| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 15 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 44 | | tagDensity | 0.341 | | leniency | 0.682 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 88.44% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1298 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | 0 | "really" | | 1 | "very" | | 2 | "suddenly" |
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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) | |
| 53.78% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1298 | | totalAiIsms | 12 | | found | | | highlights | | 0 | "weight" | | 1 | "standard" | | 2 | "marble" | | 3 | "predator" | | 4 | "beacon" | | 5 | "eyebrow" | | 6 | "profound" | | 7 | "disrupt" | | 8 | "stomach" | | 9 | "familiar" |
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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 | 53 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 53 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 82 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 62 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1290 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 15 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 39 | | wordCount | 836 | | uniqueNames | 21 | | maxNameDensity | 0.96 | | worstName | "Lucien" | | maxWindowNameDensity | 2 | | worstWindowName | "Rory" | | discoveredNames | | Moreau | 1 | | Savile | 1 | | Row | 1 | | Rory | 7 | | Oxfords | 1 | | Cardiff | 2 | | Evan | 3 | | London | 2 | | Crown | 1 | | Court | 1 | | Yu-Fei | 1 | | Bentley | 1 | | Paddy | 1 | | Power | 1 | | Dust | 1 | | Marseille | 1 | | Aurora | 1 | | Eva | 2 | | Ptolemy | 1 | | Sumerian | 1 | | Lucien | 8 |
| | persons | | 0 | "Moreau" | | 1 | "Rory" | | 2 | "Evan" | | 3 | "Yu-Fei" | | 4 | "Dust" | | 5 | "Eva" | | 6 | "Lucien" |
| | places | | 0 | "Cardiff" | | 1 | "London" | | 2 | "Paddy" | | 3 | "Marseille" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 41 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.775 | | wordCount | 1290 | | matches | | 0 | "not touching her, but hovering near her wrist, near the small scar there, then low" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 82 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 42 | | mean | 30.71 | | std | 31.62 | | cv | 1.03 | | sampleLengths | | 0 | 21 | | 1 | 38 | | 2 | 6 | | 3 | 17 | | 4 | 7 | | 5 | 38 | | 6 | 72 | | 7 | 5 | | 8 | 105 | | 9 | 56 | | 10 | 4 | | 11 | 79 | | 12 | 14 | | 13 | 3 | | 14 | 5 | | 15 | 3 | | 16 | 83 | | 17 | 22 | | 18 | 6 | | 19 | 21 | | 20 | 4 | | 21 | 42 | | 22 | 4 | | 23 | 6 | | 24 | 4 | | 25 | 74 | | 26 | 29 | | 27 | 2 | | 28 | 3 | | 29 | 25 | | 30 | 1 | | 31 | 86 | | 32 | 62 | | 33 | 43 | | 34 | 81 | | 35 | 7 | | 36 | 94 | | 37 | 17 | | 38 | 1 | | 39 | 3 | | 40 | 79 | | 41 | 18 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 53 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 144 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 82 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 841 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 21 | | adverbRatio | 0.02497027348394768 | | lyAdverbCount | 3 | | lyAdverbRatio | 0.0035671819262782403 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 82 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 82 | | mean | 15.73 | | std | 13.71 | | cv | 0.872 | | sampleLengths | | 0 | 21 | | 1 | 4 | | 2 | 28 | | 3 | 6 | | 4 | 6 | | 5 | 13 | | 6 | 4 | | 7 | 7 | | 8 | 10 | | 9 | 23 | | 10 | 5 | | 11 | 26 | | 12 | 21 | | 13 | 25 | | 14 | 5 | | 15 | 7 | | 16 | 38 | | 17 | 18 | | 18 | 42 | | 19 | 3 | | 20 | 45 | | 21 | 8 | | 22 | 3 | | 23 | 1 | | 24 | 14 | | 25 | 19 | | 26 | 19 | | 27 | 27 | | 28 | 14 | | 29 | 3 | | 30 | 5 | | 31 | 3 | | 32 | 24 | | 33 | 22 | | 34 | 5 | | 35 | 12 | | 36 | 20 | | 37 | 12 | | 38 | 4 | | 39 | 6 | | 40 | 6 | | 41 | 21 | | 42 | 4 | | 43 | 19 | | 44 | 23 | | 45 | 4 | | 46 | 6 | | 47 | 4 | | 48 | 62 | | 49 | 12 |
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| 68.29% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 4 | | diversityRatio | 0.43902439024390244 | | totalSentences | 82 | | uniqueOpeners | 36 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 51 | | matches | (empty) | | ratio | 0 | |
| 31.76% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 24 | | totalSentences | 51 | | matches | | 0 | "She didn't move" | | 1 | "His platinum hair caught the" | | 2 | "She didn't step back, which" | | 3 | "He wore his suits like" | | 4 | "Her spine straightened." | | 5 | "She hadn't heard that name" | | 6 | "It sat between them like" | | 7 | "She turned, leaving him to" | | 8 | "He moved through her space" | | 9 | "he said, eyeing the cold" | | 10 | "He'd left his number scrawled" | | 11 | "She'd burned it in the" | | 12 | "he said, touching a stack" | | 13 | "He rubbed them together with" | | 14 | "He turned, and the amber" | | 15 | "He advanced, cane tapping, until" | | 16 | "He never called her Aurora." | | 17 | "Her hand found the edge" | | 18 | "She gripped the desk edge" | | 19 | "Her voice emerged steady, law-court" |
| | ratio | 0.471 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 50 | | totalSentences | 51 | | matches | | 0 | "The third deadbolt hadn't slid" | | 1 | "Rory twisted the handle." | | 2 | "Lucien Moreau filled her doorway" | | 3 | "Rory looked down at her" | | 4 | "She didn't move" | | 5 | "The scar on her left" | | 6 | "Lucien leaned his weight onto" | | 7 | "His platinum hair caught the" | | 8 | "Lucien stepped forward" | | 9 | "She didn't step back, which" | | 10 | "He wore his suits like" | | 11 | "Her spine straightened." | | 12 | "She hadn't heard that name" | | 13 | "It sat between them like" | | 14 | "She turned, leaving him to" | | 15 | "The space barely accommodated her" | | 16 | "Lucien closed the door behind" | | 17 | "He moved through her space" | | 18 | "he said, eyeing the cold" | | 19 | "The last time she'd watched" |
| | ratio | 0.98 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 51 | | matches | (empty) | | ratio | 0 | |
| 0.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 24 | | technicalSentenceCount | 6 | | matches | | 0 | "He wore his suits like armour, charcoal wool that cost more than three months of her delivery wages." | | 1 | "Lucien closed the door behind him, three deadbolts clicking into place with a sound that made her shoulders tense." | | 2 | "He moved through her space with the economy of a predator who knew exactly where the exits were, his cane tapping a slow rhythm against the floorboards." | | 3 | "The formality struck like a slap, reverting her to the girl she'd been in Cardiff, the barrister's daughter who'd believed in signatures and certainties." | | 4 | "Rory hit the floor, Lucien's body covering hers with crushing weight, his cane clattering against the wall." | | 5 | "A figure landed where they'd stood microseconds before, seven feet of scaled muscle and burning sulphur-yellow eyes, sulphur stinging Rory's nostrils as the dem…" |
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| 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 | 5 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 44 | | tagDensity | 0.114 | | leniency | 0.227 | | rawRatio | 0.2 | | effectiveRatio | 0.045 | |