| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1749 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 100.00% | AI-ism character names | Target: 0 AI-default names (17 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 91.42% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1749 | | totalAiIsms | 3 | | found | | | highlights | | |
| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 187 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 187 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 193 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 41 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1749 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 0 | | unquotedAttributions | 0 | | matches | (empty) | |
| 74.77% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 27 | | wordCount | 1728 | | uniqueNames | 2 | | maxNameDensity | 1.5 | | worstName | "Rory" | | maxWindowNameDensity | 2 | | worstWindowName | "Rory" | | discoveredNames | | | persons | | | places | (empty) | | globalScore | 0.748 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 133 | | glossingSentenceCount | 1 | | matches | | 0 | "looked like bark until she touched it" |
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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 | 1749 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 2 | | totalSentences | 193 | | matches | | 0 | "crossed that patch" | | 1 | "filled that slit" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 83 | | mean | 21.07 | | std | 15.67 | | cv | 0.744 | | sampleLengths | | 0 | 47 | | 1 | 12 | | 2 | 9 | | 3 | 27 | | 4 | 11 | | 5 | 3 | | 6 | 54 | | 7 | 48 | | 8 | 50 | | 9 | 29 | | 10 | 36 | | 11 | 42 | | 12 | 28 | | 13 | 10 | | 14 | 19 | | 15 | 4 | | 16 | 30 | | 17 | 56 | | 18 | 15 | | 19 | 49 | | 20 | 14 | | 21 | 17 | | 22 | 2 | | 23 | 43 | | 24 | 4 | | 25 | 24 | | 26 | 34 | | 27 | 19 | | 28 | 2 | | 29 | 5 | | 30 | 39 | | 31 | 16 | | 32 | 28 | | 33 | 3 | | 34 | 13 | | 35 | 48 | | 36 | 11 | | 37 | 15 | | 38 | 3 | | 39 | 9 | | 40 | 3 | | 41 | 6 | | 42 | 2 | | 43 | 30 | | 44 | 3 | | 45 | 42 | | 46 | 35 | | 47 | 16 | | 48 | 28 | | 49 | 39 |
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| 99.63% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 187 | | matches | | 0 | "was written" | | 1 | "been taken" | | 2 | "WERE MEANT" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 292 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 2 | | flaggedSentences | 2 | | totalSentences | 193 | | ratio | 0.01 | | matches | | 0 | "She had called it twice on the bus; both times, a recorded voice had told her the number did not exist." | | 1 | "She shifted the phone to one side; the narrow shadow slid across the flowers." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1731 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 37 | | adverbRatio | 0.021374927787406125 | | lyAdverbCount | 1 | | lyAdverbRatio | 0.0005777007510109763 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 193 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 193 | | mean | 9.06 | | std | 5.47 | | cv | 0.604 | | sampleLengths | | 0 | 18 | | 1 | 9 | | 2 | 20 | | 3 | 5 | | 4 | 7 | | 5 | 6 | | 6 | 3 | | 7 | 2 | | 8 | 4 | | 9 | 21 | | 10 | 5 | | 11 | 6 | | 12 | 3 | | 13 | 5 | | 14 | 14 | | 15 | 17 | | 16 | 12 | | 17 | 6 | | 18 | 22 | | 19 | 5 | | 20 | 21 | | 21 | 40 | | 22 | 10 | | 23 | 10 | | 24 | 7 | | 25 | 12 | | 26 | 4 | | 27 | 18 | | 28 | 3 | | 29 | 11 | | 30 | 9 | | 31 | 3 | | 32 | 18 | | 33 | 12 | | 34 | 9 | | 35 | 10 | | 36 | 9 | | 37 | 10 | | 38 | 5 | | 39 | 11 | | 40 | 3 | | 41 | 4 | | 42 | 10 | | 43 | 7 | | 44 | 13 | | 45 | 4 | | 46 | 20 | | 47 | 11 | | 48 | 9 | | 49 | 12 |
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| 44.82% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 10 | | diversityRatio | 0.27979274611398963 | | totalSentences | 193 | | uniqueOpeners | 54 | |
| 18.42% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 181 | | matches | | | ratio | 0.006 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 52 | | totalSentences | 181 | | matches | | 0 | "Its surface looked like bark" | | 1 | "Her phone showed eleven fifty-eight." | | 2 | "She had called it twice" | | 3 | "She checked the screen again." | | 4 | "She had found the pendant" | | 5 | "She followed a narrow gap" | | 6 | "Their pale heads caught what" | | 7 | "It was February." | | 8 | "She could still see the" | | 9 | "She took out her phone" | | 10 | "Her voice carried across the" | | 11 | "She followed its flight with" | | 12 | "Her boot prints marked the" | | 13 | "She turned to look at" | | 14 | "She pressed one finger into" | | 15 | "It was firm and cold," | | 16 | "She stayed crouched." | | 17 | "She could see the pale" | | 18 | "She stood and took three" | | 19 | "They came from behind, each" |
| | ratio | 0.287 | |
| 40.11% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 152 | | totalSentences | 181 | | matches | | 0 | "Rory found the first standing" | | 1 | "Its surface looked like bark" | | 2 | "The ridges held the cold" | | 3 | "Her phone showed eleven fifty-eight." | | 4 | "The message had given her" | | 5 | "She had called it twice" | | 6 | "She checked the screen again." | | 7 | "The park offered no answer." | | 8 | "A plane crossed somewhere beyond" | | 9 | "Rory slipped her phone into" | | 10 | "The crimson stone rested against" | | 11 | "A faint light stirred inside" | | 12 | "She had found the pendant" | | 13 | "Yu-Fei had thought it was" | | 14 | "Rory wanted to know who" | | 15 | "Another standing stone rose through" | | 16 | "An oak root curled around" | | 17 | "She followed a narrow gap" | | 18 | "Wildflowers covered the clearing." | | 19 | "Their pale heads caught what" |
| | ratio | 0.84 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 181 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 76 | | technicalSentenceCount | 2 | | matches | | 0 | "She watched them settle and listened for breathing, a rustle of clothing, anything that might give her a direction." | | 1 | "Halfway across the clearing, she noticed a sound beneath her steps: a thin, steady scraping, as though someone dragged a fingernail over wood." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 0 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |