| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 2 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 2 | | tagDensity | 1 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 88.91% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 902 | | totalAiIsmAdverbs | 2 | | found | | | highlights | | |
| 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) | |
| 16.85% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 902 | | totalAiIsms | 15 | | found | | | highlights | | 0 | "warmth" | | 1 | "measured" | | 2 | "footsteps" | | 3 | "pulse" | | 4 | "familiar" | | 5 | "loomed" | | 6 | "silence" | | 7 | "weight" | | 8 | "whisper" | | 9 | "flickered" | | 10 | "silk" | | 11 | "could feel" |
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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 | 83 | | matches | (empty) | |
| 74.01% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 3 | | narrationSentences | 83 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 83 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 33 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 894 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 4 | | unquotedAttributions | 0 | | matches | (empty) | |
| 99.32% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 22 | | wordCount | 888 | | uniqueNames | 11 | | maxNameDensity | 1.01 | | worstName | "Aurora" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Aurora" | | discoveredNames | | Richmond | 2 | | Park | 2 | | October | 1 | | Heartstone | 1 | | Fae | 1 | | Grove | 2 | | English | 1 | | Hel | 1 | | North | 1 | | Face | 1 | | Aurora | 9 |
| | persons | | | places | | 0 | "Richmond" | | 1 | "Park" | | 2 | "Fae" | | 3 | "Grove" | | 4 | "English" |
| | globalScore | 0.993 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 66 | | glossingSentenceCount | 1 | | matches | | 0 | "not quite a hand, the pressure all wrong, too many points of contact" |
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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 | 894 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 83 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 27 | | mean | 33.11 | | std | 19.53 | | cv | 0.59 | | sampleLengths | | 0 | 66 | | 1 | 40 | | 2 | 37 | | 3 | 4 | | 4 | 28 | | 5 | 61 | | 6 | 3 | | 7 | 37 | | 8 | 38 | | 9 | 6 | | 10 | 51 | | 11 | 53 | | 12 | 56 | | 13 | 34 | | 14 | 41 | | 15 | 33 | | 16 | 10 | | 17 | 49 | | 18 | 8 | | 19 | 50 | | 20 | 52 | | 21 | 13 | | 22 | 3 | | 23 | 43 | | 24 | 42 | | 25 | 34 | | 26 | 2 |
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| 96.81% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 83 | | matches | | 0 | "was carpeted" | | 1 | "was gone" |
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| 78.79% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 3 | | totalVerbs | 165 | | matches | | 0 | "wasn't looking" | | 1 | "was bleeding" | | 2 | "was turning" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 7 | | semicolonCount | 0 | | flaggedSentences | 6 | | totalSentences | 83 | | ratio | 0.072 | | matches | | 0 | "The familiar path looked wrong somehow—the oak she usually passed on the left now loomed on her right, and the fallen log she'd stepped over countless times was nowhere to be seen." | | 1 | "Not from wind—there was no wind tonight." | | 2 | "The ground was carpeted with wildflowers—impossible given the season—their petals glowing faintly in the darkness." | | 3 | "Aurora's light caught it full on—a person, or something wearing the shape of one." | | 4 | "She looked down to find a jacket—modern, North Face, the kind hikers wore." | | 5 | "Something touched her shoulder—not quite a hand, the pressure all wrong, too many points of contact." |
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| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 65 | | adjectiveStacks | 1 | | stackExamples | | | adverbCount | 2 | | adverbRatio | 0.03076923076923077 | | lyAdverbCount | 0 | | lyAdverbRatio | 0 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 83 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 83 | | mean | 10.77 | | std | 6.27 | | cv | 0.582 | | sampleLengths | | 0 | 21 | | 1 | 18 | | 2 | 27 | | 3 | 6 | | 4 | 19 | | 5 | 15 | | 6 | 5 | | 7 | 3 | | 8 | 12 | | 9 | 17 | | 10 | 4 | | 11 | 10 | | 12 | 11 | | 13 | 7 | | 14 | 11 | | 15 | 18 | | 16 | 32 | | 17 | 3 | | 18 | 12 | | 19 | 1 | | 20 | 9 | | 21 | 5 | | 22 | 1 | | 23 | 1 | | 24 | 1 | | 25 | 7 | | 26 | 4 | | 27 | 7 | | 28 | 19 | | 29 | 8 | | 30 | 6 | | 31 | 7 | | 32 | 7 | | 33 | 15 | | 34 | 22 | | 35 | 16 | | 36 | 12 | | 37 | 25 | | 38 | 8 | | 39 | 13 | | 40 | 15 | | 41 | 4 | | 42 | 16 | | 43 | 8 | | 44 | 14 | | 45 | 12 | | 46 | 8 | | 47 | 10 | | 48 | 8 | | 49 | 15 |
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| 49.80% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 7 | | diversityRatio | 0.3493975903614458 | | totalSentences | 83 | | uniqueOpeners | 29 | |
| 86.58% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 77 | | matches | | 0 | "Just trees and darkness and" | | 1 | "Then another, and another, until" |
| | ratio | 0.026 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 17 | | totalSentences | 77 | | matches | | 0 | "She'd been here before, of" | | 1 | "She forced herself to keep" | | 2 | "she whispered, though the words" | | 3 | "They didn't walk with such" | | 4 | "Her phone's flashlight carved a" | | 5 | "She waited, counting her heartbeats." | | 6 | "Her light jerked upward, catching" | | 7 | "She pressed forward, abandoning caution" | | 8 | "They always appeared when she" | | 9 | "She recognized this wrongness." | | 10 | "She spun, catching a glimpse" | | 11 | "She pressed on across the" | | 12 | "It faced away from her," | | 13 | "Her foot caught on something" | | 14 | "She looked down to find" | | 15 | "She closed her eyes, gripping" | | 16 | "They had to be." |
| | ratio | 0.221 | |
| 31.43% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 66 | | totalSentences | 77 | | matches | | 0 | "The ancient oaks of Richmond" | | 1 | "Aurora pulled her jacket tighter" | | 2 | "The Heartstone pendant lay heavy" | | 3 | "She'd been here before, of" | | 4 | "The Fae Grove existed somewhere" | | 5 | "The standing stones that marked" | | 6 | "A twig snapped behind her." | | 7 | "Aurora froze, listening." | | 8 | "The sound came again, deliberate" | | 9 | "She forced herself to keep" | | 10 | "The pendant grew warmer." | | 11 | "she whispered, though the words" | | 12 | "Richmond Park had plenty of" | | 13 | "They didn't walk with such" | | 14 | "The darkness pressed closer as" | | 15 | "Her phone's flashlight carved a" | | 16 | "The familiar path looked wrong" | | 17 | "The footsteps stopped." | | 18 | "Aurora turned slowly, sweeping her" | | 19 | "She waited, counting her heartbeats." |
| | ratio | 0.857 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 77 | | matches | (empty) | | ratio | 0 | |
| 74.83% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 42 | | technicalSentenceCount | 4 | | matches | | 0 | "The sound came again, a groan of wood under weight, as if something large had settled onto the limb." | | 1 | "The voices overlapped, some speaking in English, others in languages she didn't recognize, all of them wrong in a way that made her teeth ache." | | 2 | "It faced away from her, perfectly still, dressed in clothes that might have been modern or might have been centuries old." | | 3 | "A wallet had fallen open, revealing a driver's license that gleamed in her phone light." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 2 | | uselessAdditionCount | 1 | | matches | | 0 | "she whispered, though the words felt hollow" |
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| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 1 | | fancyCount | 1 | | fancyTags | | 0 | "she whispered (whisper)" |
| | dialogueSentences | 2 | | tagDensity | 0.5 | | leniency | 1 | | rawRatio | 1 | | effectiveRatio | 1 | |