| 50.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 12 | | adverbTagCount | 3 | | adverbTags | | 0 | "he said quietly [quietly]" | | 1 | "she asked instead [instead]" | | 2 | "she said softly [softly]" |
| | dialogueSentences | 40 | | tagDensity | 0.3 | | leniency | 0.6 | | rawRatio | 0.25 | | effectiveRatio | 0.15 | |
| 95.02% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1005 | | totalAiIsmAdverbs | 1 | | found | | | highlights | | |
| 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) | |
| 45.27% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1005 | | totalAiIsms | 11 | | found | | | highlights | | 0 | "tracing" | | 1 | "silk" | | 2 | "charm" | | 3 | "scanned" | | 4 | "flickered" | | 5 | "glinting" | | 6 | "weight" | | 7 | "silence" | | 8 | "echoed" | | 9 | "pounding" | | 10 | "traced" |
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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 | 80 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 2 | | narrationSentences | 80 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 108 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 31 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 1 | | markdownWords | 1 | | totalWords | 996 | | ratio | 0.001 | | matches | | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 16 | | unquotedAttributions | 0 | | matches | (empty) | |
| 83.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 32 | | wordCount | 841 | | uniqueNames | 8 | | maxNameDensity | 1.31 | | worstName | "Evan" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Evan" | | discoveredNames | | Raven | 1 | | Nest | 2 | | Golden | 1 | | Empress | 1 | | London | 1 | | Evan | 11 | | Rory | 10 | | Silas | 5 |
| | persons | | 0 | "Raven" | | 1 | "Nest" | | 2 | "Evan" | | 3 | "Rory" | | 4 | "Silas" |
| | places | | | globalScore | 0.846 | | windowScore | 0.833 | |
| 0.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 46 | | glossingSentenceCount | 3 | | matches | | 0 | "something like regret—but it was gone before" | | 1 | "appeared behind the bar, his hazel eyes flicking between them with the quiet assessment of a man who’d spent a lifetime reading people" | | 2 | "looked like a man who’d seen too much and" |
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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 | 996 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 108 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 46 | | mean | 21.65 | | std | 22.28 | | cv | 1.029 | | sampleLengths | | 0 | 120 | | 1 | 20 | | 2 | 1 | | 3 | 65 | | 4 | 56 | | 5 | 38 | | 6 | 15 | | 7 | 18 | | 8 | 49 | | 9 | 9 | | 10 | 14 | | 11 | 50 | | 12 | 6 | | 13 | 34 | | 14 | 24 | | 15 | 9 | | 16 | 1 | | 17 | 4 | | 18 | 41 | | 19 | 5 | | 20 | 11 | | 21 | 11 | | 22 | 3 | | 23 | 56 | | 24 | 9 | | 25 | 7 | | 26 | 6 | | 27 | 6 | | 28 | 1 | | 29 | 5 | | 30 | 11 | | 31 | 35 | | 32 | 9 | | 33 | 8 | | 34 | 28 | | 35 | 5 | | 36 | 9 | | 37 | 9 | | 38 | 34 | | 39 | 14 | | 40 | 14 | | 41 | 20 | | 42 | 7 | | 43 | 42 | | 44 | 33 | | 45 | 24 |
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| 92.11% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 80 | | matches | | 0 | "was gone" | | 1 | "was cropped" | | 2 | "was gone" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 162 | | matches | | 0 | "was listening" | | 1 | "was doing" |
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| 37.04% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 6 | | semicolonCount | 0 | | flaggedSentences | 4 | | totalSentences | 108 | | ratio | 0.037 | | matches | | 0 | "But the Nest had a way of holding onto people, like a spider’s silk—soft, almost unnoticeable, until you tried to pull away." | | 1 | "His dark hair was cropped short, his jaw shadowed with stubble, and his eyes—once warm, now cold—scanned the room with the precision of a man who expected trouble." | | 2 | "For a second, his expression flickered—surprise, maybe even something like regret—but it was gone before she could be sure." | | 3 | "She knew what he was doing—poking, prodding, looking for a reaction." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 850 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 20 | | adverbRatio | 0.023529411764705882 | | lyAdverbCount | 4 | | lyAdverbRatio | 0.004705882352941176 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 108 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 108 | | mean | 9.22 | | std | 7.7 | | cv | 0.835 | | sampleLengths | | 0 | 28 | | 1 | 22 | | 2 | 20 | | 3 | 7 | | 4 | 21 | | 5 | 22 | | 6 | 20 | | 7 | 1 | | 8 | 3 | | 9 | 3 | | 10 | 10 | | 11 | 28 | | 12 | 21 | | 13 | 6 | | 14 | 4 | | 15 | 13 | | 16 | 4 | | 17 | 29 | | 18 | 5 | | 19 | 19 | | 20 | 14 | | 21 | 9 | | 22 | 6 | | 23 | 8 | | 24 | 10 | | 25 | 31 | | 26 | 18 | | 27 | 9 | | 28 | 9 | | 29 | 5 | | 30 | 24 | | 31 | 17 | | 32 | 9 | | 33 | 4 | | 34 | 2 | | 35 | 26 | | 36 | 5 | | 37 | 3 | | 38 | 10 | | 39 | 6 | | 40 | 8 | | 41 | 4 | | 42 | 5 | | 43 | 1 | | 44 | 2 | | 45 | 2 | | 46 | 18 | | 47 | 12 | | 48 | 8 | | 49 | 3 |
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| 45.06% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 8 | | diversityRatio | 0.3148148148148148 | | totalSentences | 108 | | uniqueOpeners | 34 | |
| 45.66% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 73 | | matches | | 0 | "Just a quick drink after" |
| | ratio | 0.014 | |
| 22.74% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 36 | | totalSentences | 73 | | matches | | 0 | "She hadn’t meant to stay" | | 1 | "Her breath hitched." | | 2 | "He looked different." | | 3 | "His dark hair was cropped" | | 4 | "He wore a leather jacket," | | 5 | "She should have left." | | 6 | "She should have slipped out" | | 7 | "He crossed the room in" | | 8 | "he said, his voice rougher" | | 9 | "She forced a smile, though" | | 10 | "He slid onto the stool" | | 11 | "he said, and there was" | | 12 | "she said before she could" | | 13 | "He set a glass in" | | 14 | "he asked Rory, his voice" | | 15 | "She shook her head." | | 16 | "He studied her, his gaze" | | 17 | "She saw the moment he" | | 18 | "he said quietly" | | 19 | "She exhaled through her nose." |
| | ratio | 0.493 | |
| 1.10% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 67 | | totalSentences | 73 | | matches | | 0 | "The Raven’s Nest hummed with" | | 1 | "The green neon sign outside" | | 2 | "Rory leaned against the bar," | | 3 | "She hadn’t meant to stay" | | 4 | "The door swung open, letting" | | 5 | "Her breath hitched." | | 6 | "He looked different." | | 7 | "The boyish charm was gone," | | 8 | "His dark hair was cropped" | | 9 | "He wore a leather jacket," | | 10 | "Rory’s fingers tightened around her" | | 11 | "She should have left." | | 12 | "She should have slipped out" | | 13 | "Some part of her, the" | | 14 | "Evan’s gaze landed on her." | | 15 | "He crossed the room in" | | 16 | "he said, his voice rougher" | | 17 | "She forced a smile, though" | | 18 | "He slid onto the stool" | | 19 | "he said, and there was" |
| | ratio | 0.918 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 73 | | matches | (empty) | | ratio | 0 | |
| 53.57% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 32 | | technicalSentenceCount | 4 | | matches | | 0 | "The Raven’s Nest hummed with the low murmur of conversation and the clink of glasses, the kind of noise that settled into the bones like a second heartbeat." | | 1 | "Silas appeared behind the bar, his hazel eyes flicking between them with the quiet assessment of a man who’d spent a lifetime reading people." | | 2 | "Silas lingered for a moment, his signet ring glinting in the dim light, before he moved down the bar to polish glasses that didn’t need polishing." | | 3 | "Evan turned and walked away, his limp barely noticeable, the door swinging shut behind him with a finality that echoed in her chest." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 12 | | uselessAdditionCount | 3 | | matches | | 0 | "he said, his voice rougher than she remembered" | | 1 | "he asked, his voice low" | | 2 | "he asked, his voice low" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 12 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 40 | | tagDensity | 0.3 | | leniency | 0.6 | | rawRatio | 0 | | effectiveRatio | 0 | |