| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 26 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 116 | | tagDensity | 0.224 | | leniency | 0.448 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 93.28% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 2231 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | 0 | "quickly" | | 1 | "very" | | 2 | "slightly" |
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| 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) | |
| 91.04% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 2231 | | totalAiIsms | 4 | | found | | | highlights | | 0 | "structure" | | 1 | "silence" | | 2 | "perfect" | | 3 | "trembled" |
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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 | 1 | | narrationSentences | 182 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 1 | | narrationSentences | 182 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 272 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 41 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 2228 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 29 | | unquotedAttributions | 1 | | matches | | 0 | "In the most satisfying version, she said nothing at all and walked away." |
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| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 120 | | wordCount | 1728 | | uniqueNames | 14 | | maxNameDensity | 2.66 | | worstName | "Eva" | | maxWindowNameDensity | 6.5 | | worstWindowName | "Eva" | | discoveredNames | | Soho | 2 | | Rory | 45 | | Nest | 3 | | Golden | 1 | | Empress | 1 | | Eva | 46 | | Cardiff | 2 | | London | 2 | | Carter | 1 | | Evan | 2 | | Leave | 1 | | Central | 1 | | Silas | 12 | | You | 1 |
| | persons | | 0 | "Rory" | | 1 | "Eva" | | 2 | "Carter" | | 3 | "Evan" | | 4 | "Silas" | | 5 | "You" |
| | places | | 0 | "Soho" | | 1 | "Golden" | | 2 | "Cardiff" | | 3 | "London" |
| | globalScore | 0.169 | | windowScore | 0 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 115 | | glossingSentenceCount | 1 | | matches | | 0 | "Not quite a laugh, but close enough that Rory remembered the girl with copper curls and red trainers, the girl who could make a stolen apple feel like a conspiracy" |
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| 0.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 5 | | per1kWords | 2.244 | | wordCount | 2228 | | matches | | 0 | "not with surprise, exactly, but with the controlled collapse of a structure" | | 1 | "not a clean wound but a room full of objects neither of them had the courage to mo" | | 2 | "Not quite a laugh, but close enough" | | 3 | "not the girl who vanished, not the woman with the scar and silver hair, but the friend who had once promised London would be different" | | 4 | "not the woman with the scar and silver hair, but the friend who had once promised London would be different" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 272 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 172 | | mean | 12.95 | | std | 16.63 | | cv | 1.284 | | sampleLengths | | 0 | 18 | | 1 | 77 | | 2 | 57 | | 3 | 21 | | 4 | 2 | | 5 | 19 | | 6 | 5 | | 7 | 1 | | 8 | 64 | | 9 | 3 | | 10 | 1 | | 11 | 1 | | 12 | 2 | | 13 | 7 | | 14 | 62 | | 15 | 5 | | 16 | 11 | | 17 | 6 | | 18 | 3 | | 19 | 2 | | 20 | 71 | | 21 | 11 | | 22 | 67 | | 23 | 8 | | 24 | 7 | | 25 | 3 | | 26 | 32 | | 27 | 3 | | 28 | 9 | | 29 | 33 | | 30 | 6 | | 31 | 19 | | 32 | 6 | | 33 | 5 | | 34 | 2 | | 35 | 13 | | 36 | 102 | | 37 | 3 | | 38 | 10 | | 39 | 5 | | 40 | 6 | | 41 | 39 | | 42 | 9 | | 43 | 8 | | 44 | 2 | | 45 | 2 | | 46 | 15 | | 47 | 25 | | 48 | 4 | | 49 | 3 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 182 | | matches | | 0 | "was buried" | | 1 | "been abandoned" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 304 | | matches | | 0 | "was polishing" | | 1 | "was drying" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 3 | | semicolonCount | 0 | | flaggedSentences | 3 | | totalSentences | 272 | | ratio | 0.011 | | matches | | 0 | "Then Eva’s face altered—not with surprise, exactly, but with the controlled collapse of a structure that had been standing under strain for too long." | | 1 | "Rory heard it then—the faint vibration of a phone." | | 2 | "For the first time in years, she allowed herself to remember Eva as she had been—not the girl who vanished, not the woman with the scar and silver hair, but the friend who had once promised London would be different." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1734 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 57 | | adverbRatio | 0.0328719723183391 | | lyAdverbCount | 21 | | lyAdverbRatio | 0.012110726643598616 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 272 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 272 | | mean | 8.19 | | std | 6.97 | | cv | 0.851 | | sampleLengths | | 0 | 18 | | 1 | 5 | | 2 | 29 | | 3 | 20 | | 4 | 23 | | 5 | 16 | | 6 | 26 | | 7 | 15 | | 8 | 8 | | 9 | 13 | | 10 | 2 | | 11 | 19 | | 12 | 5 | | 13 | 1 | | 14 | 6 | | 15 | 14 | | 16 | 20 | | 17 | 24 | | 18 | 3 | | 19 | 1 | | 20 | 1 | | 21 | 2 | | 22 | 7 | | 23 | 11 | | 24 | 8 | | 25 | 20 | | 26 | 15 | | 27 | 8 | | 28 | 2 | | 29 | 3 | | 30 | 5 | | 31 | 6 | | 32 | 6 | | 33 | 3 | | 34 | 2 | | 35 | 24 | | 36 | 5 | | 37 | 23 | | 38 | 10 | | 39 | 9 | | 40 | 11 | | 41 | 12 | | 42 | 9 | | 43 | 16 | | 44 | 18 | | 45 | 8 | | 46 | 4 | | 47 | 8 | | 48 | 7 | | 49 | 3 |
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| 45.59% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 12 | | diversityRatio | 0.27205882352941174 | | totalSentences | 272 | | uniqueOpeners | 74 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 5 | | totalSentences | 155 | | matches | | 0 | "Somewhere behind the wall, the" | | 1 | "Then Eva’s face altered—not with" | | 2 | "Then he returned to the" | | 3 | "Instead she said," | | 4 | "Then she stepped into the" |
| | ratio | 0.032 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 39 | | totalSentences | 155 | | matches | | 0 | "She should have gone upstairs." | | 1 | "Her delivery bag hung from" | | 2 | "She pushed through the door," | | 3 | "He looked up and took" | | 4 | "He had the kind of" | | 5 | "He leaned more heavily on" | | 6 | "Her black hair fell straight" | | 7 | "She rubbed it with her" | | 8 | "He noticed everything." | | 9 | "He poured boiling water over" | | 10 | "She was taller than Rory" | | 11 | "Her hair, once a riot" | | 12 | "She carried no umbrella." | | 13 | "He looked from one woman" | | 14 | "It was almost the same" | | 15 | "She had slept on the" | | 16 | "I’ll find you somewhere to" | | 17 | "He set it before Eva," | | 18 | "His silver signet ring caught" | | 19 | "he asked Rory" |
| | ratio | 0.252 | |
| 56.77% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 125 | | totalSentences | 155 | | matches | | 0 | "The rain had polished Soho" | | 1 | "She should have gone upstairs." | | 2 | "Her delivery bag hung from" | | 3 | "She pushed through the door," | | 4 | "The Nest smelled of orange" | | 5 | "Silas was polishing a glass" | | 6 | "He looked up and took" | | 7 | "Silas’s mouth moved toward a" | | 8 | "He had the kind of" | | 9 | "He leaned more heavily on" | | 10 | "Rory shrugged off her jacket" | | 11 | "Her black hair fell straight" | | 12 | "The small crescent scar on" | | 13 | "She rubbed it with her" | | 14 | "He noticed everything." | | 15 | "He poured boiling water over" | | 16 | "The Nest was nearly empty." | | 17 | "A man in a grey" | | 18 | "Rory had just taken her" | | 19 | "The woman who entered paused" |
| | ratio | 0.806 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 155 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 69 | | technicalSentenceCount | 4 | | matches | | 0 | "He had the kind of face that made amusement look like a private intelligence." | | 1 | "Then Eva’s face altered—not with surprise, exactly, but with the controlled collapse of a structure that had been standing under strain for too long." | | 2 | "At fourteen, she had dragged Rory through the Cardiff rain in red trainers, stolen apples from the market, and talked about London as if it were a secret countr…" | | 3 | "Not quite a laugh, but close enough that Rory remembered the girl with copper curls and red trainers, the girl who could make a stolen apple feel like a conspir…" |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 26 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 21 | | fancyCount | 1 | | fancyTags | | 0 | "Eva continued (continue)" |
| | dialogueSentences | 116 | | tagDensity | 0.181 | | leniency | 0.362 | | rawRatio | 0.048 | | effectiveRatio | 0.017 | |