| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | |
| 93.98% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 2493 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | 0 | "really" | | 1 | "lightly" | | 2 | "tightly" |
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| 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) | |
| 77.94% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 2493 | | totalAiIsms | 11 | | found | | | highlights | | 0 | "weight" | | 1 | "measured" | | 2 | "charm" | | 3 | "unreadable" | | 4 | "trembled" | | 5 | "pulse" | | 6 | "could feel" | | 7 | "silence" | | 8 | "warmth" | | 9 | "silk" |
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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 | 0 | | narrationSentences | 196 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 3 | | narrationSentences | 196 | | filterMatches | (empty) | | hedgeMatches | | 0 | "started to" | | 1 | "seemed to" |
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| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 319 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 45 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 2493 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 19 | | unquotedAttributions | 0 | | matches | (empty) | |
| 78.44% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 55 | | wordCount | 1677 | | uniqueNames | 9 | | maxNameDensity | 1.43 | | worstName | "Aurora" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Aurora" | | discoveredNames | | Eva | 4 | | Moreau | 1 | | Aurora | 24 | | Lucien | 12 | | Brick | 1 | | Lane | 1 | | One | 5 | | Blood | 3 | | Ptolemy | 4 |
| | persons | | 0 | "Eva" | | 1 | "Moreau" | | 2 | "Aurora" | | 3 | "Lucien" | | 4 | "One" | | 5 | "Blood" | | 6 | "Ptolemy" |
| | places | | | globalScore | 0.784 | | windowScore | 0.833 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 126 | | glossingSentenceCount | 1 | | matches | | 0 | "as if taking stock after an absence he hadn’t earned the right to mention" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 2493 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 319 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 224 | | mean | 11.13 | | std | 12.08 | | cv | 1.086 | | sampleLengths | | 0 | 40 | | 1 | 5 | | 2 | 45 | | 3 | 10 | | 4 | 10 | | 5 | 13 | | 6 | 6 | | 7 | 6 | | 8 | 14 | | 9 | 4 | | 10 | 9 | | 11 | 19 | | 12 | 5 | | 13 | 16 | | 14 | 8 | | 15 | 9 | | 16 | 7 | | 17 | 46 | | 18 | 6 | | 19 | 10 | | 20 | 5 | | 21 | 12 | | 22 | 2 | | 23 | 3 | | 24 | 7 | | 25 | 44 | | 26 | 54 | | 27 | 25 | | 28 | 6 | | 29 | 3 | | 30 | 8 | | 31 | 11 | | 32 | 21 | | 33 | 17 | | 34 | 2 | | 35 | 33 | | 36 | 38 | | 37 | 9 | | 38 | 7 | | 39 | 4 | | 40 | 4 | | 41 | 60 | | 42 | 7 | | 43 | 3 | | 44 | 5 | | 45 | 10 | | 46 | 10 | | 47 | 21 | | 48 | 6 | | 49 | 8 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 196 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 297 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 319 | | ratio | 0 | | matches | (empty) | |
| 97.07% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1684 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 73 | | adverbRatio | 0.04334916864608076 | | lyAdverbCount | 6 | | lyAdverbRatio | 0.0035629453681710215 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 319 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 319 | | mean | 7.82 | | std | 6.46 | | cv | 0.826 | | sampleLengths | | 0 | 11 | | 1 | 29 | | 2 | 5 | | 3 | 13 | | 4 | 8 | | 5 | 9 | | 6 | 9 | | 7 | 6 | | 8 | 10 | | 9 | 10 | | 10 | 13 | | 11 | 6 | | 12 | 6 | | 13 | 14 | | 14 | 4 | | 15 | 9 | | 16 | 13 | | 17 | 2 | | 18 | 2 | | 19 | 2 | | 20 | 5 | | 21 | 16 | | 22 | 8 | | 23 | 9 | | 24 | 7 | | 25 | 11 | | 26 | 35 | | 27 | 6 | | 28 | 10 | | 29 | 5 | | 30 | 12 | | 31 | 2 | | 32 | 3 | | 33 | 7 | | 34 | 22 | | 35 | 14 | | 36 | 8 | | 37 | 7 | | 38 | 8 | | 39 | 5 | | 40 | 17 | | 41 | 17 | | 42 | 25 | | 43 | 6 | | 44 | 3 | | 45 | 8 | | 46 | 11 | | 47 | 5 | | 48 | 16 | | 49 | 2 |
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| 47.18% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 9 | | diversityRatio | 0.2507836990595611 | | totalSentences | 319 | | uniqueOpeners | 80 | |
| 38.99% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 171 | | matches | | 0 | "Of course she noticed." | | 1 | "Somewhere outside, tyres hissed over" |
| | ratio | 0.012 | |
| 46.90% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 74 | | totalSentences | 171 | | matches | | 0 | "His ivory-handled cane rested against" | | 1 | "His mouth twitched, though the" | | 2 | "She started to shut the" | | 3 | "His cane shot across the" | | 4 | "She lifted her gaze back" | | 5 | "She stepped back." | | 6 | "He withdrew the cane and" | | 7 | "She shut the door with" | | 8 | "His laugh came out thin." | | 9 | "He took one step towards" | | 10 | "She always noticed with him," | | 11 | "He lowered himself into the" | | 12 | "She dropped the lot on" | | 13 | "She folded her arms." | | 14 | "His gaze travelled over her" | | 15 | "Her black hair sat in" | | 16 | "His black eye fixed on" | | 17 | "She looked down at her" | | 18 | "She let go at once" | | 19 | "She wrung out the towel" |
| | ratio | 0.433 | |
| 12.63% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 153 | | totalSentences | 171 | | matches | | 0 | "The first deadbolt scraped back," | | 1 | "Aurora yanked the door open" | | 2 | "Lucien Moreau filled the threshold." | | 3 | "Rain silvered his slicked-back hair" | | 4 | "The other sat black and" | | 5 | "His ivory-handled cane rested against" | | 6 | "Aurora’s grip tightened on the" | | 7 | "His mouth twitched, though the" | | 8 | "She started to shut the" | | 9 | "His cane shot across the" | | 10 | "A drop slid from the" | | 11 | "Aurora looked at his hand." | | 12 | "Blood had soaked through the" | | 13 | "She lifted her gaze back" | | 14 | "Ptolemy appeared from nowhere and" | | 15 | "The tabby peered at Lucien," | | 16 | "Aurora glanced down at the" | | 17 | "Lucien’s shoulders eased a fraction." | | 18 | "She stepped back." | | 19 | "He withdrew the cane and" |
| | ratio | 0.895 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 171 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 62 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 0 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |