| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 10 | | adverbTagCount | 1 | | adverbTags | | 0 | "he said finally [finally]" |
| | dialogueSentences | 29 | | tagDensity | 0.345 | | leniency | 0.69 | | rawRatio | 0.1 | | effectiveRatio | 0.069 | |
| 95.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1001 | | totalAiIsmAdverbs | 1 | | found | | 0 | | adverb | "barely above a whisper" | | count | 1 |
|
| | highlights | | 0 | "barely above a whisper" |
| |
| 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) | |
| 0.00% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1001 | | totalAiIsms | 26 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | word | "down her spine" | | count | 1 |
| | 8 | | | 9 | | | 10 | | | 11 | | | 12 | | | 13 | | | 14 | | | 15 | | | 16 | | | 17 | | | 18 | | | 19 | |
| | highlights | | 0 | "whisper" | | 1 | "echoing" | | 2 | "unreadable" | | 3 | "weight" | | 4 | "unspoken" | | 5 | "tension" | | 6 | "testament" | | 7 | "down her spine" | | 8 | "resolve" | | 9 | "stomach" | | 10 | "churn" | | 11 | "grave" | | 12 | "warmth" | | 13 | "reminder" | | 14 | "eyebrow" | | 15 | "dance" | | 16 | "sense of" | | 17 | "navigate" | | 18 | "silence" | | 19 | "comforting" |
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| 0.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 4 | | maxInWindow | 4 | | found | | 0 | | label | "shiver down spine" | | count | 1 |
| | 1 | | label | "blood ran cold" | | count | 1 |
| | 2 | | label | "weight of words/silence" | | count | 1 |
| | 3 | | label | "flicker of emotion" | | count | 1 |
|
| | highlights | | 0 | "A shiver ran down her spine" | | 1 | "blood ran cold" | | 2 | "The weight of unspoken words" | | 3 | "a glimmer of hope" |
| |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 64 | | matches | (empty) | |
| 98.21% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 2 | | narrationSentences | 64 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 83 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 27 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1000 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 11 | | unquotedAttributions | 1 | | matches | | 0 | "Finally, they agreed on a time to meet at the Abyss." |
| |
| 81.25% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 31 | | wordCount | 800 | | uniqueNames | 9 | | maxNameDensity | 1.38 | | worstName | "Aurora" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Lucien" | | discoveredNames | | Eva | 2 | | Moreau | 1 | | Frenchman | 1 | | Ptolemy | 3 | | Lucien | 10 | | Avaros | 1 | | Aurora | 11 | | London | 1 | | Abyss | 1 |
| | persons | | 0 | "Eva" | | 1 | "Moreau" | | 2 | "Ptolemy" | | 3 | "Lucien" | | 4 | "Aurora" |
| | places | | | globalScore | 0.813 | | windowScore | 0.833 | |
| 55.66% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 53 | | glossingSentenceCount | 2 | | matches | | 0 | "quite name" | | 1 | "It was as if they were falling back into a rhythm they once knew, a dance of give and take" |
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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 | 1000 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 83 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 39 | | mean | 25.64 | | std | 16.49 | | cv | 0.643 | | sampleLengths | | 0 | 66 | | 1 | 30 | | 2 | 8 | | 3 | 35 | | 4 | 24 | | 5 | 17 | | 6 | 16 | | 7 | 41 | | 8 | 6 | | 9 | 19 | | 10 | 15 | | 11 | 13 | | 12 | 6 | | 13 | 30 | | 14 | 14 | | 15 | 48 | | 16 | 10 | | 17 | 23 | | 18 | 40 | | 19 | 13 | | 20 | 36 | | 21 | 31 | | 22 | 6 | | 23 | 45 | | 24 | 13 | | 25 | 17 | | 26 | 11 | | 27 | 21 | | 28 | 15 | | 29 | 64 | | 30 | 66 | | 31 | 27 | | 32 | 10 | | 33 | 13 | | 34 | 30 | | 35 | 51 | | 36 | 32 | | 37 | 22 | | 38 | 16 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 64 | | matches | (empty) | |
| 51.85% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 3 | | totalVerbs | 135 | | matches | | 0 | "was making" | | 1 | "was cooling" | | 2 | "were falling" |
| |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 1 | | semicolonCount | 0 | | flaggedSentences | 1 | | totalSentences | 83 | | ratio | 0.012 | | matches | | 0 | "Lucien's eyes lit up with a mix of relief and something else—something she couldn’t quite name." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 805 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 25 | | adverbRatio | 0.031055900621118012 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.006211180124223602 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 83 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 83 | | mean | 12.05 | | std | 6.14 | | cv | 0.51 | | sampleLengths | | 0 | 18 | | 1 | 6 | | 2 | 26 | | 3 | 16 | | 4 | 9 | | 5 | 21 | | 6 | 7 | | 7 | 1 | | 8 | 9 | | 9 | 17 | | 10 | 6 | | 11 | 3 | | 12 | 24 | | 13 | 13 | | 14 | 4 | | 15 | 14 | | 16 | 2 | | 17 | 10 | | 18 | 13 | | 19 | 18 | | 20 | 6 | | 21 | 16 | | 22 | 3 | | 23 | 15 | | 24 | 4 | | 25 | 9 | | 26 | 6 | | 27 | 6 | | 28 | 13 | | 29 | 11 | | 30 | 5 | | 31 | 9 | | 32 | 11 | | 33 | 16 | | 34 | 21 | | 35 | 10 | | 36 | 23 | | 37 | 22 | | 38 | 18 | | 39 | 6 | | 40 | 7 | | 41 | 16 | | 42 | 20 | | 43 | 17 | | 44 | 14 | | 45 | 5 | | 46 | 1 | | 47 | 16 | | 48 | 13 | | 49 | 16 |
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| 69.88% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 2 | | diversityRatio | 0.43373493975903615 | | totalSentences | 83 | | uniqueOpeners | 36 | |
| 52.91% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 63 | | matches | | 0 | "Finally, they agreed on a" |
| | ratio | 0.016 | |
| 61.27% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 25 | | totalSentences | 63 | | matches | | 0 | "she managed, her voice barely" | | 1 | "Her heart pounded like a" | | 2 | "He gave a nod, his" | | 3 | "She could see the tension" | | 4 | "she asked, trying to sound" | | 5 | "He stepped into the flat," | | 6 | "he said finally" | | 7 | "she demanded, her voice sharp" | | 8 | "She remembered the way he" | | 9 | "she asked, her voice trembling" | | 10 | "she said, her resolve hardening" | | 11 | "He nodded, his expression grave." | | 12 | "She moved to the kitchen," | | 13 | "She poured herself another, the" | | 14 | "she asked, taking a sip" | | 15 | "she said, a hint of" | | 16 | "They spent the next hour" | | 17 | "It was as if they" | | 18 | "She knew she couldn’t afford" | | 19 | "he said, his eyes locking" |
| | ratio | 0.397 | |
| 7.62% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 57 | | totalSentences | 63 | | matches | | 0 | "The door to Eva’s flat" | | 1 | "Aurora's breath caught in her" | | 2 | "Lucien Moreau, the Frenchman with" | | 3 | "The faint scent of his" | | 4 | "she managed, her voice barely" | | 5 | "Her heart pounded like a" | | 6 | "He gave a nod, his" | | 7 | "The weight of unspoken words" | | 8 | "She could see the tension" | | 9 | "This was not a casual" | | 10 | "Something was wrong." | | 11 | "she asked, trying to sound" | | 12 | "He stepped into the flat," | | 13 | "Aurora crossed her arms, a" | | 14 | "Lucien hesitated, his gaze flicking" | | 15 | "Books and scrolls covered every" | | 16 | "The tabby cat, Ptolemy, meowed" | | 17 | "he said finally" | | 18 | "The name was a punch" | | 19 | "Aurora’s blood ran cold." |
| | ratio | 0.905 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 63 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 42 | | technicalSentenceCount | 1 | | matches | | 0 | "Lucien Moreau, the Frenchman with eyes that could shift from amber to black, stood in the threshold, his platinum-blond hair slicked back as neatly as ever." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 10 | | uselessAdditionCount | 7 | | matches | | 0 | "she managed, her voice barely above a whisper" | | 1 | "she demanded, her voice sharp" | | 2 | "she asked, her voice trembling" | | 3 | "she said, her resolve hardening" | | 4 | "she said, a hint of her old bravado returning" | | 5 | "he said, his eyes locking onto hers" | | 6 | "she whispered, her voice full of determination" |
| |
| 81.03% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 9 | | fancyCount | 2 | | fancyTags | | 0 | "she demanded (demand)" | | 1 | "she whispered (whisper)" |
| | dialogueSentences | 29 | | tagDensity | 0.31 | | leniency | 0.621 | | rawRatio | 0.222 | | effectiveRatio | 0.138 | |