| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 7 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 37 | | tagDensity | 0.189 | | leniency | 0.378 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 87.06% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 773 | | totalAiIsmAdverbs | 2 | | 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) | |
| 74.13% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 773 | | totalAiIsms | 4 | | found | | | highlights | | |
| 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 | 70 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 70 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 100 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 28 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 770 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 5 | | unquotedAttributions | 0 | | matches | (empty) | |
| 39.50% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 28 | | wordCount | 543 | | uniqueNames | 4 | | maxNameDensity | 2.21 | | worstName | "Rory" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Rory" | | discoveredNames | | | persons | | 0 | "Raven" | | 1 | "Nest" | | 2 | "Rory" | | 3 | "Silas" |
| | places | (empty) | | globalScore | 0.395 | | windowScore | 0.5 | |
| 85.90% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 39 | | glossingSentenceCount | 1 | | matches | | 0 | "as if brushing away the words" |
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| 70.13% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 1.299 | | wordCount | 770 | | matches | | 0 | "not uncomfortable, but heavy" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 100 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 50 | | mean | 15.4 | | std | 12.21 | | cv | 0.793 | | sampleLengths | | 0 | 69 | | 1 | 6 | | 2 | 47 | | 3 | 1 | | 4 | 28 | | 5 | 5 | | 6 | 13 | | 7 | 28 | | 8 | 18 | | 9 | 18 | | 10 | 5 | | 11 | 2 | | 12 | 30 | | 13 | 5 | | 14 | 19 | | 15 | 9 | | 16 | 27 | | 17 | 9 | | 18 | 10 | | 19 | 12 | | 20 | 2 | | 21 | 13 | | 22 | 25 | | 23 | 14 | | 24 | 12 | | 25 | 17 | | 26 | 7 | | 27 | 15 | | 28 | 11 | | 29 | 16 | | 30 | 2 | | 31 | 23 | | 32 | 13 | | 33 | 12 | | 34 | 8 | | 35 | 9 | | 36 | 19 | | 37 | 3 | | 38 | 17 | | 39 | 36 | | 40 | 13 | | 41 | 14 | | 42 | 12 | | 43 | 18 | | 44 | 10 | | 45 | 17 | | 46 | 7 | | 47 | 33 | | 48 | 5 | | 49 | 6 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 70 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 108 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 100 | | ratio | 0 | | matches | (empty) | |
| 91.49% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 543 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 27 | | adverbRatio | 0.049723756906077346 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.009208103130755065 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 100 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 100 | | mean | 7.7 | | std | 5.71 | | cv | 0.741 | | sampleLengths | | 0 | 26 | | 1 | 23 | | 2 | 20 | | 3 | 6 | | 4 | 19 | | 5 | 28 | | 6 | 1 | | 7 | 9 | | 8 | 19 | | 9 | 5 | | 10 | 8 | | 11 | 5 | | 12 | 13 | | 13 | 15 | | 14 | 14 | | 15 | 4 | | 16 | 8 | | 17 | 10 | | 18 | 2 | | 19 | 3 | | 20 | 2 | | 21 | 5 | | 22 | 8 | | 23 | 17 | | 24 | 5 | | 25 | 2 | | 26 | 2 | | 27 | 7 | | 28 | 8 | | 29 | 5 | | 30 | 4 | | 31 | 13 | | 32 | 14 | | 33 | 3 | | 34 | 6 | | 35 | 2 | | 36 | 3 | | 37 | 5 | | 38 | 8 | | 39 | 4 | | 40 | 2 | | 41 | 10 | | 42 | 3 | | 43 | 3 | | 44 | 7 | | 45 | 9 | | 46 | 3 | | 47 | 3 | | 48 | 5 | | 49 | 9 |
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| 60.67% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 1 | | diversityRatio | 0.37 | | totalSentences | 100 | | uniqueOpeners | 37 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 60 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 15 | | totalSentences | 60 | | matches | | 0 | "She didn’t see him at" | | 1 | "His auburn hair was streaked" | | 2 | "His gaze flicked up, hazel" | | 3 | "She wiped her hands on" | | 4 | "She’d just never thought he’d" | | 5 | "His jaw tightened." | | 6 | "She hadn’t known." | | 7 | "He waved a hand, as" | | 8 | "She turned away, busying herself" | | 9 | "Her hands stilled." | | 10 | "He reached into his pocket," | | 11 | "He lit the cigarette, the" | | 12 | "She’d known him when he" | | 13 | "She didn’t have to." | | 14 | "He was watching her too." |
| | ratio | 0.25 | |
| 51.67% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 49 | | totalSentences | 60 | | matches | | 0 | "The Raven’s Nest hummed with" | | 1 | "Rory wiped her hands on" | | 2 | "The green neon sign outside" | | 3 | "She didn’t see him at" | | 4 | "His auburn hair was streaked" | | 5 | "His gaze flicked up, hazel" | | 6 | "A beat of silence stretched" | | 7 | "Rory set the tray down" | | 8 | "Silas exhaled a slow stream" | | 9 | "She wiped her hands on" | | 10 | "A ghost of a smile" | | 11 | "The question hung there, heavy." | | 12 | "Rory turned away, busying herself" | | 13 | "The Raven’s Nest had always" | | 14 | "She’d just never thought he’d" | | 15 | "Silas stubbed out his cigarette." | | 16 | "His jaw tightened." | | 17 | "She hadn’t known." | | 18 | "Silas must have seen it" | | 19 | "He waved a hand, as" |
| | ratio | 0.817 | |
| 83.33% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 60 | | matches | | 0 | "Because she knew what it" |
| | ratio | 0.017 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 12 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 53.57% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 7 | | uselessAdditionCount | 1 | | matches | | 0 | "He lit, the flame flickering in his eyes" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 3 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 37 | | tagDensity | 0.081 | | leniency | 0.162 | | rawRatio | 0 | | effectiveRatio | 0 | |