| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 22 | | adverbTagCount | 1 | | adverbTags | | 0 | "Eva said finally [finally]" |
| | dialogueSentences | 66 | | tagDensity | 0.333 | | leniency | 0.667 | | rawRatio | 0.045 | | effectiveRatio | 0.03 | |
| 93.83% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1621 | | totalAiIsmAdverbs | 2 | | 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) | |
| 53.73% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1621 | | totalAiIsms | 15 | | found | | | highlights | | 0 | "familiar" | | 1 | "methodical" | | 2 | "warmth" | | 3 | "gleaming" | | 4 | "weight" | | 5 | "remarkable" | | 6 | "scanning" | | 7 | "lilt" | | 8 | "silence" | | 9 | "flicked" | | 10 | "tension" | | 11 | "measured" | | 12 | "flickered" |
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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 | 1 | | narrationSentences | 102 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 102 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 144 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 65 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1614 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 15 | | unquotedAttributions | 0 | | matches | (empty) | |
| 33.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 71 | | wordCount | 1177 | | uniqueNames | 14 | | maxNameDensity | 1.95 | | worstName | "Rory" | | maxWindowNameDensity | 4 | | worstWindowName | "Eva" | | discoveredNames | | London | 3 | | Raven | 3 | | Nest | 3 | | Thursday | 1 | | Rioja | 1 | | Rory | 23 | | Silas | 7 | | Masood | 1 | | Eva | 22 | | Soho | 1 | | Camberwell | 1 | | Doc | 1 | | Martens | 1 | | Cardiff | 3 |
| | persons | | 0 | "Raven" | | 1 | "Nest" | | 2 | "Rory" | | 3 | "Silas" | | 4 | "Masood" | | 5 | "Eva" |
| | places | | 0 | "London" | | 1 | "Soho" | | 2 | "Camberwell" | | 3 | "Cardiff" |
| | globalScore | 0.523 | | windowScore | 0.333 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 62 | | glossingSentenceCount | 1 | | matches | | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1614 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 2 | | totalSentences | 144 | | matches | | 0 | "say that she'd" | | 1 | "say that she" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 65 | | mean | 24.83 | | std | 24.43 | | cv | 0.984 | | sampleLengths | | 0 | 68 | | 1 | 62 | | 2 | 20 | | 3 | 20 | | 4 | 43 | | 5 | 63 | | 6 | 35 | | 7 | 55 | | 8 | 8 | | 9 | 1 | | 10 | 24 | | 11 | 1 | | 12 | 84 | | 13 | 24 | | 14 | 12 | | 15 | 38 | | 16 | 3 | | 17 | 11 | | 18 | 48 | | 19 | 8 | | 20 | 16 | | 21 | 25 | | 22 | 23 | | 23 | 3 | | 24 | 28 | | 25 | 11 | | 26 | 91 | | 27 | 5 | | 28 | 70 | | 29 | 7 | | 30 | 15 | | 31 | 2 | | 32 | 7 | | 33 | 2 | | 34 | 12 | | 35 | 81 | | 36 | 5 | | 37 | 9 | | 38 | 33 | | 39 | 33 | | 40 | 20 | | 41 | 1 | | 42 | 39 | | 43 | 5 | | 44 | 68 | | 45 | 3 | | 46 | 2 | | 47 | 27 | | 48 | 45 | | 49 | 2 |
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| 88.06% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 5 | | totalSentences | 102 | | matches | | 0 | "being asked" | | 1 | "been guilt" | | 2 | "was gone" | | 3 | "were painted" | | 4 | "was scared" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 197 | | matches | | |
| 23.81% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 7 | | semicolonCount | 0 | | flaggedSentences | 6 | | totalSentences | 144 | | ratio | 0.042 | | matches | | 0 | "But the way she said the name—that particular lilt on the first syllable—that hadn't changed at all." | | 1 | "It wasn't lines or grey hairs—it was something in the architecture of her face." | | 2 | "Eva laughed, but it came out wrong—too polished, too controlled." | | 3 | "Something flickered there—something old and familiar that hadn't been entirely buried." | | 4 | "\"No.\" Eva smiled, and for a moment it was real—small and sad and genuine." | | 5 | "She thought about all the versions of herself she had been—the girl in Cardiff, the girl who fled, the girl who arrived in London with nothing, the woman who sat here now." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1189 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 30 | | adverbRatio | 0.025231286795626577 | | lyAdverbCount | 6 | | lyAdverbRatio | 0.005046257359125316 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 144 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 144 | | mean | 11.21 | | std | 10.6 | | cv | 0.946 | | sampleLengths | | 0 | 21 | | 1 | 26 | | 2 | 21 | | 3 | 7 | | 4 | 10 | | 5 | 21 | | 6 | 24 | | 7 | 13 | | 8 | 7 | | 9 | 18 | | 10 | 2 | | 11 | 24 | | 12 | 19 | | 13 | 9 | | 14 | 20 | | 15 | 7 | | 16 | 4 | | 17 | 23 | | 18 | 32 | | 19 | 3 | | 20 | 10 | | 21 | 25 | | 22 | 20 | | 23 | 8 | | 24 | 1 | | 25 | 4 | | 26 | 1 | | 27 | 2 | | 28 | 17 | | 29 | 1 | | 30 | 36 | | 31 | 11 | | 32 | 14 | | 33 | 1 | | 34 | 2 | | 35 | 20 | | 36 | 7 | | 37 | 13 | | 38 | 4 | | 39 | 12 | | 40 | 10 | | 41 | 23 | | 42 | 5 | | 43 | 3 | | 44 | 7 | | 45 | 4 | | 46 | 7 | | 47 | 15 | | 48 | 26 | | 49 | 3 |
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| 50.93% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 15 | | diversityRatio | 0.3680555555555556 | | totalSentences | 144 | | uniqueOpeners | 53 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 85 | | matches | (empty) | | ratio | 0 | |
| 97.65% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 26 | | totalSentences | 85 | | matches | | 0 | "His signet ring caught the" | | 1 | "He never asked about her" | | 2 | "He didn't need to." | | 3 | "She glanced up." | | 4 | "She was scanning the room," | | 5 | "She had aged, though not" | | 6 | "It wasn't lines or grey" | | 7 | "She moved closer, her heels" | | 8 | "They sat in silence for" | | 9 | "His hazel eyes flicked between" | | 10 | "She'd been counting too." | | 11 | "She picked up the menu," | | 12 | "She didn't say that she'd" | | 13 | "She didn't say that she" | | 14 | "Her nails were painted a" | | 15 | "She pressed her fingers to" | | 16 | "She watched the rain trace" | | 17 | "She turned the glass in" | | 18 | "It was old and deep" | | 19 | "They sat together in the" |
| | ratio | 0.306 | |
| 7.06% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 77 | | totalSentences | 85 | | matches | | 0 | "The rain had been falling" | | 1 | "Rory pushed through the door" | | 2 | "The green neon sign buzzed" | | 3 | "The bar was quiet for" | | 4 | "A couple nursed gin and" | | 5 | "An older man in a" | | 6 | "Silas stood behind the counter," | | 7 | "Rory dropped her bag on" | | 8 | "Silas set the glass down" | | 9 | "Rory accepted the wine and" | | 10 | "Silas made a sound that" | | 11 | "His signet ring caught the" | | 12 | "He never asked about her" | | 13 | "He didn't need to." | | 14 | "Rory was halfway through her" | | 15 | "She glanced up." | | 16 | "The woman who entered was" | | 17 | "She was scanning the room," | | 18 | "The voice was different." | | 19 | "Eva Masood stood in the" |
| | ratio | 0.906 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 85 | | matches | (empty) | | ratio | 0 | |
| 57.82% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 42 | | technicalSentenceCount | 5 | | matches | | 0 | "Silas stood behind the counter, polishing a glass with the methodical patience of a man who had spent decades waiting for things to happen." | | 1 | "Rory was halfway through her glass, scrolling through her phone without really seeing it, when the door opened and brought with it a gust of cold air and the so…" | | 2 | "Dark hair cut sharp at the jaw, expensive-looking coat, heels that clicked against the floor with the confidence of someone who belonged wherever she walked." | | 3 | "For a moment, Rory saw the woman who had sat up with her until four in the morning during their first year at Cardiff, who had convinced her that one more drink…" | | 4 | "They sat together in the quiet of the bar, two women who had once been girls together in a flat in Cardiff, who had shared clothes and secrets and late-night ci…" |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 22 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 9 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 66 | | tagDensity | 0.136 | | leniency | 0.273 | | rawRatio | 0 | | effectiveRatio | 0 | |