| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 8 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 139 | | tagDensity | 0.058 | | leniency | 0.115 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 97.75% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 2226 | | 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) | |
| 86.52% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 2226 | | totalAiIsms | 6 | | found | | | highlights | | 0 | "traced" | | 1 | "silence" | | 2 | "weight" | | 3 | "perfect" | | 4 | "familiar" | | 5 | "pulse" |
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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 | 157 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 157 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 289 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 39 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 2226 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 15 | | unquotedAttributions | 0 | | matches | (empty) | |
| 31.23% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 75 | | wordCount | 1305 | | uniqueNames | 10 | | maxNameDensity | 2.38 | | worstName | "Aurora" | | maxWindowNameDensity | 4 | | worstWindowName | "Aurora" | | discoveredNames | | Moreau | 1 | | Aurora | 31 | | Lucien | 28 | | Eva | 2 | | July | 1 | | Nice | 1 | | Mesopotamian | 1 | | Marseille | 1 | | Blood | 4 | | Ptolemy | 5 |
| | persons | | 0 | "Moreau" | | 1 | "Aurora" | | 2 | "Lucien" | | 3 | "Eva" | | 4 | "Blood" | | 5 | "Ptolemy" |
| | places | | 0 | "July" | | 1 | "Nice" | | 2 | "Marseille" |
| | globalScore | 0.312 | | windowScore | 0.333 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 111 | | glossingSentenceCount | 1 | | matches | | 0 | "looked like a man reading the weather" |
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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 | 2226 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 3 | | totalSentences | 289 | | matches | | 0 | "hated that sight" | | 1 | "hated that she" | | 2 | "remembered that scent" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 228 | | mean | 9.76 | | std | 10.56 | | cv | 1.082 | | sampleLengths | | 0 | 9 | | 1 | 13 | | 2 | 55 | | 3 | 4 | | 4 | 14 | | 5 | 2 | | 6 | 13 | | 7 | 8 | | 8 | 9 | | 9 | 5 | | 10 | 4 | | 11 | 3 | | 12 | 18 | | 13 | 56 | | 14 | 8 | | 15 | 9 | | 16 | 3 | | 17 | 7 | | 18 | 6 | | 19 | 1 | | 20 | 45 | | 21 | 6 | | 22 | 6 | | 23 | 2 | | 24 | 3 | | 25 | 8 | | 26 | 7 | | 27 | 16 | | 28 | 43 | | 29 | 17 | | 30 | 6 | | 31 | 3 | | 32 | 9 | | 33 | 1 | | 34 | 55 | | 35 | 6 | | 36 | 1 | | 37 | 1 | | 38 | 4 | | 39 | 30 | | 40 | 6 | | 41 | 1 | | 42 | 13 | | 43 | 9 | | 44 | 7 | | 45 | 7 | | 46 | 9 | | 47 | 27 | | 48 | 10 | | 49 | 23 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 157 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 220 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 289 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1264 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 26 | | adverbRatio | 0.020569620253164556 | | lyAdverbCount | 3 | | lyAdverbRatio | 0.0023734177215189874 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 289 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 289 | | mean | 7.7 | | std | 5.71 | | cv | 0.742 | | sampleLengths | | 0 | 9 | | 1 | 13 | | 2 | 14 | | 3 | 8 | | 4 | 14 | | 5 | 19 | | 6 | 4 | | 7 | 14 | | 8 | 2 | | 9 | 5 | | 10 | 8 | | 11 | 8 | | 12 | 9 | | 13 | 5 | | 14 | 4 | | 15 | 3 | | 16 | 10 | | 17 | 8 | | 18 | 19 | | 19 | 7 | | 20 | 5 | | 21 | 25 | | 22 | 8 | | 23 | 9 | | 24 | 3 | | 25 | 7 | | 26 | 6 | | 27 | 1 | | 28 | 8 | | 29 | 11 | | 30 | 9 | | 31 | 17 | | 32 | 6 | | 33 | 6 | | 34 | 2 | | 35 | 3 | | 36 | 8 | | 37 | 3 | | 38 | 4 | | 39 | 16 | | 40 | 20 | | 41 | 10 | | 42 | 8 | | 43 | 5 | | 44 | 4 | | 45 | 13 | | 46 | 6 | | 47 | 3 | | 48 | 9 | | 49 | 1 |
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| 47.23% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 8 | | diversityRatio | 0.21453287197231835 | | totalSentences | 289 | | uniqueOpeners | 62 | |
| 23.31% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 143 | | matches | | 0 | "Then, the next morning, he" |
| | ratio | 0.007 | |
| 91.33% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 46 | | totalSentences | 143 | | matches | | 0 | "His platinum hair had escaped" | | 1 | "He held his ivory-handled cane" | | 2 | "He gave the door a" | | 3 | "It struck Aurora then that" | | 4 | "He also wore gloves in" | | 5 | "He had come in a" | | 6 | "His mouth tightened." | | 7 | "His other eye held no" | | 8 | "She hated that she still" | | 9 | "He had told her a" | | 10 | "His gloved hand slipped from" | | 11 | "He never looked pleased when" | | 12 | "He looked like a man" | | 13 | "She opened the door wide" | | 14 | "He stepped inside." | | 15 | "His cane tapped once against" | | 16 | "He stood straight out of" | | 17 | "She caught his elbow and" | | 18 | "His sleeve felt cold and" | | 19 | "His body leaned into hers" |
| | ratio | 0.322 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 134 | | totalSentences | 143 | | matches | | 0 | "The first deadbolt came free" | | 1 | "Aurora kept her hand on" | | 2 | "Lucien Moreau filled the warped" | | 3 | "Rain had darkened the shoulders" | | 4 | "His platinum hair had escaped" | | 5 | "He held his ivory-handled cane" | | 6 | "Blood marked the glove." | | 7 | "Ptolemy launched himself from the" | | 8 | "The cat’s tail puffed out." | | 9 | "He gave the door a" | | 10 | "Aurora drew the chain across." | | 11 | "The words landed harder than" | | 12 | "Aurora kept her fingers around" | | 13 | "Books lay open across the" | | 14 | "Scrolls slumped from the armchair." | | 15 | "A chalk circle covered half" | | 16 | "Lucien looked through the gap" | | 17 | "Rain threaded down the front" | | 18 | "It struck Aurora then that" | | 19 | "Lucien carried umbrellas in weather" |
| | ratio | 0.937 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 143 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 48 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 62.50% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 8 | | uselessAdditionCount | 1 | | matches | | 0 | "She remembered, London glittering below them in puddles of gold and white" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 7 | | fancyCount | 2 | | fancyTags | | 0 | "Aurora ordered (order)" | | 1 | "he murmured (murmur)" |
| | dialogueSentences | 139 | | tagDensity | 0.05 | | leniency | 0.101 | | rawRatio | 0.286 | | effectiveRatio | 0.029 | |