| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | |
| 96.49% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1424 | | 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) | |
| 54.35% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1424 | | totalAiIsms | 13 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | word | "carried the weight" | | count | 1 |
| | 5 | | | 6 | | | 7 | | | 8 | |
| | highlights | | 0 | "familiar" | | 1 | "weight" | | 2 | "chaotic" | | 3 | "pulse" | | 4 | "carried the weight" | | 5 | "navigated" | | 6 | "eyebrow" | | 7 | "silence" | | 8 | "tension" |
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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 | 127 | | matches | (empty) | |
| 75.37% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 5 | | hedgeCount | 1 | | narrationSentences | 127 | | filterMatches | | 0 | "know" | | 1 | "look" | | 2 | "feel" | | 3 | "see" |
| | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 127 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 42 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1424 | | ratio | 0 | | matches | (empty) | |
| 0.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 7 | | unquotedAttributions | 6 | | matches | | 0 | "Come in, he said finally, the words quiet but leaving no room for refusal." | | 1 | "You do not have secrets you can keep from the people in your life anymore, he said, quieter now." | | 2 | "I handle problems, he corrected, stepping closer." | | 3 | "Then why come back, she whispered." | | 4 | "You are late, she said, her voice steady despite the tremor in her hands." | | 5 | "Sit down, she said." |
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| 33.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 49 | | wordCount | 1424 | | uniqueNames | 22 | | maxNameDensity | 0.98 | | worstName | "You" | | maxWindowNameDensity | 4 | | worstWindowName | "You" | | discoveredNames | | Aurora | 5 | | Moreau | 1 | | Brick | 1 | | Lane | 1 | | Marseille | 1 | | Yu-Fei | 1 | | Eva | 3 | | East | 1 | | London | 3 | | Golden | 1 | | Empress | 1 | | Tuesday | 1 | | Manchester | 1 | | Lucien | 4 | | Avaros | 2 | | Evan | 1 | | Cardiff | 1 | | Luc | 1 | | Avaros-bound | 1 | | Ptolemy | 3 | | Carter | 1 | | You | 14 |
| | persons | | 0 | "Aurora" | | 1 | "Moreau" | | 2 | "Yu-Fei" | | 3 | "Eva" | | 4 | "Lucien" | | 5 | "Avaros" | | 6 | "Evan" | | 7 | "Luc" | | 8 | "Avaros-bound" | | 9 | "Ptolemy" | | 10 | "Carter" | | 11 | "You" |
| | places | | 0 | "Brick" | | 1 | "Lane" | | 2 | "Marseille" | | 3 | "East" | | 4 | "London" | | 5 | "Manchester" | | 6 | "Cardiff" |
| | globalScore | 1 | | windowScore | 0.333 | |
| 95.65% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 92 | | glossingSentenceCount | 2 | | matches | | 0 | "as if remembering a boundary he had once ignored" | | 1 | "not quite reach the weight in his eyes" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.702 | | wordCount | 1424 | | matches | | 0 | "not touching her, but letting his knuckles hover near her shoulder as if rememberi" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 127 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 28 | | mean | 50.86 | | std | 37.01 | | cv | 0.728 | | sampleLengths | | 0 | 51 | | 1 | 109 | | 2 | 22 | | 3 | 15 | | 4 | 12 | | 5 | 4 | | 6 | 102 | | 7 | 120 | | 8 | 28 | | 9 | 57 | | 10 | 37 | | 11 | 5 | | 12 | 140 | | 13 | 37 | | 14 | 4 | | 15 | 61 | | 16 | 48 | | 17 | 53 | | 18 | 37 | | 19 | 118 | | 20 | 47 | | 21 | 82 | | 22 | 47 | | 23 | 14 | | 24 | 42 | | 25 | 48 | | 26 | 18 | | 27 | 66 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 127 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 255 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 127 | | ratio | 0 | | matches | (empty) | |
| 88.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1440 | | adjectiveStacks | 2 | | stackExamples | | 0 | "dim, grease-spotted hallway" | | 1 | "cramped, book-choked square" |
| | adverbCount | 56 | | adverbRatio | 0.03888888888888889 | | lyAdverbCount | 18 | | lyAdverbRatio | 0.0125 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 127 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 127 | | mean | 11.21 | | std | 8.41 | | cv | 0.75 | | sampleLengths | | 0 | 17 | | 1 | 34 | | 2 | 18 | | 3 | 30 | | 4 | 20 | | 5 | 4 | | 6 | 5 | | 7 | 32 | | 8 | 1 | | 9 | 21 | | 10 | 6 | | 11 | 9 | | 12 | 7 | | 13 | 5 | | 14 | 4 | | 15 | 6 | | 16 | 14 | | 17 | 9 | | 18 | 22 | | 19 | 18 | | 20 | 33 | | 21 | 10 | | 22 | 12 | | 23 | 6 | | 24 | 10 | | 25 | 8 | | 26 | 9 | | 27 | 24 | | 28 | 41 | | 29 | 14 | | 30 | 8 | | 31 | 6 | | 32 | 10 | | 33 | 31 | | 34 | 4 | | 35 | 7 | | 36 | 5 | | 37 | 5 | | 38 | 10 | | 39 | 16 | | 40 | 3 | | 41 | 3 | | 42 | 5 | | 43 | 2 | | 44 | 7 | | 45 | 23 | | 46 | 6 | | 47 | 6 | | 48 | 18 | | 49 | 6 |
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| 44.36% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 17 | | diversityRatio | 0.3464566929133858 | | totalSentences | 127 | | uniqueOpeners | 44 | |
| 82.64% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 121 | | matches | | 0 | "Then what are you." | | 1 | "Especially not when you are" | | 2 | "Then why come back, she" |
| | ratio | 0.025 | |
| 8.43% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 64 | | totalSentences | 121 | | matches | | 0 | "Her palm remained flat against" | | 1 | "He stood exactly as he" | | 2 | "His right hand rested on" | | 3 | "They pinned her to the" | | 4 | "His voice was a low" | | 5 | "She kept her face carefully" | | 6 | "You know I do not" | | 7 | "I am not Yu-Fei's courgettes." | | 8 | "He did not answer right" | | 9 | "He shifted his weight, and" | | 10 | "It was the most cramped," | | 11 | "She had spent eighteen months" | | 12 | "She had told herself the" | | 13 | "He had been a complication" | | 14 | "They had ended on a" | | 15 | "She stared at him over" | | 16 | "It was jumping now." | | 17 | "He tilted his head, those" | | 18 | "You look well." | | 19 | "You still wear your mind" |
| | ratio | 0.529 | |
| 75.70% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 93 | | totalSentences | 121 | | matches | | 0 | "The three deadbolts slid back" | | 1 | "Her palm remained flat against" | | 2 | "Lucien Moreau never looked out" | | 3 | "He stood exactly as he" | | 4 | "His right hand rested on" | | 5 | "They pinned her to the" | | 6 | "His voice was a low" | | 7 | "She kept her face carefully" | | 8 | "You know I do not" | | 9 | "A faint, disarming smile touched" | | 10 | "I am not Yu-Fei's courgettes." | | 11 | "He did not answer right" | | 12 | "He shifted his weight, and" | | 13 | "Ptolemy, Eva's tabby, trilled from" | | 14 | "The curry house downstairs sent" | | 15 | "It was the most cramped," | | 16 | "She had spent eighteen months" | | 17 | "Pre-law textbooks stacked on the" | | 18 | "The steady, quiet rhythm of" | | 19 | "She had told herself the" |
| | ratio | 0.769 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 5 | | totalSentences | 121 | | matches | | 0 | "Though I suspect you will" | | 1 | "Because the city got smaller." | | 2 | "Because you were right." | | 3 | "Because the underworld does not" | | 4 | "Before Ptolemy steals your cane," |
| | ratio | 0.041 | |
| 70.22% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 59 | | technicalSentenceCount | 6 | | matches | | 0 | "He stood exactly as he had in her memory: impossibly tall, broad-shouldered in a charcoal suit that swallowed the flickering fluorescent light, platinum blond h…" | | 1 | "It was the most cramped, book-choked square footage in East London, a fortress of half-finished research, translated scrolls, and three deadbolts that could not…" | | 2 | "A fixer who dealt in whispers and underground ledgers, moving through a world that left ash on his cuffs and secrets on his tongue." | | 3 | "They had ended on a Tuesday, sharp and cold, with him pressing a leather-bound address book into her palm and saying nothing that would have mattered, and her w…" | | 4 | "He reached out, not touching her, but letting his knuckles hover near her shoulder as if remembering a boundary he had once ignored." | | 5 | "And every name I verify, every ledger I burn, every alley I cut through in this city, I keep hearing your voice telling me I am overcomplicating it." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 0 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |