| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 1 | | adverbTagCount | 1 | | adverbTags | | 0 | "he said finally [finally]" |
| | dialogueSentences | 32 | | tagDensity | 0.031 | | leniency | 0.063 | | rawRatio | 1 | | effectiveRatio | 0.063 | |
| 92.33% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 652 | | 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) | |
| 61.66% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 652 | | totalAiIsms | 5 | | found | | | highlights | | 0 | "flickered" | | 1 | "familiar" | | 2 | "flicker" | | 3 | "silence" | | 4 | "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 | 57 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 57 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 87 | | 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 | 2 | | markdownWords | 4 | | totalWords | 647 | | ratio | 0.006 | | matches | | 0 | "The Raven’s Nest" | | 1 | "care" |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 3 | | unquotedAttributions | 0 | | matches | (empty) | |
| 91.52% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 17 | | wordCount | 513 | | uniqueNames | 7 | | maxNameDensity | 1.17 | | worstName | "Rory" | | maxWindowNameDensity | 2 | | worstWindowName | "Rory" | | discoveredNames | | Raven | 1 | | Soho | 1 | | Carter | 1 | | Yu-Fei | 1 | | Blackwood | 1 | | Rory | 6 | | Silas | 6 |
| | persons | | 0 | "Raven" | | 1 | "Carter" | | 2 | "Yu-Fei" | | 3 | "Blackwood" | | 4 | "Rory" | | 5 | "Silas" |
| | places | | | globalScore | 0.915 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 34 | | 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 | 647 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 87 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 40 | | mean | 16.18 | | std | 15.99 | | cv | 0.989 | | sampleLengths | | 0 | 74 | | 1 | 61 | | 2 | 39 | | 3 | 1 | | 4 | 9 | | 5 | 35 | | 6 | 17 | | 7 | 5 | | 8 | 19 | | 9 | 24 | | 10 | 3 | | 11 | 12 | | 12 | 22 | | 13 | 16 | | 14 | 11 | | 15 | 14 | | 16 | 8 | | 17 | 6 | | 18 | 54 | | 19 | 6 | | 20 | 3 | | 21 | 5 | | 22 | 20 | | 23 | 1 | | 24 | 14 | | 25 | 14 | | 26 | 18 | | 27 | 9 | | 28 | 1 | | 29 | 8 | | 30 | 19 | | 31 | 17 | | 32 | 3 | | 33 | 1 | | 34 | 14 | | 35 | 17 | | 36 | 22 | | 37 | 12 | | 38 | 5 | | 39 | 8 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 57 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 81 | | matches | (empty) | |
| 44.33% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 3 | | semicolonCount | 0 | | flaggedSentences | 3 | | totalSentences | 87 | | ratio | 0.034 | | matches | | 0 | "She’d been delivering Yu-Fei’s dumplings to the back alley when the rain started—fat, insistent drops that turned the pavement into a mirror." | | 1 | "His hazel eyes locked onto hers for half a second before his expression shifted—just a flicker, like a candle in a draft." | | 2 | "But his posture was still the same—controlled, deliberate." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 518 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 14 | | adverbRatio | 0.02702702702702703 | | lyAdverbCount | 3 | | lyAdverbRatio | 0.005791505791505791 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 87 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 87 | | mean | 7.44 | | std | 5.51 | | cv | 0.741 | | sampleLengths | | 0 | 18 | | 1 | 21 | | 2 | 22 | | 3 | 13 | | 4 | 14 | | 5 | 12 | | 6 | 18 | | 7 | 17 | | 8 | 8 | | 9 | 22 | | 10 | 9 | | 11 | 1 | | 12 | 2 | | 13 | 7 | | 14 | 4 | | 15 | 19 | | 16 | 2 | | 17 | 2 | | 18 | 8 | | 19 | 13 | | 20 | 4 | | 21 | 5 | | 22 | 7 | | 23 | 11 | | 24 | 1 | | 25 | 7 | | 26 | 11 | | 27 | 6 | | 28 | 3 | | 29 | 8 | | 30 | 4 | | 31 | 15 | | 32 | 7 | | 33 | 4 | | 34 | 12 | | 35 | 5 | | 36 | 6 | | 37 | 5 | | 38 | 9 | | 39 | 3 | | 40 | 5 | | 41 | 2 | | 42 | 4 | | 43 | 18 | | 44 | 8 | | 45 | 7 | | 46 | 21 | | 47 | 6 | | 48 | 3 | | 49 | 3 |
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| 60.92% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 2 | | diversityRatio | 0.3793103448275862 | | totalSentences | 87 | | uniqueOpeners | 33 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 51 | | matches | | 0 | "Then he set the glass" | | 1 | "Just reached for a bottle" | | 2 | "Just the way she used" |
| | ratio | 0.059 | |
| 86.67% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 17 | | totalSentences | 51 | | matches | | 0 | "She’d been delivering Yu-Fei’s dumplings" | | 1 | "She shook the water from" | | 2 | "His hazel eyes locked onto" | | 3 | "He didn’t smile back." | | 4 | "She wrapped her fingers around" | | 5 | "She took a sip, the" | | 6 | "His voice was low, rough" | | 7 | "She swirled the whiskey, watching" | | 8 | "His jaw tightened." | | 9 | "She wondered if he still" | | 10 | "he said finally" | | 11 | "He didn’t press." | | 12 | "She didn’t flinch." | | 13 | "She took another sip, the" | | 14 | "He chuckled, low and rough." | | 15 | "He took a slow sip," | | 16 | "She met his gaze." |
| | ratio | 0.333 | |
| 38.43% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 43 | | totalSentences | 51 | | matches | | 0 | "The neon green sign of" | | 1 | "Rory Carter pushed through the" | | 2 | "She’d been delivering Yu-Fei’s dumplings" | | 3 | "She shook the water from" | | 4 | "The bar was half-full, the" | | 5 | "A jazz record spun lazily" | | 6 | "Rory slid onto a stool" | | 7 | "Silas Blackwood looked up from" | | 8 | "His hazel eyes locked onto" | | 9 | "He didn’t smile back." | | 10 | "She wrapped her fingers around" | | 11 | "A laugh escaped her, sharp" | | 12 | "She took a sip, the" | | 13 | "Silas leaned against the counter," | | 14 | "The silver signet ring on" | | 15 | "His voice was low, rough" | | 16 | "She swirled the whiskey, watching" | | 17 | "A beat of silence." | | 18 | "The jazz record scratched, the" | | 19 | "Silas exhaled through his nose." |
| | ratio | 0.843 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 51 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 23 | | technicalSentenceCount | 1 | | matches | | 0 | "She’d been delivering Yu-Fei’s dumplings to the back alley when the rain started—fat, insistent drops that turned the pavement into a mirror." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 1 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 1 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 32 | | tagDensity | 0.031 | | leniency | 0.063 | | rawRatio | 0 | | effectiveRatio | 0 | |