| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 2 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 45 | | tagDensity | 0.044 | | leniency | 0.089 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 95.87% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1210 | | totalAiIsmAdverbs | 1 | | found | | | highlights | | |
| 100.00% | AI-ism character names | Target: 0 AI-default names (16 tracked, −20% each) | | codexExemptions | | | found | (empty) | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 66.94% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1210 | | totalAiIsms | 8 | | found | | | highlights | | 0 | "weight" | | 1 | "lilt" | | 2 | "scanning" | | 3 | "reminder" | | 4 | "traced" | | 5 | "warmth" | | 6 | "shattered" | | 7 | "flicker" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 64 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 64 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 107 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 35 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1210 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 9 | | unquotedAttributions | 0 | | matches | (empty) | |
| 33.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 37 | | wordCount | 684 | | uniqueNames | 7 | | maxNameDensity | 2.19 | | worstName | "Eva" | | maxWindowNameDensity | 4 | | worstWindowName | "Eva" | | discoveredNames | | Silas | 9 | | Rory | 9 | | Mediterranean | 1 | | Italy | 1 | | Eva | 15 | | Soho | 1 | | Glock | 1 |
| | persons | | 0 | "Silas" | | 1 | "Rory" | | 2 | "Mediterranean" | | 3 | "Eva" |
| | places | | | globalScore | 0.404 | | windowScore | 0.333 | |
| 51.96% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 51 | | glossingSentenceCount | 2 | | matches | | 0 | "sounded like gravel grinding under a boot" | | 1 | "felt like the worst thing in her world" |
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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 | 1210 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 107 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 69 | | mean | 17.54 | | std | 14.28 | | cv | 0.815 | | sampleLengths | | 0 | 73 | | 1 | 54 | | 2 | 10 | | 3 | 12 | | 4 | 41 | | 5 | 1 | | 6 | 10 | | 7 | 9 | | 8 | 6 | | 9 | 15 | | 10 | 22 | | 11 | 16 | | 12 | 7 | | 13 | 23 | | 14 | 26 | | 15 | 9 | | 16 | 2 | | 17 | 5 | | 18 | 40 | | 19 | 3 | | 20 | 12 | | 21 | 13 | | 22 | 41 | | 23 | 41 | | 24 | 5 | | 25 | 15 | | 26 | 19 | | 27 | 14 | | 28 | 17 | | 29 | 9 | | 30 | 22 | | 31 | 8 | | 32 | 14 | | 33 | 35 | | 34 | 6 | | 35 | 23 | | 36 | 9 | | 37 | 18 | | 38 | 11 | | 39 | 33 | | 40 | 22 | | 41 | 3 | | 42 | 18 | | 43 | 42 | | 44 | 2 | | 45 | 6 | | 46 | 2 | | 47 | 5 | | 48 | 8 | | 49 | 10 |
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| 99.78% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 64 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 117 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 107 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 684 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 19 | | adverbRatio | 0.027777777777777776 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.007309941520467836 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 107 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 107 | | mean | 11.31 | | std | 7.22 | | cv | 0.638 | | sampleLengths | | 0 | 15 | | 1 | 18 | | 2 | 19 | | 3 | 21 | | 4 | 6 | | 5 | 13 | | 6 | 19 | | 7 | 16 | | 8 | 2 | | 9 | 8 | | 10 | 12 | | 11 | 7 | | 12 | 8 | | 13 | 9 | | 14 | 17 | | 15 | 1 | | 16 | 10 | | 17 | 9 | | 18 | 6 | | 19 | 15 | | 20 | 6 | | 21 | 16 | | 22 | 16 | | 23 | 7 | | 24 | 11 | | 25 | 12 | | 26 | 26 | | 27 | 9 | | 28 | 2 | | 29 | 5 | | 30 | 13 | | 31 | 6 | | 32 | 3 | | 33 | 18 | | 34 | 3 | | 35 | 12 | | 36 | 13 | | 37 | 9 | | 38 | 32 | | 39 | 5 | | 40 | 27 | | 41 | 9 | | 42 | 5 | | 43 | 15 | | 44 | 19 | | 45 | 3 | | 46 | 11 | | 47 | 17 | | 48 | 9 | | 49 | 22 |
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| 43.46% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 7 | | diversityRatio | 0.29906542056074764 | | totalSentences | 107 | | uniqueOpeners | 32 | |
| 54.64% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 61 | | matches | | 0 | "Instead, it flew open with" |
| | ratio | 0.016 | |
| 56.07% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 25 | | totalSentences | 61 | | matches | | 0 | "She stared at the row" | | 1 | "He didn't speak, but his" | | 2 | "She wore a sharp, tailored" | | 3 | "Her hair, once a wild" | | 4 | "It sounded like gravel grinding" | | 5 | "She stopped three feet away," | | 6 | "She didn't smile, but her" | | 7 | "She looked back at Rory," | | 8 | "She didn't ask for a" | | 9 | "She simply waited." | | 10 | "She stepped closer, the smoke" | | 11 | "She reached out, her fingers" | | 12 | "She stopped before a large," | | 13 | "Her finger traced a line" | | 14 | "She didn't turn around." | | 15 | "She paused, looking back over" | | 16 | "She turned to leave, her" | | 17 | "They didn't look like Soho" | | 18 | "They wore heavy, charcoal grey" | | 19 | "He looked straight at Eva." |
| | ratio | 0.41 | |
| 0.98% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 56 | | totalSentences | 61 | | matches | | 0 | "Rory gripped the damp rim" | | 1 | "She stared at the row" | | 2 | "He didn't speak, but his" | | 3 | "The door groaned on its" | | 4 | "A woman stepped inside, pausing" | | 5 | "She wore a sharp, tailored" | | 6 | "Her hair, once a wild" | | 7 | "The glass slipped a fraction" | | 8 | "The voice had lost its" | | 9 | "It sounded like gravel grinding" | | 10 | "Eva walked toward them, her" | | 11 | "She stopped three feet away," | | 12 | "Rory set the glass down" | | 13 | "Eva turned her gaze to" | | 14 | "She didn't smile, but her" | | 15 | "Eva laughed, a short, sharp" | | 16 | "She looked back at Rory," | | 17 | "Rory smoothed the fabric of" | | 18 | "Eva reached into her coat" | | 19 | "She didn't ask for a" |
| | ratio | 0.918 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 61 | | matches | (empty) | | ratio | 0 | |
| 56.28% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 33 | | technicalSentenceCount | 4 | | matches | | 0 | "She looked back at Rory, her expression shifting to something resembling pity." | | 1 | "Rory felt the crescent scar on her wrist itch, a phantom reminder of a childhood accident that had once felt like the worst thing in her world." | | 2 | "They wore heavy, charcoal grey suits and mirrored sunglasses that hid their eyes." | | 3 | "He twisted his arm, a sharp, professional movement that sent Silas stumbling back." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 2 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 1 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 45 | | tagDensity | 0.022 | | leniency | 0.044 | | rawRatio | 1 | | effectiveRatio | 0.044 | |