| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 2417 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 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) | |
| 93.79% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 2417 | | totalAiIsms | 3 | | found | | | highlights | | 0 | "grave" | | 1 | "coded" | | 2 | "weight" |
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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 | 97 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 97 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 242 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 49 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 2417 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 18 | | unquotedAttributions | 0 | | matches | (empty) | |
| 66.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 55 | | wordCount | 1203 | | uniqueNames | 8 | | maxNameDensity | 1.5 | | worstName | "Rory" | | maxWindowNameDensity | 3 | | worstWindowName | "Rory" | | discoveredNames | | Rory | 18 | | Moreau | 1 | | Lane | 2 | | Ptolemy | 6 | | Lucien | 18 | | Eva | 7 | | Welsh | 1 | | Brick | 2 |
| | persons | | 0 | "Rory" | | 1 | "Moreau" | | 2 | "Ptolemy" | | 3 | "Lucien" | | 4 | "Eva" |
| | places | | | globalScore | 0.752 | | windowScore | 0.667 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 82 | | 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 | 2417 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 242 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 202 | | mean | 11.97 | | std | 11.28 | | cv | 0.943 | | sampleLengths | | 0 | 19 | | 1 | 58 | | 2 | 8 | | 3 | 3 | | 4 | 16 | | 5 | 6 | | 6 | 7 | | 7 | 14 | | 8 | 11 | | 9 | 31 | | 10 | 7 | | 11 | 4 | | 12 | 4 | | 13 | 4 | | 14 | 6 | | 15 | 5 | | 16 | 7 | | 17 | 13 | | 18 | 4 | | 19 | 7 | | 20 | 3 | | 21 | 20 | | 22 | 12 | | 23 | 12 | | 24 | 4 | | 25 | 3 | | 26 | 16 | | 27 | 12 | | 28 | 3 | | 29 | 8 | | 30 | 35 | | 31 | 5 | | 32 | 6 | | 33 | 10 | | 34 | 9 | | 35 | 3 | | 36 | 3 | | 37 | 1 | | 38 | 2 | | 39 | 12 | | 40 | 2 | | 41 | 4 | | 42 | 15 | | 43 | 19 | | 44 | 19 | | 45 | 4 | | 46 | 6 | | 47 | 50 | | 48 | 6 | | 49 | 5 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 97 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 176 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 242 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1207 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 16 | | adverbRatio | 0.013256006628003313 | | lyAdverbCount | 0 | | lyAdverbRatio | 0 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 242 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 242 | | mean | 9.99 | | std | 7.05 | | cv | 0.706 | | sampleLengths | | 0 | 19 | | 1 | 25 | | 2 | 7 | | 3 | 26 | | 4 | 8 | | 5 | 3 | | 6 | 16 | | 7 | 6 | | 8 | 7 | | 9 | 14 | | 10 | 11 | | 11 | 4 | | 12 | 27 | | 13 | 7 | | 14 | 4 | | 15 | 4 | | 16 | 4 | | 17 | 6 | | 18 | 5 | | 19 | 7 | | 20 | 13 | | 21 | 4 | | 22 | 7 | | 23 | 3 | | 24 | 20 | | 25 | 12 | | 26 | 12 | | 27 | 4 | | 28 | 3 | | 29 | 16 | | 30 | 12 | | 31 | 3 | | 32 | 8 | | 33 | 20 | | 34 | 15 | | 35 | 5 | | 36 | 6 | | 37 | 10 | | 38 | 9 | | 39 | 3 | | 40 | 3 | | 41 | 1 | | 42 | 2 | | 43 | 12 | | 44 | 2 | | 45 | 4 | | 46 | 15 | | 47 | 19 | | 48 | 7 | | 49 | 12 |
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| 44.35% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 16 | | diversityRatio | 0.30578512396694213 | | totalSentences | 242 | | uniqueOpeners | 74 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 96 | | matches | (empty) | | ratio | 0 | |
| 57.50% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 39 | | totalSentences | 96 | | matches | | 0 | "His ivory-handled cane rested against" | | 1 | "She pushed the door." | | 2 | "He set the cane tip" | | 3 | "Her gaze dropped to the" | | 4 | "His smile thinned." | | 5 | "He shut the door behind" | | 6 | "He turned into the room" | | 7 | "His height filled the narrow" | | 8 | "He took in Rory's bare" | | 9 | "He followed her gaze to" | | 10 | "She stepped around him and" | | 11 | "He set the atlases on" | | 12 | "He lowered himself onto the" | | 13 | "He shrugged out of the" | | 14 | "He dropped the wet wool" | | 15 | "She reached for the buttons." | | 16 | "He went quiet." | | 17 | "Her knuckles brushed his chest" | | 18 | "She undid three buttons, then" | | 19 | "Her breath left her in" |
| | ratio | 0.406 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 93 | | totalSentences | 96 | | matches | | 0 | "The third deadbolt gave with" | | 1 | "Lucien Moreau stood in the" | | 2 | "His ivory-handled cane rested against" | | 3 | "Brick Lane traffic hissed on" | | 4 | "Rory kept one hand on" | | 5 | "Lucien lifted his chin, and" | | 6 | "She pushed the door." | | 7 | "He set the cane tip" | | 8 | "Rory stopped the door against" | | 9 | "Her gaze dropped to the" | | 10 | "Rory stared at him." | | 11 | "The tabby looked at Lucien," | | 12 | "Lucien smiled at the cat." | | 13 | "His smile thinned." | | 14 | "The stain had reached his" | | 15 | "A drop fell from his" | | 16 | "Rory unhooked the chain." | | 17 | "Lucien crossed the threshold and" | | 18 | "Books covered the sofa, the" | | 19 | "Scrolls leaned in the corner" |
| | ratio | 0.969 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 96 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 55 | | 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 | |