| 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 | 1489 | | 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) | |
| 86.57% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1489 | | totalAiIsms | 4 | | found | | | highlights | | 0 | "pulsed" | | 1 | "warmth" | | 2 | "chill" | | 3 | "weight" |
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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 | 156 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 2 | | narrationSentences | 156 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 160 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 26 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1489 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 0 | | unquotedAttributions | 0 | | matches | (empty) | |
| 50.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 38 | | wordCount | 1468 | | uniqueNames | 8 | | maxNameDensity | 1.57 | | worstName | "Rory" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Rory" | | discoveredNames | | Heartstone | 2 | | Richmond | 1 | | Park | 1 | | Hel | 1 | | Eva | 4 | | Rory | 23 | | Calling | 1 | | One | 5 |
| | persons | | 0 | "Heartstone" | | 1 | "Eva" | | 2 | "Rory" | | 3 | "One" |
| | places | | | globalScore | 0.717 | | windowScore | 0.5 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 112 | | 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 | 1489 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 2 | | totalSentences | 160 | | matches | | 0 | "made that noise" | | 1 | "check that she" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 58 | | mean | 25.67 | | std | 18.19 | | cv | 0.709 | | sampleLengths | | 0 | 23 | | 1 | 56 | | 2 | 18 | | 3 | 19 | | 4 | 57 | | 5 | 10 | | 6 | 2 | | 7 | 64 | | 8 | 64 | | 9 | 5 | | 10 | 4 | | 11 | 43 | | 12 | 42 | | 13 | 19 | | 14 | 29 | | 15 | 2 | | 16 | 12 | | 17 | 32 | | 18 | 2 | | 19 | 41 | | 20 | 35 | | 21 | 37 | | 22 | 14 | | 23 | 63 | | 24 | 3 | | 25 | 38 | | 26 | 41 | | 27 | 8 | | 28 | 34 | | 29 | 37 | | 30 | 51 | | 31 | 8 | | 32 | 9 | | 33 | 36 | | 34 | 34 | | 35 | 10 | | 36 | 36 | | 37 | 15 | | 38 | 1 | | 39 | 5 | | 40 | 45 | | 41 | 13 | | 42 | 16 | | 43 | 10 | | 44 | 43 | | 45 | 36 | | 46 | 45 | | 47 | 9 | | 48 | 42 | | 49 | 9 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 156 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 247 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 1 | | semicolonCount | 0 | | flaggedSentences | 1 | | totalSentences | 160 | | ratio | 0.006 | | matches | | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 300 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 6 | | adverbRatio | 0.02 | | lyAdverbCount | 0 | | lyAdverbRatio | 0 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 160 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 160 | | mean | 9.31 | | std | 5.19 | | cv | 0.558 | | sampleLengths | | 0 | 23 | | 1 | 23 | | 2 | 11 | | 3 | 7 | | 4 | 15 | | 5 | 5 | | 6 | 13 | | 7 | 16 | | 8 | 3 | | 9 | 8 | | 10 | 24 | | 11 | 12 | | 12 | 13 | | 13 | 10 | | 14 | 2 | | 15 | 11 | | 16 | 11 | | 17 | 13 | | 18 | 10 | | 19 | 19 | | 20 | 9 | | 21 | 8 | | 22 | 17 | | 23 | 13 | | 24 | 17 | | 25 | 5 | | 26 | 4 | | 27 | 2 | | 28 | 12 | | 29 | 6 | | 30 | 23 | | 31 | 6 | | 32 | 12 | | 33 | 7 | | 34 | 17 | | 35 | 5 | | 36 | 5 | | 37 | 5 | | 38 | 4 | | 39 | 5 | | 40 | 11 | | 41 | 13 | | 42 | 2 | | 43 | 7 | | 44 | 5 | | 45 | 4 | | 46 | 11 | | 47 | 6 | | 48 | 11 | | 49 | 2 |
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| 48.75% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 2 | | diversityRatio | 0.3 | | totalSentences | 160 | | uniqueOpeners | 48 | |
| 21.79% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 153 | | matches | | 0 | "Even the wind stopped at" |
| | ratio | 0.007 | |
| 99.74% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 46 | | totalSentences | 153 | | matches | | 0 | "It moved the grass against" | | 1 | "She checked the receipt again." | | 2 | "She had found the writing" | | 3 | "She folded it and put" | | 4 | "Her voice reached the nearest" | | 5 | "She looked back through the" | | 6 | "Her bike waited against a" | | 7 | "She had left it with" | | 8 | "She pulled it out by" | | 9 | "Its crimson stone carried a" | | 10 | "She had worn it for" | | 11 | "She stepped between two pillars." | | 12 | "She knew what that could" | | 13 | "She looked at the ground" | | 14 | "Its top disappeared into the" | | 15 | "She counted from the gap." | | 16 | "She loosened her grip on" | | 17 | "Their heads dipped in a" | | 18 | "She saw bare earth and" | | 19 | "She took out her phone." |
| | ratio | 0.301 | |
| 71.11% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 119 | | totalSentences | 153 | | matches | | 0 | "Rory reached the edge of" | | 1 | "The park behind her had" | | 2 | "Here, beyond the ring of" | | 3 | "It moved the grass against" | | 4 | "She checked the receipt again." | | 5 | "A crease ran through the" | | 6 | "Yu-Fei’s till had printed the" | | 7 | "Rory had watched it curl" | | 8 | "She had found the writing" | | 9 | "The ink had marked the" | | 10 | "She folded it and put" | | 11 | "Her voice reached the nearest" | | 12 | "She looked back through the" | | 13 | "Her bike waited against a" | | 14 | "She had left it with" | | 15 | "The pendant rested against her" | | 16 | "She pulled it out by" | | 17 | "Its crimson stone carried a" | | 18 | "She had worn it for" | | 19 | "She stepped between two pillars." |
| | ratio | 0.778 | |
| 65.36% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 153 | | matches | | 0 | "If you want to know" | | 1 | "If I’m not back by—" |
| | ratio | 0.013 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 67 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 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 | |