| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 4 | | adverbTagCount | 1 | | adverbTags | | 0 | "She turned away [away]" |
| | dialogueSentences | 67 | | tagDensity | 0.06 | | leniency | 0.119 | | rawRatio | 0.25 | | effectiveRatio | 0.03 | |
| 87.71% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1221 | | totalAiIsmAdverbs | 3 | | 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) | |
| 71.33% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1221 | | totalAiIsms | 7 | | found | | | highlights | | 0 | "silence" | | 1 | "weight" | | 2 | "flickered" | | 3 | "pristine" | | 4 | "pulse" | | 5 | "unreadable" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 104 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 104 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 167 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 34 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1221 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 14 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 23 | | wordCount | 866 | | uniqueNames | 8 | | maxNameDensity | 0.92 | | worstName | "Rory" | | maxWindowNameDensity | 2 | | worstWindowName | "Lucien" | | discoveredNames | | Eva | 2 | | Silas | 1 | | Moreau | 1 | | London | 1 | | Lucien | 7 | | White | 1 | | Rory | 8 | | Needed | 2 |
| | persons | | 0 | "Eva" | | 1 | "Silas" | | 2 | "Moreau" | | 3 | "Lucien" | | 4 | "Rory" |
| | places | | | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 63 | | glossingSentenceCount | 1 | | matches | | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.819 | | wordCount | 1221 | | matches | | 0 | "not with his body, which was lean bordering on sharp, but with something else" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 2 | | totalSentences | 167 | | matches | | 0 | "had that effect" | | 1 | "knew that, she" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 93 | | mean | 13.13 | | std | 13.25 | | cv | 1.009 | | sampleLengths | | 0 | 18 | | 1 | 41 | | 2 | 7 | | 3 | 31 | | 4 | 30 | | 5 | 3 | | 6 | 7 | | 7 | 4 | | 8 | 1 | | 9 | 43 | | 10 | 2 | | 11 | 2 | | 12 | 4 | | 13 | 15 | | 14 | 35 | | 15 | 5 | | 16 | 13 | | 17 | 29 | | 18 | 5 | | 19 | 2 | | 20 | 1 | | 21 | 47 | | 22 | 16 | | 23 | 4 | | 24 | 8 | | 25 | 2 | | 26 | 4 | | 27 | 50 | | 28 | 36 | | 29 | 13 | | 30 | 2 | | 31 | 28 | | 32 | 6 | | 33 | 2 | | 34 | 1 | | 35 | 23 | | 36 | 2 | | 37 | 25 | | 38 | 3 | | 39 | 8 | | 40 | 24 | | 41 | 42 | | 42 | 3 | | 43 | 7 | | 44 | 2 | | 45 | 3 | | 46 | 37 | | 47 | 24 | | 48 | 15 | | 49 | 2 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 104 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 146 | | matches | | 0 | "was feeling" | | 1 | "was standing" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 167 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 871 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 33 | | adverbRatio | 0.03788748564867968 | | lyAdverbCount | 10 | | lyAdverbRatio | 0.011481056257175661 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 167 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 167 | | mean | 7.31 | | std | 6.11 | | cv | 0.835 | | sampleLengths | | 0 | 5 | | 1 | 1 | | 2 | 1 | | 3 | 11 | | 4 | 6 | | 5 | 9 | | 6 | 26 | | 7 | 7 | | 8 | 22 | | 9 | 9 | | 10 | 13 | | 11 | 17 | | 12 | 3 | | 13 | 7 | | 14 | 4 | | 15 | 1 | | 16 | 12 | | 17 | 18 | | 18 | 13 | | 19 | 2 | | 20 | 2 | | 21 | 4 | | 22 | 7 | | 23 | 8 | | 24 | 9 | | 25 | 26 | | 26 | 5 | | 27 | 13 | | 28 | 6 | | 29 | 4 | | 30 | 10 | | 31 | 6 | | 32 | 3 | | 33 | 5 | | 34 | 2 | | 35 | 1 | | 36 | 3 | | 37 | 7 | | 38 | 6 | | 39 | 17 | | 40 | 1 | | 41 | 1 | | 42 | 12 | | 43 | 14 | | 44 | 2 | | 45 | 4 | | 46 | 8 | | 47 | 2 | | 48 | 4 | | 49 | 24 |
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| 74.45% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 4 | | diversityRatio | 0.46107784431137727 | | totalSentences | 167 | | uniqueOpeners | 77 | |
| 37.88% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 88 | | matches | | | ratio | 0.011 | |
| 97.27% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 27 | | totalSentences | 88 | | matches | | 0 | "She crossed the tiny flat" | | 1 | "His heterochromatic eyes, one amber" | | 2 | "He leaned against the doorframe," | | 3 | "His mouth curved, not quite" | | 4 | "She stepped aside." | | 5 | "He entered, and the flat" | | 6 | "He filled rooms not with" | | 7 | "He set his cane against" | | 8 | "She watched him examine her" | | 9 | "His hand went to his" | | 10 | "His given name, which she'd" | | 11 | "She couldn't tell with him," | | 12 | "His fingers moved to his" | | 13 | "She knelt between his spread" | | 14 | "His gaze dropped to it," | | 15 | "She didn't apologise for the" | | 16 | "He didn't flinch." | | 17 | "He pressed his hand over" | | 18 | "His jaw tightened." | | 19 | "She'd seen him in worse" |
| | ratio | 0.307 | |
| 62.27% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 70 | | totalSentences | 88 | | matches | | 0 | "The knock came three times." | | 1 | "The kind that didn't ask" | | 2 | "Rory's hand froze on the" | | 3 | "The second round of knocking" | | 4 | "She crossed the tiny flat" | | 5 | "The door swung wide, umbrella" | | 6 | "Lucien Moreau stood in the" | | 7 | "His heterochromatic eyes, one amber" | | 8 | "He leaned against the doorframe," | | 9 | "The charcoal suit was immaculate" | | 10 | "A bruise darkened his jawline," | | 11 | "His mouth curved, not quite" | | 12 | "The use of her surname" | | 13 | "Rory glanced back at her" | | 14 | "Dishes in the sink." | | 15 | "Ptolemy, Eva's cat she'd been" | | 16 | "Research papers spread across every" | | 17 | "Nothing worth hiding." | | 18 | "Nothing worth showing him, either." | | 19 | "She stepped aside." |
| | ratio | 0.795 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 88 | | matches | (empty) | | ratio | 0 | |
| 96.77% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 31 | | technicalSentenceCount | 2 | | matches | | 0 | "Three months of silence, and he stood there acting like they were colleagues, like he hadn't vanished without a word after everything that happened between them…" | | 1 | "He filled rooms not with his body, which was lean bordering on sharp, but with something else." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 4 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 1 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 67 | | tagDensity | 0.015 | | leniency | 0.03 | | rawRatio | 0 | | effectiveRatio | 0 | |