| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 15 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 48 | | tagDensity | 0.313 | | leniency | 0.625 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 95.58% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1130 | | 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) | |
| 69.03% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1130 | | totalAiIsms | 7 | | found | | | highlights | | 0 | "glinting" | | 1 | "navigated" | | 2 | "charm" | | 3 | "stomach" | | 4 | "silence" | | 5 | "warmth" | | 6 | "unreadable" |
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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 | 68 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 68 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 101 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 50 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1130 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 15 | | unquotedAttributions | 1 | | matches | | 0 | "Defensive, she guessed, the kind you got grabbing for a blade instead of away from it." |
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| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 13 | | wordCount | 721 | | uniqueNames | 7 | | maxNameDensity | 0.69 | | worstName | "Lucien" | | maxWindowNameDensity | 1 | | worstWindowName | "Lucien" | | discoveredNames | | Ptolemy | 2 | | Copper | 1 | | Evan | 1 | | Cardiff | 2 | | Eva | 1 | | London | 1 | | Lucien | 5 |
| | persons | | 0 | "Ptolemy" | | 1 | "Evan" | | 2 | "Eva" | | 3 | "Lucien" |
| | places | | | 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 | 0 | | per1kWords | 0 | | wordCount | 1130 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 101 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 56 | | mean | 20.18 | | std | 17.29 | | cv | 0.857 | | sampleLengths | | 0 | 27 | | 1 | 6 | | 2 | 56 | | 3 | 3 | | 4 | 5 | | 5 | 56 | | 6 | 7 | | 7 | 5 | | 8 | 17 | | 9 | 30 | | 10 | 33 | | 11 | 2 | | 12 | 2 | | 13 | 5 | | 14 | 34 | | 15 | 48 | | 16 | 4 | | 17 | 49 | | 18 | 18 | | 19 | 49 | | 20 | 6 | | 21 | 7 | | 22 | 36 | | 23 | 3 | | 24 | 9 | | 25 | 11 | | 26 | 6 | | 27 | 5 | | 28 | 39 | | 29 | 27 | | 30 | 1 | | 31 | 36 | | 32 | 10 | | 33 | 1 | | 34 | 28 | | 35 | 36 | | 36 | 9 | | 37 | 4 | | 38 | 21 | | 39 | 13 | | 40 | 42 | | 41 | 7 | | 42 | 7 | | 43 | 36 | | 44 | 28 | | 45 | 12 | | 46 | 30 | | 47 | 50 | | 48 | 11 | | 49 | 2 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 68 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 119 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 101 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 727 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 27 | | adverbRatio | 0.037138927097661624 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.0068775790921595595 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 101 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 101 | | mean | 11.19 | | std | 9.82 | | cv | 0.878 | | sampleLengths | | 0 | 7 | | 1 | 3 | | 2 | 17 | | 3 | 6 | | 4 | 33 | | 5 | 23 | | 6 | 3 | | 7 | 5 | | 8 | 10 | | 9 | 18 | | 10 | 28 | | 11 | 7 | | 12 | 5 | | 13 | 12 | | 14 | 5 | | 15 | 19 | | 16 | 11 | | 17 | 1 | | 18 | 8 | | 19 | 4 | | 20 | 20 | | 21 | 2 | | 22 | 2 | | 23 | 5 | | 24 | 30 | | 25 | 2 | | 26 | 2 | | 27 | 5 | | 28 | 43 | | 29 | 4 | | 30 | 15 | | 31 | 8 | | 32 | 23 | | 33 | 3 | | 34 | 3 | | 35 | 15 | | 36 | 6 | | 37 | 15 | | 38 | 28 | | 39 | 6 | | 40 | 7 | | 41 | 4 | | 42 | 16 | | 43 | 10 | | 44 | 3 | | 45 | 3 | | 46 | 3 | | 47 | 9 | | 48 | 3 | | 49 | 8 |
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| 65.02% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 6 | | diversityRatio | 0.42574257425742573 | | totalSentences | 101 | | uniqueOpeners | 43 | |
| 54.64% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 61 | | matches | | 0 | "Instead she stepped aside." |
| | ratio | 0.016 | |
| 16.72% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 31 | | totalSentences | 61 | | matches | | 0 | "His mismatched eyes caught what" | | 1 | "She kept her hand on" | | 2 | "He tilted his head, studying" | | 3 | "She caught it now, faint" | | 4 | "Her gaze dropped to his" | | 5 | "He glanced down the corridor," | | 6 | "She should have said no." | | 7 | "He probably had." | | 8 | "He lowered himself into the" | | 9 | "She fetched the first-aid tin" | | 10 | "She took his hand anyway" | | 11 | "She pressed a damp cloth" | | 12 | "He didn't flinch." | | 13 | "He never did." | | 14 | "Her hands stilled." | | 15 | "His good eye fixed on" | | 16 | "She thought of Cardiff." | | 17 | "Her stomach knotted." | | 18 | "He turned his hand in" | | 19 | "He only used it when" |
| | ratio | 0.508 | |
| 33.77% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 52 | | totalSentences | 61 | | matches | | 0 | "The deadbolts slid back one" | | 1 | "Aurora counted the metallic clicks" | | 2 | "Lucien stood in the dim" | | 3 | "His mismatched eyes caught what" | | 4 | "She kept her hand on" | | 5 | "The words came out sharper" | | 6 | "He tilted his head, studying" | | 7 | "She caught it now, faint" | | 8 | "Blood, dried, recent enough." | | 9 | "Her gaze dropped to his" | | 10 | "He glanced down the corridor," | | 11 | "She should have said no." | | 12 | "Every sensible part of her," | | 13 | "Lucien moved past her with" | | 14 | "The flat felt smaller with" | | 15 | "Books and scrolls climbed every" | | 16 | "He probably had." | | 17 | "A smile ghosted over his" | | 18 | "He lowered himself into the" | | 19 | "She fetched the first-aid tin" |
| | ratio | 0.852 | |
| 81.97% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 61 | | matches | | | ratio | 0.016 | |
| 6.80% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 21 | | technicalSentenceCount | 4 | | matches | | 0 | "Behind her, Ptolemy wound a figure-eight around her ankles, purring as if nothing in the world had changed." | | 1 | "As if the last person who'd promised her safety hadn't walked out of her life with a half-truth on his lips and a debt still hanging between them." | | 2 | "Every sensible part of her, the part that had survived Evan, the part that had fled Cardiff with a packed bag and a head full of warnings, screamed at her to sl…" | | 3 | "Close enough that she caught the warmth of him, the copper and the cedar, the heat that radiated off half-demon skin like a banked fire." |
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| 91.67% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 15 | | uselessAdditionCount | 1 | | matches | | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 5 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 48 | | tagDensity | 0.104 | | leniency | 0.208 | | rawRatio | 0.2 | | effectiveRatio | 0.042 | |