| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 20 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 28 | | tagDensity | 0.714 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 78.35% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 924 | | totalAiIsmAdverbs | 4 | | found | | | highlights | | |
| 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) | |
| 24.24% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 924 | | totalAiIsms | 14 | | found | | | highlights | | 0 | "pounding" | | 1 | "flickered" | | 2 | "familiar" | | 3 | "comforting" | | 4 | "flicker" | | 5 | "flicked" | | 6 | "silence" | | 7 | "raced" | | 8 | "eyebrow" | | 9 | "calculating" | | 10 | "weight" | | 11 | "unspoken" |
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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 | 49 | | matches | (empty) | |
| 84.55% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 2 | | narrationSentences | 49 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 56 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 62 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 927 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 17 | | unquotedAttributions | 0 | | matches | (empty) | |
| 32.11% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 43 | | wordCount | 721 | | uniqueNames | 5 | | maxNameDensity | 2.36 | | worstName | "Eva" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Eva" | | discoveredNames | | Carter | 1 | | Eva | 17 | | Rory | 14 | | Silence | 1 | | Luc | 10 |
| | persons | | 0 | "Carter" | | 1 | "Eva" | | 2 | "Rory" | | 3 | "Silence" | | 4 | "Luc" |
| | places | (empty) | | globalScore | 0.321 | | windowScore | 0.5 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 33 | | 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 | 927 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 56 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 36 | | mean | 25.75 | | std | 16.1 | | cv | 0.625 | | sampleLengths | | 0 | 51 | | 1 | 35 | | 2 | 13 | | 3 | 41 | | 4 | 55 | | 5 | 10 | | 6 | 6 | | 7 | 16 | | 8 | 41 | | 9 | 10 | | 10 | 16 | | 11 | 19 | | 12 | 19 | | 13 | 38 | | 14 | 11 | | 15 | 5 | | 16 | 14 | | 17 | 12 | | 18 | 47 | | 19 | 14 | | 20 | 21 | | 21 | 45 | | 22 | 15 | | 23 | 14 | | 24 | 14 | | 25 | 37 | | 26 | 24 | | 27 | 19 | | 28 | 4 | | 29 | 50 | | 30 | 28 | | 31 | 19 | | 32 | 56 | | 33 | 22 | | 34 | 61 | | 35 | 25 |
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| 98.10% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 49 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 159 | | matches | | |
| 40.82% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 3 | | semicolonCount | 0 | | flaggedSentences | 2 | | totalSentences | 56 | | ratio | 0.036 | | matches | | 0 | "A flicker of something — hope, maybe — crossed Eva’s face before being squashed." | | 1 | "But —” She paused, trying to find the words to express just how desperate she was. “I have nowhere else to turn.”" |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 499 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 11 | | adverbRatio | 0.022044088176352707 | | lyAdverbCount | 3 | | lyAdverbRatio | 0.006012024048096192 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 56 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 56 | | mean | 16.55 | | std | 13.58 | | cv | 0.82 | | sampleLengths | | 0 | 15 | | 1 | 26 | | 2 | 10 | | 3 | 15 | | 4 | 14 | | 5 | 6 | | 6 | 9 | | 7 | 4 | | 8 | 7 | | 9 | 16 | | 10 | 8 | | 11 | 10 | | 12 | 16 | | 13 | 19 | | 14 | 15 | | 15 | 5 | | 16 | 10 | | 17 | 6 | | 18 | 14 | | 19 | 2 | | 20 | 33 | | 21 | 8 | | 22 | 10 | | 23 | 10 | | 24 | 6 | | 25 | 12 | | 26 | 7 | | 27 | 15 | | 28 | 2 | | 29 | 2 | | 30 | 38 | | 31 | 11 | | 32 | 5 | | 33 | 13 | | 34 | 1 | | 35 | 10 | | 36 | 2 | | 37 | 47 | | 38 | 14 | | 39 | 21 | | 40 | 45 | | 41 | 15 | | 42 | 14 | | 43 | 14 | | 44 | 15 | | 45 | 22 | | 46 | 24 | | 47 | 19 | | 48 | 4 | | 49 | 50 |
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| 98.21% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 1 | | diversityRatio | 0.6428571428571429 | | totalSentences | 56 | | uniqueOpeners | 36 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 40 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 6 | | totalSentences | 40 | | matches | | 0 | "It had been months since" | | 1 | "His heterochromatic eyes widened as" | | 2 | "He shrugged, a small smile" | | 3 | "He gestured for her to" | | 4 | "She took a deep breath" | | 5 | "She cut that train of" |
| | ratio | 0.15 | |
| 72.50% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 31 | | totalSentences | 40 | | matches | | 0 | "Aurora Carter stared at the" | | 1 | "It had been months since" | | 2 | "The door swung open to" | | 3 | "Shock flickered across her face" | | 4 | "Rory sighed, shouldering her bag" | | 5 | "Rory brushed past her, the" | | 6 | "Books and papers spilled across" | | 7 | "Ptolemy, Eva’s tabby cat, wound" | | 8 | "Eva shut the door behind" | | 9 | "Rory turned to face her," | | 10 | "Words bubbled up inside her," | | 11 | "Eva asked, crossing her arms" | | 12 | "A flicker of something —" | | 13 | "His heterochromatic eyes widened as" | | 14 | "Rory said, pleased at how" | | 15 | "He shrugged, a small smile" | | 16 | "Rory’s gaze flicked to Eva," | | 17 | "Silence stretched between them, awkward" | | 18 | "Luc raised an eyebrow, his" | | 19 | "He gestured for her to" |
| | ratio | 0.775 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 40 | | matches | | 0 | "Because if they failed, she" |
| | ratio | 0.025 | |
| 45.45% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 22 | | technicalSentenceCount | 3 | | matches | | 0 | "He gestured for her to sit on the battered sofa, already moving to settle himself next to Eva on the floor. Rory hesitated before joining them, her heart sinkin…" | | 1 | "She took a deep breath and then launched into an explanation, trying to ignore the weight of Eva and Luc’s gazes on her. As she talked, detailing the danger she…" | | 2 | "But there was no time for self-indulgent questions, not when her very life depended on the wits of her estranged friends and the secrets held in dusty tomes. Ro…" |
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| 66.18% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 17 | | uselessAdditionCount | 2 | | matches | | 0 | "Rory demanded, frustration bubbling up" | | 1 | "Luc said, voice wry" |
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| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 14 | | fancyCount | 8 | | fancyTags | | 0 | "Rory sighed (sigh)" | | 1 | "Rory admitted (admit)" | | 2 | "he drawled (drawl)" | | 3 | "Eva muttered (mutter)" | | 4 | "Rory interjected (interject)" | | 5 | "Rory demanded (demand)" | | 6 | "Eva sighed (sigh)" | | 7 | "Rory breathed (breathe)" |
| | dialogueSentences | 28 | | tagDensity | 0.5 | | leniency | 1 | | rawRatio | 0.571 | | effectiveRatio | 0.571 | |