| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 6 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 47 | | tagDensity | 0.128 | | leniency | 0.255 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1327 | | 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) | |
| 32.18% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1327 | | totalAiIsms | 18 | | found | | | highlights | | 0 | "flickered" | | 1 | "scanning" | | 2 | "crystal" | | 3 | "rhythmic" | | 4 | "unreadable" | | 5 | "fleeting" | | 6 | "flicker" | | 7 | "silence" | | 8 | "velvet" | | 9 | "calculating" | | 10 | "whisper" | | 11 | "familiar" | | 12 | "chill" | | 13 | "predator" | | 14 | "intensity" | | 15 | "echoed" |
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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 | 75 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 75 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 117 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 42 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1327 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 5 | | unquotedAttributions | 0 | | matches | (empty) | |
| 83.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 39 | | wordCount | 908 | | uniqueNames | 8 | | maxNameDensity | 1.32 | | worstName | "Rory" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Rory" | | discoveredNames | | Golden | 1 | | Empress | 1 | | Raven | 1 | | Nest | 2 | | Soho | 1 | | Rory | 12 | | Silas | 12 | | Evan | 9 |
| | persons | | 0 | "Raven" | | 1 | "Nest" | | 2 | "Rory" | | 3 | "Silas" | | 4 | "Evan" |
| | places | | | globalScore | 0.839 | | windowScore | 0.833 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 62 | | glossingSentenceCount | 1 | | matches | | 0 | "felt like a physical blow" |
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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 | 1327 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 117 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 73 | | mean | 18.18 | | std | 15.76 | | cv | 0.867 | | sampleLengths | | 0 | 64 | | 1 | 40 | | 2 | 43 | | 3 | 4 | | 4 | 22 | | 5 | 2 | | 6 | 4 | | 7 | 56 | | 8 | 25 | | 9 | 1 | | 10 | 18 | | 11 | 1 | | 12 | 46 | | 13 | 3 | | 14 | 12 | | 15 | 30 | | 16 | 9 | | 17 | 47 | | 18 | 24 | | 19 | 6 | | 20 | 10 | | 21 | 10 | | 22 | 19 | | 23 | 66 | | 24 | 3 | | 25 | 10 | | 26 | 15 | | 27 | 5 | | 28 | 16 | | 29 | 42 | | 30 | 6 | | 31 | 11 | | 32 | 12 | | 33 | 13 | | 34 | 53 | | 35 | 25 | | 36 | 11 | | 37 | 16 | | 38 | 6 | | 39 | 4 | | 40 | 7 | | 41 | 30 | | 42 | 42 | | 43 | 29 | | 44 | 8 | | 45 | 2 | | 46 | 15 | | 47 | 28 | | 48 | 23 | | 49 | 5 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 75 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 148 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 1 | | flaggedSentences | 1 | | totalSentences | 117 | | ratio | 0.009 | | matches | | 0 | "She knew the architecture of his apologies; they were built like labyrinths, designed to make the victim feel lost until they accepted the only exit he provided." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 731 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 16 | | adverbRatio | 0.02188782489740082 | | lyAdverbCount | 4 | | lyAdverbRatio | 0.005471956224350205 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 117 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 117 | | mean | 11.34 | | std | 7.35 | | cv | 0.648 | | sampleLengths | | 0 | 26 | | 1 | 22 | | 2 | 16 | | 3 | 18 | | 4 | 22 | | 5 | 18 | | 6 | 25 | | 7 | 4 | | 8 | 22 | | 9 | 2 | | 10 | 4 | | 11 | 16 | | 12 | 16 | | 13 | 13 | | 14 | 6 | | 15 | 5 | | 16 | 3 | | 17 | 16 | | 18 | 6 | | 19 | 1 | | 20 | 7 | | 21 | 11 | | 22 | 1 | | 23 | 11 | | 24 | 24 | | 25 | 11 | | 26 | 3 | | 27 | 12 | | 28 | 19 | | 29 | 11 | | 30 | 9 | | 31 | 6 | | 32 | 19 | | 33 | 7 | | 34 | 15 | | 35 | 7 | | 36 | 17 | | 37 | 6 | | 38 | 10 | | 39 | 10 | | 40 | 19 | | 41 | 12 | | 42 | 23 | | 43 | 4 | | 44 | 27 | | 45 | 3 | | 46 | 10 | | 47 | 3 | | 48 | 12 | | 49 | 5 |
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| 39.32% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 14 | | diversityRatio | 0.3076923076923077 | | totalSentences | 117 | | uniqueOpeners | 36 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 73 | | matches | (empty) | | ratio | 0 | |
| 28.22% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 35 | | totalSentences | 73 | | matches | | 0 | "She marched toward the green" | | 1 | "She pushed inside, the sudden" | | 2 | "He polished a crystal tumbler" | | 3 | "He sat in a deep" | | 4 | "He wore a navy cashmere" | | 5 | "He didn't look like a" | | 6 | "He looked like a ghost." | | 7 | "His face had sharpened, the" | | 8 | "He slid out of the" | | 9 | "He stopped a few feet" | | 10 | "He smelled of sandalwood and" | | 11 | "He let out a soft," | | 12 | "He didn't say a word," | | 13 | "He knew exactly who the" | | 14 | "He probably knew the brand" | | 15 | "He reached out as if" | | 16 | "He looked at her, and" | | 17 | "It was a trap." | | 18 | "She knew the architecture of" | | 19 | "He turned to Silas, his" |
| | ratio | 0.479 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 69 | | totalSentences | 73 | | matches | | 0 | "Rory slammed the heavy glass" | | 1 | "She marched toward the green" | | 2 | "The sign flickered, casting a" | | 3 | "She pushed inside, the sudden" | | 4 | "The Nest felt smaller tonight," | | 5 | "Silas stood behind the bar," | | 6 | "He polished a crystal tumbler" | | 7 | "Rory leaned against the polished" | | 8 | "He sat in a deep" | | 9 | "He wore a navy cashmere" | | 10 | "He didn't look like a" | | 11 | "He looked like a ghost." | | 12 | "The man turned." | | 13 | "His face had sharpened, the" | | 14 | "The name felt like a" | | 15 | "Rory froze, her fingers tightening" | | 16 | "He slid out of the" | | 17 | "He stopped a few feet" | | 18 | "He smelled of sandalwood and" | | 19 | "He let out a soft," |
| | ratio | 0.945 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 73 | | matches | (empty) | | ratio | 0 | |
| 94.16% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 44 | | technicalSentenceCount | 3 | | matches | | 0 | "He wore a navy cashmere coat that cost more than Rory's annual rent." | | 1 | "He recognized the authority in the older man's posture, the way he occupied the space behind the bar as if it were a fortress." | | 2 | "The bookshelf that led to the secret room groaned, and the sound of splintering wood filled the air." |
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| 41.67% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 6 | | uselessAdditionCount | 1 | | matches | | 0 | "Silas replied, his voice a low rasp" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 3 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 47 | | tagDensity | 0.064 | | leniency | 0.128 | | rawRatio | 0 | | effectiveRatio | 0 | |