| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 17 | | adverbTagCount | 1 | | adverbTags | | 0 | "he said simply [simply]" |
| | dialogueSentences | 47 | | tagDensity | 0.362 | | leniency | 0.723 | | rawRatio | 0.059 | | effectiveRatio | 0.043 | |
| 70.29% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1683 | | totalAiIsmAdverbs | 10 | | found | | 0 | | | 1 | | | 2 | | adverb | "deliberately" | | count | 1 |
| | 3 | | | 4 | | | 5 | |
| | highlights | | 0 | "slowly" | | 1 | "quickly" | | 2 | "deliberately" | | 3 | "very" | | 4 | "suddenly" | | 5 | "softly" |
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| 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) | |
| 76.23% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1683 | | totalAiIsms | 8 | | found | | | highlights | | 0 | "unreadable" | | 1 | "stomach" | | 2 | "flickered" | | 3 | "tension" | | 4 | "silence" | | 5 | "complex" | | 6 | "traced" | | 7 | "weight" |
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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 | 1 | | narrationSentences | 107 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 107 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 138 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 66 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1688 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 23 | | unquotedAttributions | 0 | | matches | (empty) | |
| 50.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 54 | | wordCount | 1303 | | uniqueNames | 19 | | maxNameDensity | 0.84 | | worstName | "Eva" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Eva" | | discoveredNames | | Eva | 11 | | Oxford | 1 | | Thursday | 1 | | Raja | 1 | | Palace | 1 | | Ptolemy | 5 | | Post-its | 1 | | Moreau | 2 | | Rain | 1 | | Marseille | 1 | | Rory | 9 | | Carter | 1 | | Empress | 2 | | Lucien | 7 | | Avaros | 1 | | Brick | 1 | | Lane | 1 | | One | 4 | | Cool-headed | 3 |
| | persons | | 0 | "Eva" | | 1 | "Thursday" | | 2 | "Ptolemy" | | 3 | "Moreau" | | 4 | "Rory" | | 5 | "Carter" | | 6 | "Lucien" |
| | places | | 0 | "Oxford" | | 1 | "Raja" | | 2 | "Palace" | | 3 | "Marseille" | | 4 | "Empress" | | 5 | "Avaros" | | 6 | "Brick" | | 7 | "Lane" |
| | globalScore | 1 | | windowScore | 0.5 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 68 | | 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 | 1688 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 138 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 70 | | mean | 24.11 | | std | 24.31 | | cv | 1.008 | | sampleLengths | | 0 | 24 | | 1 | 73 | | 2 | 7 | | 3 | 37 | | 4 | 3 | | 5 | 8 | | 6 | 79 | | 7 | 8 | | 8 | 40 | | 9 | 5 | | 10 | 6 | | 11 | 88 | | 12 | 12 | | 13 | 18 | | 14 | 9 | | 15 | 1 | | 16 | 108 | | 17 | 5 | | 18 | 7 | | 19 | 19 | | 20 | 22 | | 21 | 14 | | 22 | 32 | | 23 | 31 | | 24 | 4 | | 25 | 10 | | 26 | 8 | | 27 | 8 | | 28 | 40 | | 29 | 14 | | 30 | 57 | | 31 | 13 | | 32 | 57 | | 33 | 9 | | 34 | 2 | | 35 | 16 | | 36 | 9 | | 37 | 14 | | 38 | 48 | | 39 | 8 | | 40 | 64 | | 41 | 42 | | 42 | 6 | | 43 | 2 | | 44 | 6 | | 45 | 22 | | 46 | 9 | | 47 | 21 | | 48 | 25 | | 49 | 9 |
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| 98.70% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 107 | | matches | | 0 | "was supposed" | | 1 | "was stressed" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 224 | | matches | | 0 | "was slowly darkening" | | 1 | "was hammering" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 3 | | semicolonCount | 0 | | flaggedSentences | 2 | | totalSentences | 138 | | ratio | 0.014 | | matches | | 0 | "Every surface was a battlefield of Eva's research - open books spine-up, scrolls half-unrolled, Post-its in three different colors stuck to a corkboard with red string between them like a conspiracy theorist's fever dream." | | 1 | "Rory undid them one by one - top, middle, bottom - and the cold metal bit into her fingertips." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 607 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 19 | | adverbRatio | 0.03130148270181219 | | lyAdverbCount | 2 | | lyAdverbRatio | 0.0032948929159802307 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 138 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 138 | | mean | 12.23 | | std | 11.58 | | cv | 0.947 | | sampleLengths | | 0 | 24 | | 1 | 14 | | 2 | 3 | | 3 | 26 | | 4 | 30 | | 5 | 4 | | 6 | 2 | | 7 | 1 | | 8 | 21 | | 9 | 16 | | 10 | 3 | | 11 | 8 | | 12 | 26 | | 13 | 19 | | 14 | 34 | | 15 | 2 | | 16 | 6 | | 17 | 19 | | 18 | 21 | | 19 | 5 | | 20 | 6 | | 21 | 10 | | 22 | 12 | | 23 | 39 | | 24 | 5 | | 25 | 10 | | 26 | 12 | | 27 | 4 | | 28 | 5 | | 29 | 3 | | 30 | 13 | | 31 | 5 | | 32 | 9 | | 33 | 1 | | 34 | 5 | | 35 | 7 | | 36 | 23 | | 37 | 15 | | 38 | 7 | | 39 | 35 | | 40 | 16 | | 41 | 5 | | 42 | 7 | | 43 | 19 | | 44 | 11 | | 45 | 11 | | 46 | 5 | | 47 | 1 | | 48 | 1 | | 49 | 7 |
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| 50.97% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 13 | | diversityRatio | 0.36231884057971014 | | totalSentences | 138 | | uniqueOpeners | 50 | |
| 71.68% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 93 | | matches | | 0 | "Slowly, as if he was" | | 1 | "Then he bent, just enough" |
| | ratio | 0.022 | |
| 69.46% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 35 | | totalSentences | 93 | | matches | | 0 | "She had a chipped mug" | | 1 | "She set the mug down" | | 2 | "Her left wrist caught the" | | 3 | "She pulled the door open." | | 4 | "He was out of context," | | 5 | "He wore a tailored charcoal" | | 6 | "His eyes found hers." | | 7 | "he said, in that Marseille" | | 8 | "Her stomach dropped somewhere down" | | 9 | "She said his name flat." | | 10 | "She hadn't seen him in" | | 11 | "He lifted the bag" | | 12 | "He looked tired." | | 13 | "he murmured, and scratched behind" | | 14 | "she said, but her voice" | | 15 | "He stood, and now he" | | 16 | "She could smell rain and" | | 17 | "Her bright blue eyes snapped" | | 18 | "he said simply" | | 19 | "She stepped back." |
| | ratio | 0.376 | |
| 67.53% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 73 | | totalSentences | 93 | | matches | | 0 | "The knock came just after" | | 1 | "Rory stared at the door" | | 2 | "Eva never knocked." | | 3 | "Eva had keys and no" | | 4 | "Anyone else who wanted Eva" | | 5 | "The knocking came again." | | 6 | "She had a chipped mug" | | 7 | "She set the mug down" | | 8 | "Ptolemy blinked at her and" | | 9 | "Rory padded to the door" | | 10 | "The flat was cold despite" | | 11 | "Every surface was a battlefield" | | 12 | "Eva was paranoid for good" | | 13 | "Rory undid them one by" | | 14 | "Her left wrist caught the" | | 15 | "She pulled the door open." | | 16 | "Lucien Moreau stood in the" | | 17 | "He was out of context," | | 18 | "He wore a tailored charcoal" | | 19 | "Rain beaded on his shoulders." |
| | ratio | 0.785 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 93 | | matches | (empty) | | ratio | 0 | |
| 26.58% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 43 | | technicalSentenceCount | 7 | | matches | | 0 | "The knock came just after midnight, three sharp raps that cut through the low hum of the extraction fan from the curry house below." | | 1 | "Cool-headed Rory Carter, who could talk her way out of a police stop and into a locked archive with the same even tone." | | 2 | "Not girl who melted because a half-demon fixer who spoke four languages fluently remembered her friend's cat's name." | | 3 | "She could smell rain and his cologne and the faint sulfur undertone that clung to him when he was stressed, something from his father's side, from Avaros." | | 4 | "The hallway was cold but the flat behind her was warm with tea and old paper, and she was suddenly, acutely aware that she wore an oversized cardigan that slipp…" | | 5 | "Slowly, as if he was afraid of spooking her, he lifted his free hand and brushed a damp strand of black hair behind her ear." | | 6 | "Then he bent, just enough that their foreheads nearly touched, his cane clattering softly against the counter as he let it fall to lean his weight on his other …" |
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| 66.18% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 17 | | uselessAdditionCount | 2 | | matches | | 0 | "she said, but her voice was thinner now" | | 1 | "she said, and her voice was steady now, because it was true and truth was easy" |
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| 86.17% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 14 | | fancyCount | 3 | | fancyTags | | 0 | "he murmured (murmur)" | | 1 | "he corrected (correct)" | | 2 | "he whispered (whisper)" |
| | dialogueSentences | 47 | | tagDensity | 0.298 | | leniency | 0.596 | | rawRatio | 0.214 | | effectiveRatio | 0.128 | |