| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 15 | | adverbTagCount | 1 | | adverbTags | | 0 | "Rory stepped back [back]" |
| | dialogueSentences | 83 | | tagDensity | 0.181 | | leniency | 0.361 | | rawRatio | 0.067 | | effectiveRatio | 0.024 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1514 | | 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) | |
| 93.39% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1514 | | totalAiIsms | 2 | | found | | | highlights | | |
| 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 | 88 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 88 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 156 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 34 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1514 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 30 | | unquotedAttributions | 0 | | matches | (empty) | |
| 19.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 63 | | wordCount | 844 | | uniqueNames | 10 | | maxNameDensity | 2.61 | | worstName | "Rory" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Rory" | | discoveredNames | | Moreau | 1 | | Rory | 22 | | Ptolemy | 6 | | Eva | 7 | | Lucien | 17 | | Golden | 2 | | Empress | 2 | | Yu-Fei | 4 | | Clerkenwell | 1 | | Rainwater | 1 |
| | persons | | 0 | "Moreau" | | 1 | "Rory" | | 2 | "Ptolemy" | | 3 | "Eva" | | 4 | "Lucien" | | 5 | "Yu-Fei" | | 6 | "Rainwater" |
| | places | | | globalScore | 0.197 | | windowScore | 0.5 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 63 | | 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 | 1514 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 156 | | matches | | 0 | "mistaken that composure" |
| |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 97 | | mean | 15.61 | | std | 13.95 | | cv | 0.893 | | sampleLengths | | 0 | 44 | | 1 | 10 | | 2 | 4 | | 3 | 11 | | 4 | 4 | | 5 | 6 | | 6 | 28 | | 7 | 17 | | 8 | 34 | | 9 | 5 | | 10 | 18 | | 11 | 57 | | 12 | 16 | | 13 | 18 | | 14 | 12 | | 15 | 5 | | 16 | 2 | | 17 | 33 | | 18 | 31 | | 19 | 17 | | 20 | 2 | | 21 | 20 | | 22 | 19 | | 23 | 16 | | 24 | 1 | | 25 | 5 | | 26 | 1 | | 27 | 23 | | 28 | 32 | | 29 | 48 | | 30 | 7 | | 31 | 9 | | 32 | 3 | | 33 | 2 | | 34 | 6 | | 35 | 15 | | 36 | 48 | | 37 | 10 | | 38 | 2 | | 39 | 26 | | 40 | 21 | | 41 | 4 | | 42 | 12 | | 43 | 14 | | 44 | 24 | | 45 | 24 | | 46 | 9 | | 47 | 11 | | 48 | 34 | | 49 | 13 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 88 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 149 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 1 | | flaggedSentences | 1 | | totalSentences | 156 | | ratio | 0.006 | | matches | | 0 | "His amber eye caught the light from Eva’s hall; the black one gave nothing back." |
| |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 849 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 16 | | adverbRatio | 0.01884570082449941 | | lyAdverbCount | 0 | | lyAdverbRatio | 0 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 156 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 156 | | mean | 9.71 | | std | 6.32 | | cv | 0.651 | | sampleLengths | | 0 | 9 | | 1 | 20 | | 2 | 15 | | 3 | 10 | | 4 | 4 | | 5 | 11 | | 6 | 4 | | 7 | 6 | | 8 | 17 | | 9 | 11 | | 10 | 10 | | 11 | 7 | | 12 | 4 | | 13 | 22 | | 14 | 8 | | 15 | 5 | | 16 | 18 | | 17 | 7 | | 18 | 8 | | 19 | 14 | | 20 | 16 | | 21 | 12 | | 22 | 5 | | 23 | 11 | | 24 | 9 | | 25 | 4 | | 26 | 5 | | 27 | 7 | | 28 | 5 | | 29 | 5 | | 30 | 2 | | 31 | 6 | | 32 | 11 | | 33 | 16 | | 34 | 14 | | 35 | 17 | | 36 | 5 | | 37 | 12 | | 38 | 2 | | 39 | 20 | | 40 | 8 | | 41 | 11 | | 42 | 16 | | 43 | 1 | | 44 | 5 | | 45 | 1 | | 46 | 15 | | 47 | 8 | | 48 | 32 | | 49 | 5 |
| |
| 46.15% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 6 | | diversityRatio | 0.2948717948717949 | | totalSentences | 156 | | uniqueOpeners | 46 | |
| 38.31% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 87 | | matches | | 0 | "Instead, she reached into the" |
| | ratio | 0.011 | |
| 59.08% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 35 | | totalSentences | 87 | | matches | | 0 | "He held a paper bag" | | 1 | "he told her" | | 2 | "He raised the bag." | | 3 | "She had last seen it" | | 4 | "He had kissed her there," | | 5 | "He had told Yu-Fei she" | | 6 | "She took the bag." | | 7 | "she told him" | | 8 | "She should have shut the" | | 9 | "he told her" | | 10 | "It contained a name, an" | | 11 | "She held up the paper" | | 12 | "His amber eye caught the" | | 13 | "She glanced at Lucien’s mouth" | | 14 | "She unfolded the paper." | | 15 | "she told him" | | 16 | "She bent to pick him" | | 17 | "she told Lucien" | | 18 | "His gaze dropped to her" | | 19 | "His hand moved on the" |
| | ratio | 0.402 | |
| 0.23% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 80 | | totalSentences | 87 | | matches | | 0 | "The door opened as far" | | 1 | "Lucien Moreau stood on the" | | 2 | "He held a paper bag" | | 3 | "Rory kept her fingers on" | | 4 | "Lucien glanced past her, but" | | 5 | "he told her" | | 6 | "He raised the bag." | | 7 | "A corner of dark blue" | | 8 | "She had last seen it" | | 9 | "Ptolemy hooked a page beneath" | | 10 | "Rory watched Lucien’s fingers tighten" | | 11 | "A week ago, those fingers" | | 12 | "He had kissed her there," | | 13 | "Lucien had asked for it." | | 14 | "He had told Yu-Fei she" | | 15 | "Rory slid the chain free" | | 16 | "She took the bag." | | 17 | "Lucien stayed where he was." | | 18 | "she told him" | | 19 | "She should have shut the" |
| | ratio | 0.92 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 87 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 40 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 15 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 10 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 83 | | tagDensity | 0.12 | | leniency | 0.241 | | rawRatio | 0.1 | | effectiveRatio | 0.024 | |