| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 8 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 94 | | tagDensity | 0.085 | | leniency | 0.17 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 2090 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 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) | |
| 73.68% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 2090 | | totalAiIsms | 11 | | found | | | highlights | | 0 | "flicked" | | 1 | "charm" | | 2 | "measured" | | 3 | "silence" | | 4 | "tension" | | 5 | "pulse" | | 6 | "fascinating" | | 7 | "fleeting" | | 8 | "fluttered" | | 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 | 2 | | narrationSentences | 150 | | matches | | 0 | "t with fear" | | 1 | "d with relief" |
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| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 150 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 236 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 50 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 2093 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 23 | | unquotedAttributions | 0 | | matches | (empty) | |
| 83.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 44 | | wordCount | 1416 | | uniqueNames | 10 | | maxNameDensity | 1.13 | | worstName | "Lucien" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Lucien" | | discoveredNames | | Aurora | 14 | | Ptolemy | 5 | | Moreau | 1 | | French | 1 | | Lucien | 16 | | Eva | 3 | | Bengali | 1 | | Latin | 1 | | Brick | 1 | | Lane | 1 |
| | persons | | 0 | "Aurora" | | 1 | "Ptolemy" | | 2 | "Moreau" | | 3 | "Lucien" | | 4 | "Eva" |
| | places | | 0 | "Bengali" | | 1 | "Brick" | | 2 | "Lane" |
| | globalScore | 0.935 | | windowScore | 0.833 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 87 | | glossingSentenceCount | 1 | | matches | | 0 | "as if anchoring himself against the cramped room" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.478 | | wordCount | 2093 | | matches | | 0 | "not from hospitality but because standing there gawping at him in the hall gave the n" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 4 | | totalSentences | 236 | | matches | | 0 | "let that sit" | | 1 | "hated that bruise" | | 2 | "Hated that he" | | 3 | "made that sound" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 170 | | mean | 12.31 | | std | 13.71 | | cv | 1.114 | | sampleLengths | | 0 | 22 | | 1 | 5 | | 2 | 65 | | 3 | 14 | | 4 | 4 | | 5 | 18 | | 6 | 7 | | 7 | 3 | | 8 | 24 | | 9 | 2 | | 10 | 7 | | 11 | 19 | | 12 | 7 | | 13 | 25 | | 14 | 14 | | 15 | 58 | | 16 | 13 | | 17 | 5 | | 18 | 3 | | 19 | 3 | | 20 | 3 | | 21 | 42 | | 22 | 3 | | 23 | 44 | | 24 | 2 | | 25 | 12 | | 26 | 4 | | 27 | 5 | | 28 | 22 | | 29 | 6 | | 30 | 36 | | 31 | 9 | | 32 | 6 | | 33 | 12 | | 34 | 5 | | 35 | 6 | | 36 | 52 | | 37 | 12 | | 38 | 14 | | 39 | 49 | | 40 | 11 | | 41 | 1 | | 42 | 3 | | 43 | 14 | | 44 | 7 | | 45 | 11 | | 46 | 1 | | 47 | 9 | | 48 | 47 | | 49 | 4 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 150 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 228 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 3 | | semicolonCount | 0 | | flaggedSentences | 2 | | totalSentences | 236 | | ratio | 0.008 | | matches | | 0 | "The corridor light caught in his strange eyes — amber in one socket, black in the other — and for one ugly second her body remembered him before her mind did." | | 1 | "Her reflection hovered there — blue eyes hard, shoulders squared, a woman who had long ago learned how to stand after men tried to fold her." |
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| 97.85% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1413 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 60 | | adverbRatio | 0.04246284501061571 | | lyAdverbCount | 10 | | lyAdverbRatio | 0.007077140835102618 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 236 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 236 | | mean | 8.87 | | std | 8.11 | | cv | 0.914 | | sampleLengths | | 0 | 22 | | 1 | 5 | | 2 | 34 | | 3 | 31 | | 4 | 1 | | 5 | 1 | | 6 | 5 | | 7 | 7 | | 8 | 4 | | 9 | 11 | | 10 | 2 | | 11 | 5 | | 12 | 7 | | 13 | 3 | | 14 | 24 | | 15 | 2 | | 16 | 7 | | 17 | 16 | | 18 | 3 | | 19 | 7 | | 20 | 25 | | 21 | 14 | | 22 | 34 | | 23 | 14 | | 24 | 10 | | 25 | 13 | | 26 | 5 | | 27 | 3 | | 28 | 3 | | 29 | 3 | | 30 | 4 | | 31 | 16 | | 32 | 18 | | 33 | 4 | | 34 | 3 | | 35 | 26 | | 36 | 8 | | 37 | 10 | | 38 | 2 | | 39 | 12 | | 40 | 4 | | 41 | 5 | | 42 | 22 | | 43 | 6 | | 44 | 26 | | 45 | 10 | | 46 | 9 | | 47 | 6 | | 48 | 5 | | 49 | 2 |
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| 50.14% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 5 | | diversityRatio | 0.3135593220338983 | | totalSentences | 236 | | uniqueOpeners | 74 | |
| 82.64% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 121 | | matches | | 0 | "Then the rest arrived." | | 1 | "Somewhere downstairs, a pan clanged" | | 2 | "Instead she dragged a hand" |
| | ratio | 0.025 | |
| 61.32% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 48 | | totalSentences | 121 | | matches | | 0 | "She yanked the door open." | | 1 | "She gripped the edge of" | | 2 | "His gaze flicked over her" | | 3 | "She shut the door harder" | | 4 | "He let that sit." | | 5 | "He took in the room:" | | 6 | "His eyes returned to her" | | 7 | "She moved past him into" | | 8 | "Her fingers wanted occupation." | | 9 | "She had nearly put a" | | 10 | "He looked less like a" | | 11 | "His mouth thinned." | | 12 | "She set the mug down" | | 13 | "He had always done that" | | 14 | "She laughed once, without humour." | | 15 | "His expression barely changed, but" | | 16 | "He moved toward the tiny" | | 17 | "He picked up a loose" | | 18 | "She stared at him." | | 19 | "He turned then, his voice" |
| | ratio | 0.397 | |
| 26.12% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 105 | | totalSentences | 121 | | matches | | 0 | "She yanked the door open." | | 1 | "Lucien Moreau filled the gap" | | 2 | "The corridor light caught in" | | 3 | "A mouth at her throat." | | 4 | "That low French murmur against" | | 5 | "The note he had left" | | 6 | "She gripped the edge of" | | 7 | "His gaze flicked over her" | | 8 | "Ptolemy wound round Lucien’s polished" | | 9 | "Lucien glanced down." | | 10 | "Aurora pushed the door wider," | | 11 | "Lucien stepped in with that" | | 12 | "Rain clung to his blond" | | 13 | "The sight of even that" | | 14 | "She shut the door harder" | | 15 | "He let that sit." | | 16 | "Ptolemy rose on his hind" | | 17 | "Lucien bent with a faint" | | 18 | "Ptolemy rumbled at once." | | 19 | "The flat smelled of old" |
| | ratio | 0.868 | |
| 41.32% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 121 | | matches | | 0 | "By the time Aurora slid" |
| | ratio | 0.008 | |
| 88.95% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 53 | | technicalSentenceCount | 4 | | matches | | 0 | "Lucien Moreau filled the gap in the frame as if he had always belonged there, one gloved hand resting on the ivory head of his cane, rain darkening the shoulder…" | | 1 | "Lucien stepped in with that infuriating grace of his, each movement measured, as though the cramped flat with its leaning towers of books and curling research n…" | | 2 | "Lucien rested his fingertips on the back of a chair, as if anchoring himself against the cramped room." | | 3 | "Her reflection hovered there — blue eyes hard, shoulders squared, a woman who had long ago learned how to stand after men tried to fold her." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 8 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 5 | | fancyCount | 1 | | fancyTags | | 0 | "Aurora muttered (mutter)" |
| | dialogueSentences | 94 | | tagDensity | 0.053 | | leniency | 0.106 | | rawRatio | 0.2 | | effectiveRatio | 0.021 | |