| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 20 | | adverbTagCount | 2 | | adverbTags | | 0 | "Silas said flatly [flatly]" | | 1 | "she said finally [finally]" |
| | dialogueSentences | 46 | | tagDensity | 0.435 | | leniency | 0.87 | | rawRatio | 0.1 | | effectiveRatio | 0.087 | |
| 79.82% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 991 | | totalAiIsmAdverbs | 4 | | found | | | highlights | | 0 | "really" | | 1 | "slowly" | | 2 | "carefully" |
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| 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) | |
| 59.64% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 991 | | totalAiIsms | 8 | | found | | | highlights | | 0 | "chill" | | 1 | "warmth" | | 2 | "could feel" | | 3 | "weight" | | 4 | "unreadable" | | 5 | "silence" | | 6 | "footsteps" |
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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 | 1 | | narrationSentences | 92 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 92 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 119 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 24 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 984 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 13 | | unquotedAttributions | 0 | | matches | (empty) | |
| 66.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 29 | | wordCount | 789 | | uniqueNames | 7 | | maxNameDensity | 1.65 | | worstName | "Silas" | | maxWindowNameDensity | 3 | | worstWindowName | "Silas" | | discoveredNames | | Raven | 1 | | Nest | 1 | | Carter | 1 | | November | 1 | | Rory | 4 | | Silas | 13 | | Evan | 8 |
| | persons | | 0 | "Raven" | | 1 | "Nest" | | 2 | "Carter" | | 3 | "November" | | 4 | "Rory" | | 5 | "Silas" | | 6 | "Evan" |
| | places | (empty) | | globalScore | 0.676 | | windowScore | 0.667 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 58 | | glossingSentenceCount | 1 | | matches | | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 984 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 119 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 52 | | mean | 18.92 | | std | 15.64 | | cv | 0.827 | | sampleLengths | | 0 | 76 | | 1 | 48 | | 2 | 22 | | 3 | 31 | | 4 | 20 | | 5 | 9 | | 6 | 10 | | 7 | 42 | | 8 | 10 | | 9 | 30 | | 10 | 13 | | 11 | 37 | | 12 | 3 | | 13 | 19 | | 14 | 3 | | 15 | 34 | | 16 | 15 | | 17 | 23 | | 18 | 13 | | 19 | 37 | | 20 | 3 | | 21 | 25 | | 22 | 6 | | 23 | 20 | | 24 | 4 | | 25 | 9 | | 26 | 4 | | 27 | 61 | | 28 | 11 | | 29 | 6 | | 30 | 15 | | 31 | 25 | | 32 | 10 | | 33 | 17 | | 34 | 2 | | 35 | 14 | | 36 | 38 | | 37 | 7 | | 38 | 17 | | 39 | 6 | | 40 | 14 | | 41 | 16 | | 42 | 39 | | 43 | 13 | | 44 | 7 | | 45 | 12 | | 46 | 7 | | 47 | 44 | | 48 | 19 | | 49 | 8 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 92 | | matches | | |
| 31.22% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 4 | | totalVerbs | 158 | | matches | | 0 | "was polishing" | | 1 | "was like looking" | | 2 | "wasn’t running" | | 3 | "was choosing" |
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| 22.81% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 7 | | semicolonCount | 0 | | flaggedSentences | 5 | | totalSentences | 119 | | ratio | 0.042 | | matches | | 0 | "His hazel gaze was as steady as ever, but there was something new there—something guarded." | | 1 | "Rory didn’t turn—she wasn’t interested in whoever had just walked in—but then she heard a voice that made her spine stiffen." | | 2 | "But his eyes—those were the same." | | 3 | "\"Right.\" He leaned in, close enough that she could smell the cologne he’d always worn—something woodsy, expensive." | | 4 | "She looked at him—really looked at him—and saw the ghost of the boy she’d loved." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 521 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 19 | | adverbRatio | 0.036468330134357005 | | lyAdverbCount | 2 | | lyAdverbRatio | 0.003838771593090211 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 119 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 119 | | mean | 8.27 | | std | 5.35 | | cv | 0.647 | | sampleLengths | | 0 | 10 | | 1 | 24 | | 2 | 21 | | 3 | 21 | | 4 | 18 | | 5 | 15 | | 6 | 11 | | 7 | 4 | | 8 | 3 | | 9 | 5 | | 10 | 14 | | 11 | 10 | | 12 | 15 | | 13 | 6 | | 14 | 14 | | 15 | 6 | | 16 | 3 | | 17 | 6 | | 18 | 10 | | 19 | 11 | | 20 | 10 | | 21 | 21 | | 22 | 4 | | 23 | 6 | | 24 | 8 | | 25 | 22 | | 26 | 7 | | 27 | 6 | | 28 | 8 | | 29 | 8 | | 30 | 21 | | 31 | 3 | | 32 | 4 | | 33 | 15 | | 34 | 3 | | 35 | 10 | | 36 | 7 | | 37 | 7 | | 38 | 6 | | 39 | 4 | | 40 | 10 | | 41 | 5 | | 42 | 6 | | 43 | 17 | | 44 | 8 | | 45 | 5 | | 46 | 11 | | 47 | 19 | | 48 | 7 | | 49 | 3 |
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| 59.38% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 6 | | diversityRatio | 0.3865546218487395 | | totalSentences | 119 | | uniqueOpeners | 46 | |
| 80.32% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 83 | | matches | | 0 | "Slowly, she turned." | | 1 | "Dark, intense, always searching." |
| | ratio | 0.024 | |
| 0.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 46 | | totalSentences | 83 | | matches | | 0 | "She shook the rain from" | | 1 | "She slid onto a stool" | | 2 | "He didn’t look up, but" | | 3 | "She hadn’t been in traffic." | | 4 | "She’d been standing outside for" | | 5 | "His hazel gaze was as" | | 6 | "She rubbed the small crescent" | | 7 | "He didn’t move." | | 8 | "She forced a smile, but" | | 9 | "He slid it across to" | | 10 | "She took a sip." | | 11 | "It burned all the way" | | 12 | "She opened her mouth, then" | | 13 | "She knew that voice." | | 14 | "He was taller than she" | | 15 | "His hair was shorter, his" | | 16 | "He grinned, and it was" | | 17 | "Her fingers tightened around the" | | 18 | "She could feel Silas watching" | | 19 | "she said, and her voice" |
| | ratio | 0.554 | |
| 8.19% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 75 | | totalSentences | 83 | | matches | | 0 | "The Raven's Nest smelled of" | | 1 | "Aurora Carter pushed through the" | | 2 | "She shook the rain from" | | 3 | "The place was half-empty-just a" | | 4 | "She slid onto a stool" | | 5 | "Silas was polishing a glass," | | 6 | "He didn’t look up, but" | | 7 | "She hadn’t been in traffic." | | 8 | "She’d been standing outside for" | | 9 | "Silas set the glass down" | | 10 | "His hazel gaze was as" | | 11 | "She rubbed the small crescent" | | 12 | "He didn’t move." | | 13 | "She forced a smile, but" | | 14 | "Silas exhaled through his nose" | | 15 | "The liquid was dark, almost" | | 16 | "He slid it across to" | | 17 | "She took a sip." | | 18 | "It burned all the way" | | 19 | "Silas leaned against the back" |
| | ratio | 0.904 | |
| 60.24% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 83 | | matches | | 0 | "Before she could answer, the" |
| | ratio | 0.012 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 32 | | technicalSentenceCount | 1 | | matches | | 0 | "He slapped his ID on the counter, and Silas took his time examining it before pouring the drink." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 20 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 41.30% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 10 | | fancyCount | 5 | | fancyTags | | 0 | "Rory lied (lie)" | | 1 | "he observed (observe)" | | 2 | "she corrected (correct)" | | 3 | "He whistled (whistle)" | | 4 | "he murmured (murmur)" |
| | dialogueSentences | 46 | | tagDensity | 0.217 | | leniency | 0.435 | | rawRatio | 0.5 | | effectiveRatio | 0.217 | |