | | 49 | 9 |
| |
| 42.49% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 13 | | diversityRatio | 0.2254335260115607 | | totalSentences | 173 | | uniqueOpeners | 39 | |
| 85.47% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 78 | | matches | | 0 | "Bright blue eyes held still." | | 1 | "Somewhere a train rattled." |
| | ratio | 0.026 | |
| 25.13% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 38 | | totalSentences | 78 | | matches | | 0 | "He stood in the narrow" | | 1 | "His ivory-handled cane rested against" | | 2 | "She stared at him." | | 3 | "She stepped back." | | 4 | "He was five eleven to" | | 5 | "He filled the frame." | | 6 | "His mouth thinned." | | 7 | "She didn’t look down." | | 8 | "She lifted her chin." | | 9 | "He studied the books piled" | | 10 | "She closed her eyes for" | | 11 | "He shifted his weight." | | 12 | "His amber eye narrowed." | | 13 | "Her hair fell forward, straight" | | 14 | "She laughed once, sharp and" | | 15 | "She looked at the door," | | 16 | "He stepped forward." | | 17 | "He smelled of cold iron" | | 18 | "Her hand dropped." | | 19 | "He looked past her into" |
| | ratio | 0.487 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 75 | | totalSentences | 78 | | matches | | 0 | "The three deadbolts screeched one" | | 1 | "Aurora kept her shoulder against" | | 2 | "The hallway light from Eva’s" | | 3 | "He stood in the narrow" | | 4 | "His ivory-handled cane rested against" | | 5 | "The amber eye fixed on" | | 6 | "Ptolemy launched from the bookshelf" | | 7 | "The tabby hissed." | | 8 | "Lucien didn’t move." | | 9 | "Aurora’s hand found the scar" | | 10 | "She stared at him." | | 11 | "The flat behind her was" | | 12 | "Scrolls and research notes covered" | | 13 | "A stack of takeaway menus" | | 14 | "She stepped back." | | 15 | "The door didn’t close." | | 16 | "The hallway smelled of cumin" | | 17 | "Lucien took one step up" | | 18 | "He was five eleven to" | | 19 | "He filled the frame." |
| | ratio | 0.962 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 78 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 19 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 16 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 15 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 92 | | tagDensity | 0.163 | | leniency | 0.326 | | rawRatio | 0 | | effectiveRatio | 0 | |