| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 11 | | adverbTagCount | 1 | | adverbTags | | 0 | "Eva laughed again [again]" |
| | dialogueSentences | 28 | | tagDensity | 0.393 | | leniency | 0.786 | | rawRatio | 0.091 | | effectiveRatio | 0.071 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 974 | | 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) | |
| 89.73% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 974 | | totalAiIsms | 2 | | 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 | 52 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 52 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 69 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 40 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 1 | | markdownWords | 1 | | totalWords | 974 | | ratio | 0.001 | | matches | | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 11 | | unquotedAttributions | 0 | | matches | (empty) | |
| 50.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 30 | | wordCount | 693 | | uniqueNames | 9 | | maxNameDensity | 1.59 | | worstName | "Eva" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Eva" | | discoveredNames | | Golden | 1 | | Empress | 1 | | Western | 1 | | Front | 1 | | Canton | 1 | | Ely | 1 | | Eva | 11 | | Rory | 10 | | Silas | 3 |
| | persons | | | places | | | globalScore | 0.706 | | windowScore | 0.5 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 33 | | 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 | 974 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 69 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 32 | | mean | 30.44 | | std | 25.41 | | cv | 0.835 | | sampleLengths | | 0 | 87 | | 1 | 47 | | 2 | 78 | | 3 | 5 | | 4 | 84 | | 5 | 20 | | 6 | 7 | | 7 | 5 | | 8 | 1 | | 9 | 28 | | 10 | 1 | | 11 | 36 | | 12 | 47 | | 13 | 33 | | 14 | 56 | | 15 | 3 | | 16 | 24 | | 17 | 6 | | 18 | 35 | | 19 | 47 | | 20 | 6 | | 21 | 52 | | 22 | 4 | | 23 | 60 | | 24 | 8 | | 25 | 58 | | 26 | 19 | | 27 | 3 | | 28 | 44 | | 29 | 37 | | 30 | 4 | | 31 | 29 |
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| 78.27% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 4 | | totalSentences | 52 | | matches | | 0 | "been worn" | | 1 | "been cropped" | | 2 | "been covered" | | 3 | "were clenched" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 109 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 69 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 694 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 17 | | adverbRatio | 0.024495677233429394 | | lyAdverbCount | 4 | | lyAdverbRatio | 0.005763688760806916 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 69 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 69 | | mean | 14.12 | | std | 10.84 | | cv | 0.768 | | sampleLengths | | 0 | 21 | | 1 | 22 | | 2 | 9 | | 3 | 12 | | 4 | 23 | | 5 | 9 | | 6 | 3 | | 7 | 16 | | 8 | 19 | | 9 | 11 | | 10 | 23 | | 11 | 4 | | 12 | 40 | | 13 | 5 | | 14 | 31 | | 15 | 26 | | 16 | 11 | | 17 | 16 | | 18 | 3 | | 19 | 17 | | 20 | 3 | | 21 | 4 | | 22 | 3 | | 23 | 2 | | 24 | 1 | | 25 | 21 | | 26 | 7 | | 27 | 1 | | 28 | 17 | | 29 | 19 | | 30 | 4 | | 31 | 13 | | 32 | 28 | | 33 | 2 | | 34 | 3 | | 35 | 30 | | 36 | 6 | | 37 | 11 | | 38 | 39 | | 39 | 3 | | 40 | 24 | | 41 | 6 | | 42 | 26 | | 43 | 9 | | 44 | 2 | | 45 | 12 | | 46 | 33 | | 47 | 6 | | 48 | 14 | | 49 | 38 |
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| 54.59% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 9 | | diversityRatio | 0.4057971014492754 | | totalSentences | 69 | | uniqueOpeners | 28 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 47 | | matches | | 0 | "Instead she took the stool" | | 1 | "Only the mouth remained the" |
| | ratio | 0.043 | |
| 75.32% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 17 | | totalSentences | 47 | | matches | | 0 | "She should have climbed the" | | 1 | "He said nothing." | | 2 | "He tilted his head toward" | | 3 | "He went back to polishing," | | 4 | "She heard the laugh before" | | 5 | "It rose from the booth" | | 6 | "She had heard it through" | | 7 | "She turned on the stool." | | 8 | "Her body had already made" | | 9 | "Her eyes dropped to the" | | 10 | "She stopped at the edge" | | 11 | "She didn't finish." | | 12 | "His left leg dragged a" | | 13 | "He didn't look at them." | | 14 | "He didn't need to." | | 15 | "Her fingers were clenched around" | | 16 | "She made them open, one" |
| | ratio | 0.362 | |
| 2.55% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 43 | | totalSentences | 47 | | matches | | 0 | "The green neon above the" | | 1 | "Rory ducked beneath it with" | | 2 | "The noodles inside had gone" | | 3 | "She should have climbed the" | | 4 | "Silas glanced up from the" | | 5 | "He said nothing." | | 6 | "He tilted his head toward" | | 7 | "He went back to polishing," | | 8 | "She heard the laugh before" | | 9 | "It rose from the booth" | | 10 | "Rory knew that laugh." | | 11 | "She had heard it through" | | 12 | "She turned on the stool." | | 13 | "Eva sat with her back" | | 14 | "The hair that used to" | | 15 | "The freckles across her nose" | | 16 | "Rory considered leaving." | | 17 | "Her body had already made" | | 18 | "Eva looked up." | | 19 | "The laugh died mid-climb." |
| | ratio | 0.915 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 47 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 25 | | technicalSentenceCount | 1 | | matches | | 0 | "Up close, Eva's face held lines Rory had never seen, faint grooves beside her mouth and between her brows, the marks of someone who had spent a long time keepin…" |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 11 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 5 | | fancyCount | 1 | | fancyTags | | 0 | "Eva laughed again (laugh)" |
| | dialogueSentences | 28 | | tagDensity | 0.179 | | leniency | 0.357 | | rawRatio | 0.2 | | effectiveRatio | 0.071 | |