| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 34 | | adverbTagCount | 2 | | adverbTags | | 0 | "he said softly [softly]" | | 1 | "he said lightly [lightly]" |
| | dialogueSentences | 62 | | tagDensity | 0.548 | | leniency | 1 | | rawRatio | 0.059 | | effectiveRatio | 0.059 | |
| 69.61% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1810 | | totalAiIsmAdverbs | 11 | | found | | | highlights | | 0 | "very" | | 1 | "perfectly" | | 2 | "completely" | | 3 | "softly" | | 4 | "lightly" | | 5 | "precisely" | | 6 | "carefully" |
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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) | |
| 83.43% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1810 | | totalAiIsms | 6 | | found | | | highlights | | 0 | "weight" | | 1 | "stomach" | | 2 | "perfect" | | 3 | "absolutely" | | 4 | "familiar" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "stomach dropped/sank" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 128 | | matches | (empty) | |
| 64.73% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 6 | | narrationSentences | 128 | | filterMatches | | | hedgeMatches | | 0 | "started to" | | 1 | "tried to" | | 2 | "seemed to" | | 3 | "try to" |
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| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 151 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 57 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1819 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 34 | | unquotedAttributions | 0 | | matches | (empty) | |
| 83.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 43 | | wordCount | 1412 | | uniqueNames | 18 | | maxNameDensity | 0.42 | | worstName | "Eva" | | maxWindowNameDensity | 2.5 | | worstWindowName | "You" | | discoveredNames | | Eva | 6 | | Rory | 6 | | Ptolemy | 5 | | Sumerian | 2 | | Moreau | 1 | | French | 1 | | Clerkenwell | 1 | | Aurora | 2 | | Lucien | 5 | | Corrected | 1 | | London | 1 | | Cardiff | 1 | | Evan | 1 | | Marseille | 1 | | Avaros | 1 | | You | 6 | | Carter | 1 | | Laila | 1 |
| | persons | | 0 | "Eva" | | 1 | "Rory" | | 2 | "Ptolemy" | | 3 | "Moreau" | | 4 | "Aurora" | | 5 | "Lucien" | | 6 | "Evan" | | 7 | "You" | | 8 | "Carter" | | 9 | "Laila" |
| | places | | 0 | "Sumerian" | | 1 | "Clerkenwell" | | 2 | "London" | | 3 | "Cardiff" | | 4 | "Marseille" | | 5 | "Avaros" |
| | globalScore | 1 | | windowScore | 0.833 | |
| 28.05% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 82 | | glossingSentenceCount | 4 | | matches | | 0 | "smelled like turmeric and damp from the cu" | | 1 | "smelled like rain and expensive cologne, e" | | 2 | "smelled like old paper and rain on wool an" | | 3 | "tasted like he'd been waiting three month" |
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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 | 1819 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 151 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 73 | | mean | 24.92 | | std | 20.73 | | cv | 0.832 | | sampleLengths | | 0 | 5 | | 1 | 70 | | 2 | 13 | | 3 | 110 | | 4 | 7 | | 5 | 20 | | 6 | 79 | | 7 | 28 | | 8 | 8 | | 9 | 18 | | 10 | 50 | | 11 | 28 | | 12 | 14 | | 13 | 36 | | 14 | 25 | | 15 | 13 | | 16 | 17 | | 17 | 75 | | 18 | 17 | | 19 | 18 | | 20 | 3 | | 21 | 75 | | 22 | 10 | | 23 | 12 | | 24 | 18 | | 25 | 44 | | 26 | 45 | | 27 | 34 | | 28 | 3 | | 29 | 12 | | 30 | 37 | | 31 | 15 | | 32 | 17 | | 33 | 50 | | 34 | 29 | | 35 | 11 | | 36 | 16 | | 37 | 40 | | 38 | 1 | | 39 | 1 | | 40 | 2 | | 41 | 36 | | 42 | 17 | | 43 | 6 | | 44 | 23 | | 45 | 24 | | 46 | 20 | | 47 | 36 | | 48 | 4 | | 49 | 55 |
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| 94.30% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 4 | | totalSentences | 128 | | matches | | 0 | "been camped" | | 1 | "was busted" | | 2 | "was slicked" | | 3 | "was cramped" |
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| 74.21% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 5 | | totalVerbs | 265 | | matches | | 0 | "was knocking" | | 1 | "was giving" | | 2 | "was giving" | | 3 | "were protecting" | | 4 | "was hammering" |
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| 48.25% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 9 | | semicolonCount | 0 | | flaggedSentences | 5 | | totalSentences | 151 | | ratio | 0.033 | | matches | | 0 | "She'd left Rory with a key and a list — water the spider plant, feed Ptolemy, don't touch the scrolls on the kitchen table because some of them bite — and the strict instruction not to open the door for anyone after nine." | | 1 | "His eyes — eyes — dropped to the doorway, the barricade of research notes behind her." | | 2 | "He entered in that fluid, economical way he had, cane barely touching the floor — more affectation than necessity most days, unless his father's blood was giving him trouble." | | 3 | "Lucien's hand came up — hesitated — then settled, barely, on her elbow. His fingers were warm. Always warmer than a human's should be." | | 4 | "You are — you were — you are extraordinary, Aurora Carter, and you were in a room full of things that eat extraordinary girls alive." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 701 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 23 | | adverbRatio | 0.03281027104136947 | | lyAdverbCount | 3 | | lyAdverbRatio | 0.0042796005706134095 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 151 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 151 | | mean | 12.05 | | std | 9.97 | | cv | 0.827 | | sampleLengths | | 0 | 5 | | 1 | 16 | | 2 | 16 | | 3 | 30 | | 4 | 6 | | 5 | 1 | | 6 | 1 | | 7 | 13 | | 8 | 8 | | 9 | 43 | | 10 | 5 | | 11 | 54 | | 12 | 7 | | 13 | 12 | | 14 | 8 | | 15 | 30 | | 16 | 10 | | 17 | 21 | | 18 | 13 | | 19 | 5 | | 20 | 28 | | 21 | 7 | | 22 | 1 | | 23 | 2 | | 24 | 16 | | 25 | 7 | | 26 | 9 | | 27 | 7 | | 28 | 2 | | 29 | 25 | | 30 | 8 | | 31 | 16 | | 32 | 4 | | 33 | 14 | | 34 | 16 | | 35 | 20 | | 36 | 25 | | 37 | 3 | | 38 | 10 | | 39 | 9 | | 40 | 4 | | 41 | 4 | | 42 | 26 | | 43 | 15 | | 44 | 2 | | 45 | 2 | | 46 | 11 | | 47 | 6 | | 48 | 13 | | 49 | 17 |
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| 57.40% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 10 | | diversityRatio | 0.3841059602649007 | | totalSentences | 151 | | uniqueOpeners | 58 | |
| 31.15% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 107 | | matches | | 0 | "Just, I think it's better" |
| | ratio | 0.009 | |
| 36.82% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 49 | | totalSentences | 107 | | matches | | 0 | "she called, and it came" | | 1 | "She'd left Rory with a" | | 2 | "It was ten past ten." | | 3 | "She threw the last deadbolt" | | 4 | "He wore a tailored charcoal" | | 5 | "His platinum blond hair was" | | 6 | "He looked at her bare" | | 7 | "he said softly, and then" | | 8 | "Her voice sounded tight even" | | 9 | "His eyes — eyes —" | | 10 | "He shifted his weight, and" | | 11 | "Her full name, like a" | | 12 | "She wanted to slam the" | | 13 | "She wanted to grab the" | | 14 | "She stepped back." | | 15 | "He entered in that fluid," | | 16 | "He took in the flat" | | 17 | "he said, without looking at" | | 18 | "he said lightly" | | 19 | "He set his cane against" |
| | ratio | 0.458 | |
| 67.48% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 84 | | totalSentences | 107 | | matches | | 0 | "The third deadbolt stuck again." | | 1 | "Rory jiggled it with her" | | 2 | "The crescent-shaped scar on the" | | 3 | "she called, and it came" | | 4 | "Eva wasn't supposed to be" | | 5 | "She'd left Rory with a" | | 6 | "It was ten past ten." | | 7 | "The tabby was asleep on" | | 8 | "She threw the last deadbolt" | | 9 | "The hallway light was busted," | | 10 | "Lucien Moreau stood on Eva's" | | 11 | "That he, specifically, was never" | | 12 | "He wore a tailored charcoal" | | 13 | "His platinum blond hair was" | | 14 | "He looked at her bare" | | 15 | "he said softly, and then" | | 16 | "Her voice sounded tight even" | | 17 | "His eyes — eyes —" | | 18 | "He shifted his weight, and" | | 19 | "The blade concealed inside that" |
| | ratio | 0.785 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 3 | | totalSentences | 107 | | matches | | 0 | "As if it had been" | | 1 | "If she's gone to get" | | 2 | "Because she thinks she's" |
| | ratio | 0.028 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 46 | | technicalSentenceCount | 2 | | matches | | 0 | "You are — you were — you are extraordinary, Aurora Carter, and you were in a room full of things that eat extraordinary girls alive." | | 1 | "You need someone who can talk Eva down when she's in full research spiral." |
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| 73.28% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 29 | | uselessAdditionCount | 3 | | matches | | 0 | "he said, without looking at her" | | 1 | "he said, low" | | 2 | "she said, breathless," |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 17 | | fancyCount | 3 | | fancyTags | | 0 | "he repeated (repeat)" | | 1 | "she whispered (whisper)" | | 2 | "he promised (promise)" |
| | dialogueSentences | 62 | | tagDensity | 0.274 | | leniency | 0.548 | | rawRatio | 0.176 | | effectiveRatio | 0.097 | |