| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 9 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 71 | | tagDensity | 0.127 | | leniency | 0.254 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1033 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 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) | |
| 41.92% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1033 | | totalAiIsms | 12 | | found | | | highlights | | 0 | "silence" | | 1 | "weight" | | 2 | "traced" | | 3 | "gleaming" | | 4 | "fractured" |
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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 | 0 | | narrationSentences | 120 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 120 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 182 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 29 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1028 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 11 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 6 | | wordCount | 715 | | uniqueNames | 4 | | maxNameDensity | 0.42 | | worstName | "Silence" | | maxWindowNameDensity | 0.5 | | worstWindowName | "Silence" | | discoveredNames | | Europe | 1 | | Raven | 1 | | Shadow | 1 | | Silence | 3 |
| | persons | | | places | | | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 52 | | 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 | 1028 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 182 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 79 | | mean | 13.01 | | std | 8.11 | | cv | 0.623 | | sampleLengths | | 0 | 17 | | 1 | 40 | | 2 | 44 | | 3 | 2 | | 4 | 46 | | 5 | 4 | | 6 | 5 | | 7 | 9 | | 8 | 14 | | 9 | 11 | | 10 | 17 | | 11 | 14 | | 12 | 10 | | 13 | 24 | | 14 | 23 | | 15 | 14 | | 16 | 16 | | 17 | 18 | | 18 | 26 | | 19 | 9 | | 20 | 22 | | 21 | 10 | | 22 | 17 | | 23 | 17 | | 24 | 14 | | 25 | 14 | | 26 | 15 | | 27 | 15 | | 28 | 7 | | 29 | 3 | | 30 | 6 | | 31 | 6 | | 32 | 12 | | 33 | 9 | | 34 | 7 | | 35 | 6 | | 36 | 24 | | 37 | 12 | | 38 | 7 | | 39 | 11 | | 40 | 6 | | 41 | 11 | | 42 | 12 | | 43 | 6 | | 44 | 14 | | 45 | 10 | | 46 | 9 | | 47 | 7 | | 48 | 6 | | 49 | 19 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 120 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 144 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 2 | | semicolonCount | 0 | | flaggedSentences | 2 | | totalSentences | 182 | | ratio | 0.011 | | matches | | 0 | "She let her eyes roam over every bottle, every photograph on the wall—old maps of Europe, a black-and-white snapshot of two friends slung across a motorbike." | | 1 | "She glanced at the chalkboard above his head—whiskies, beers, a single cocktail named The Raven’s Shadow." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 720 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 17 | | adverbRatio | 0.02361111111111111 | | lyAdverbCount | 1 | | lyAdverbRatio | 0.001388888888888889 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 182 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 182 | | mean | 5.65 | | std | 3.4 | | cv | 0.602 | | sampleLengths | | 0 | 5 | | 1 | 9 | | 2 | 3 | | 3 | 13 | | 4 | 16 | | 5 | 5 | | 6 | 5 | | 7 | 1 | | 8 | 7 | | 9 | 9 | | 10 | 6 | | 11 | 15 | | 12 | 2 | | 13 | 5 | | 14 | 2 | | 15 | 8 | | 16 | 12 | | 17 | 26 | | 18 | 4 | | 19 | 5 | | 20 | 7 | | 21 | 2 | | 22 | 5 | | 23 | 5 | | 24 | 4 | | 25 | 2 | | 26 | 9 | | 27 | 4 | | 28 | 13 | | 29 | 11 | | 30 | 3 | | 31 | 7 | | 32 | 3 | | 33 | 4 | | 34 | 10 | | 35 | 6 | | 36 | 4 | | 37 | 9 | | 38 | 4 | | 39 | 6 | | 40 | 4 | | 41 | 9 | | 42 | 5 | | 43 | 9 | | 44 | 6 | | 45 | 1 | | 46 | 16 | | 47 | 2 | | 48 | 4 | | 49 | 11 |
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| 55.68% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 2 | | diversityRatio | 0.34065934065934067 | | totalSentences | 182 | | uniqueOpeners | 62 | |
| 64.72% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 103 | | matches | | 0 | "Then she spoke again." | | 1 | "Then she said," |
| | ratio | 0.019 | |
| 0.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 76 | | totalSentences | 103 | | matches | | 0 | "She stepped inside." | | 1 | "She drew in a breath." | | 2 | "He crooked a glance toward" | | 3 | "He knelt to rest his" | | 4 | "She crossed the distance in" | | 5 | "Her hand landed on the" | | 6 | "She let her eyes roam" | | 7 | "he answered, voice low" | | 8 | "She turned her head, searching" | | 9 | "He laid the glass down." | | 10 | "He narrowed his eyes." | | 11 | "She let her fingers trail" | | 12 | "He set another glass beside" | | 13 | "She raised her chin." | | 14 | "He examined the small crescent" | | 15 | "He traced it with a" | | 16 | "She closed her hand around" | | 17 | "He reached under the bar" | | 18 | "She glanced at the chalkboard" | | 19 | "He poured amber liquid." |
| | ratio | 0.738 | |
| 3.69% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 94 | | totalSentences | 103 | | matches | | 0 | "Aurora pushed open the door." | | 1 | "A bell above the frame" | | 2 | "She stepped inside." | | 3 | "Rows of bottles glowed like" | | 4 | "Neon green light spilled through" | | 5 | "She drew in a breath." | | 6 | "The faint hiss of condensation." | | 7 | "Silas scrubbed a glass behind" | | 8 | "He crooked a glance toward" | | 9 | "The glass hovered in his" | | 10 | "He knelt to rest his" | | 11 | "Hair streaked through with grey." | | 12 | "She crossed the distance in" | | 13 | "Her hand landed on the" | | 14 | "She let her eyes roam" | | 15 | "he answered, voice low" | | 16 | "She turned her head, searching" | | 17 | "He laid the glass down." | | 18 | "He narrowed his eyes." | | 19 | "She let her fingers trail" |
| | ratio | 0.913 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 103 | | matches | (empty) | | ratio | 0 | |
| 98.21% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 16 | | technicalSentenceCount | 1 | | matches | | 0 | "He cracked a grin that creased the corners of his eyes." |
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| 13.89% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 9 | | uselessAdditionCount | 2 | | matches | | 0 | "he answered, voice low" | | 1 | "he said, blunt" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 9 | | fancyCount | 3 | | fancyTags | | 0 | "he corrected (correct)" | | 1 | "He whispered (whisper)" | | 2 | "Whispered (whisper)" |
| | dialogueSentences | 71 | | tagDensity | 0.127 | | leniency | 0.254 | | rawRatio | 0.333 | | effectiveRatio | 0.085 | |