| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 5 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 17 | | tagDensity | 0.294 | | leniency | 0.588 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1693 | | 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) | |
| 58.65% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1693 | | totalAiIsms | 14 | | found | | | highlights | | 0 | "familiar" | | 1 | "quivered" | | 2 | "warmth" | | 3 | "trembled" | | 4 | "pulse" | | 5 | "weight" | | 6 | "flickered" | | 7 | "measured" | | 8 | "wavered" | | 9 | "pulsed" |
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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 | 203 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 2 | | narrationSentences | 203 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 215 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 27 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1693 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 5 | | unquotedAttributions | 0 | | matches | (empty) | |
| 66.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 32 | | wordCount | 1650 | | uniqueNames | 6 | | maxNameDensity | 1.39 | | worstName | "Aurora" | | maxWindowNameDensity | 3 | | worstWindowName | "Aurora" | | discoveredNames | | Aurora | 23 | | Richmond | 1 | | Park | 1 | | Heartstone | 4 | | Leave | 1 | | Eva | 2 |
| | persons | | 0 | "Aurora" | | 1 | "Heartstone" | | 2 | "Eva" |
| | places | | 0 | "Richmond" | | 1 | "Park" | | 2 | "Leave" |
| | globalScore | 0.803 | | windowScore | 0.667 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 134 | | glossingSentenceCount | 1 | | matches | | 0 | "sounded like Eva: a little breathless, a l" |
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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 | 1693 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 2 | | totalSentences | 215 | | matches | | 0 | "planted that afternoon" | | 1 | "read that line" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 104 | | mean | 16.28 | | std | 16.56 | | cv | 1.017 | | sampleLengths | | 0 | 8 | | 1 | 42 | | 2 | 12 | | 3 | 3 | | 4 | 57 | | 5 | 16 | | 6 | 72 | | 7 | 7 | | 8 | 10 | | 9 | 61 | | 10 | 9 | | 11 | 28 | | 12 | 7 | | 13 | 8 | | 14 | 65 | | 15 | 19 | | 16 | 46 | | 17 | 6 | | 18 | 8 | | 19 | 7 | | 20 | 5 | | 21 | 33 | | 22 | 7 | | 23 | 25 | | 24 | 20 | | 25 | 6 | | 26 | 4 | | 27 | 56 | | 28 | 7 | | 29 | 21 | | 30 | 5 | | 31 | 33 | | 32 | 4 | | 33 | 32 | | 34 | 8 | | 35 | 1 | | 36 | 25 | | 37 | 3 | | 38 | 6 | | 39 | 1 | | 40 | 2 | | 41 | 37 | | 42 | 6 | | 43 | 3 | | 44 | 38 | | 45 | 6 | | 46 | 15 | | 47 | 7 | | 48 | 20 | | 49 | 4 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 203 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 261 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 1 | | flaggedSentences | 1 | | totalSentences | 215 | | ratio | 0.005 | | matches | | 0 | "The path should have led her towards the boundary stones; she had checked the map three times before leaving." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1653 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 39 | | adverbRatio | 0.023593466424682397 | | lyAdverbCount | 3 | | lyAdverbRatio | 0.0018148820326678765 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 215 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 215 | | mean | 7.87 | | std | 5.14 | | cv | 0.653 | | sampleLengths | | 0 | 8 | | 1 | 9 | | 2 | 6 | | 3 | 27 | | 4 | 12 | | 5 | 3 | | 6 | 5 | | 7 | 18 | | 8 | 8 | | 9 | 8 | | 10 | 2 | | 11 | 16 | | 12 | 8 | | 13 | 8 | | 14 | 4 | | 15 | 15 | | 16 | 7 | | 17 | 21 | | 18 | 25 | | 19 | 7 | | 20 | 3 | | 21 | 7 | | 22 | 5 | | 23 | 5 | | 24 | 6 | | 25 | 19 | | 26 | 19 | | 27 | 7 | | 28 | 9 | | 29 | 2 | | 30 | 7 | | 31 | 19 | | 32 | 4 | | 33 | 3 | | 34 | 8 | | 35 | 14 | | 36 | 11 | | 37 | 22 | | 38 | 8 | | 39 | 10 | | 40 | 7 | | 41 | 12 | | 42 | 13 | | 43 | 5 | | 44 | 21 | | 45 | 7 | | 46 | 6 | | 47 | 6 | | 48 | 2 | | 49 | 7 |
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| 40.70% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 20 | | diversityRatio | 0.21395348837209302 | | totalSentences | 215 | | uniqueOpeners | 46 | |
| 54.95% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 182 | | matches | | 0 | "Just the faint tick of" | | 1 | "Instead, she held it in" | | 2 | "Then the gate clacked shut" |
| | ratio | 0.016 | |
| 92.53% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 58 | | totalSentences | 182 | | matches | | 0 | "She stopped with one hand" | | 1 | "She had shut it behind" | | 2 | "She remembered the latch scraping" | | 3 | "Their branches crowded above the" | | 4 | "Her phone showed 11:42." | | 5 | "It had not given her" | | 6 | "She had brought the note" | | 7 | "She followed the narrow track." | | 8 | "She found a gap and" | | 9 | "She swept her torch over" | | 10 | "She lowered the beam." | | 11 | "They stood between two old" | | 12 | "Their edges looked too straight" | | 13 | "They looked fresh enough to" | | 14 | "Its final line read: Leave" | | 15 | "She had read that line" | | 16 | "She knew what it asked." | | 17 | "She had come to find" | | 18 | "She raised her torch." | | 19 | "Her thumb found the small" |
| | ratio | 0.319 | |
| 20.44% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 160 | | totalSentences | 182 | | matches | | 0 | "The gate stood open when" | | 1 | "She stopped with one hand" | | 2 | "She had shut it behind" | | 3 | "She remembered the latch scraping" | | 4 | "The gate hung ajar now," | | 5 | "The trees gave no answer." | | 6 | "Their branches crowded above the" | | 7 | "Aurora stepped through and pulled" | | 8 | "The latch caught with a" | | 9 | "Her phone showed 11:42." | | 10 | "The note had given her" | | 11 | "It had not given her" | | 12 | "The handwriting looked familiar, but" | | 13 | "She had brought the note" | | 14 | "She followed the narrow track." | | 15 | "Mud gave under her boots." | | 16 | "The trees thinned, then gathered" | | 17 | "The path should have led" | | 18 | "She found a gap and" | | 19 | "A twig dragged along the" |
| | ratio | 0.879 | |
| 27.47% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 182 | | matches | | 0 | "Now it sat cool against" |
| | ratio | 0.005 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 61 | | technicalSentenceCount | 3 | | matches | | 0 | "Their branches crowded above the path, making a tunnel that swallowed the glow from the streetlamps behind her." | | 1 | "The Heartstone’s warmth had been building all evening, then fading, then building again, as if something had called from this spot." | | 2 | "Her boots pressed down flowers that sprang upright behind her." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 5 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 91.18% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 4 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 17 | | tagDensity | 0.235 | | leniency | 0.471 | | rawRatio | 0.25 | | effectiveRatio | 0.118 | |