| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 22 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 47 | | tagDensity | 0.468 | | leniency | 0.936 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 88.65% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1322 | | totalAiIsmAdverbs | 3 | | 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) | |
| 69.74% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1322 | | totalAiIsms | 8 | | found | | | highlights | | 0 | "pulse" | | 1 | "whisper" | | 2 | "throb" | | 3 | "stomach" | | 4 | "pulsed" | | 5 | "silk" |
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| 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 | 108 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 108 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 132 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 37 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1322 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 11 | | unquotedAttributions | 0 | | matches | (empty) | |
| 94.03% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 28 | | wordCount | 1072 | | uniqueNames | 8 | | maxNameDensity | 1.12 | | worstName | "Nyx" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Aurora" | | discoveredNames | | Richmond | 1 | | Park | 1 | | Aurora | 10 | | Sawyer | 1 | | Hill | 1 | | Road | 1 | | Nyx | 12 | | Shade | 1 |
| | persons | | 0 | "Aurora" | | 1 | "Sawyer" | | 2 | "Nyx" | | 3 | "Shade" |
| | places | | 0 | "Richmond" | | 1 | "Park" | | 2 | "Hill" | | 3 | "Road" |
| | globalScore | 0.94 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 70 | | glossingSentenceCount | 1 | | matches | | 0 | "felt like touching a sleeping animal" |
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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 | 1322 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 132 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 52 | | mean | 25.42 | | std | 22.23 | | cv | 0.874 | | sampleLengths | | 0 | 48 | | 1 | 28 | | 2 | 24 | | 3 | 22 | | 4 | 51 | | 5 | 8 | | 6 | 52 | | 7 | 2 | | 8 | 12 | | 9 | 35 | | 10 | 4 | | 11 | 73 | | 12 | 9 | | 13 | 25 | | 14 | 51 | | 15 | 14 | | 16 | 9 | | 17 | 2 | | 18 | 2 | | 19 | 10 | | 20 | 57 | | 21 | 5 | | 22 | 39 | | 23 | 3 | | 24 | 41 | | 25 | 1 | | 26 | 10 | | 27 | 85 | | 28 | 10 | | 29 | 21 | | 30 | 22 | | 31 | 22 | | 32 | 25 | | 33 | 88 | | 34 | 5 | | 35 | 49 | | 36 | 8 | | 37 | 22 | | 38 | 61 | | 39 | 8 | | 40 | 7 | | 41 | 24 | | 42 | 9 | | 43 | 68 | | 44 | 20 | | 45 | 6 | | 46 | 25 | | 47 | 32 | | 48 | 30 | | 49 | 5 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 108 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 184 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 132 | | ratio | 0 | | matches | (empty) | |
| 99.19% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1075 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 44 | | adverbRatio | 0.04093023255813953 | | lyAdverbCount | 6 | | lyAdverbRatio | 0.005581395348837209 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 132 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 132 | | mean | 10.02 | | std | 7.56 | | cv | 0.755 | | sampleLengths | | 0 | 20 | | 1 | 4 | | 2 | 8 | | 3 | 16 | | 4 | 13 | | 5 | 15 | | 6 | 16 | | 7 | 8 | | 8 | 13 | | 9 | 9 | | 10 | 3 | | 11 | 6 | | 12 | 30 | | 13 | 12 | | 14 | 5 | | 15 | 3 | | 16 | 25 | | 17 | 10 | | 18 | 17 | | 19 | 2 | | 20 | 3 | | 21 | 9 | | 22 | 2 | | 23 | 19 | | 24 | 3 | | 25 | 11 | | 26 | 4 | | 27 | 5 | | 28 | 6 | | 29 | 32 | | 30 | 14 | | 31 | 16 | | 32 | 4 | | 33 | 5 | | 34 | 22 | | 35 | 3 | | 36 | 3 | | 37 | 23 | | 38 | 13 | | 39 | 6 | | 40 | 6 | | 41 | 6 | | 42 | 1 | | 43 | 7 | | 44 | 9 | | 45 | 2 | | 46 | 2 | | 47 | 7 | | 48 | 3 | | 49 | 2 |
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| 69.70% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 8 | | diversityRatio | 0.45454545454545453 | | totalSentences | 132 | | uniqueOpeners | 60 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 97 | | matches | | 0 | "Somewhere behind them, the last" | | 1 | "Then she let her focus" | | 2 | "Slowly, patiently, a pale green" |
| | ratio | 0.031 | |
| 96.29% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 30 | | totalSentences | 97 | | matches | | 0 | "She looked left." | | 1 | "It rippled like heat over" | | 2 | "Her pulse ticked up" | | 3 | "They stepped through and the" | | 4 | "Her ears popped." | | 5 | "She opened her eyes." | | 6 | "They stood in a ring," | | 7 | "She looked down." | | 8 | "She crouched and touched a" | | 9 | "It felt like touching a" | | 10 | "She jerked her hand back" | | 11 | "Her phone hummed in her" | | 12 | "She fished it out." | | 13 | "She thumbed the side button." | | 14 | "It was too even for" | | 15 | "It had a pulse, a" | | 16 | "She pulled the silver chain" | | 17 | "She turned it over in" | | 18 | "It kept pulsing against her" | | 19 | "Its wings were made of" |
| | ratio | 0.309 | |
| 16.70% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 86 | | totalSentences | 97 | | matches | | 0 | "Frost furred the bracken in" | | 1 | "The deer had gone quiet" | | 2 | "Aurora shoved her hands deeper" | | 3 | "The crescent scar on her" | | 4 | "Nyx drifted a pace ahead," | | 5 | "The violet of their eyes" | | 6 | "The voice slid across her" | | 7 | "She looked left." | | 8 | "Nothing but a stand of" | | 9 | "It rippled like heat over" | | 10 | "Her pulse ticked up" | | 11 | "Nyx raised one hand" | | 12 | "The fingers thinned to smoke" | | 13 | "Nyx didn't answer." | | 14 | "They stepped through and the" | | 15 | "The pressure hit first, a" | | 16 | "Her ears popped." | | 17 | "The frost bit at her" | | 18 | "She opened her eyes." | | 19 | "The oaks were not trees." |
| | ratio | 0.887 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 97 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 40 | | technicalSentenceCount | 1 | | matches | | 0 | "A blue-white one shed a thread of light that lengthened, snapped, and drifted down to become a moth." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 22 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 64.89% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 6 | | fancyCount | 4 | | fancyTags | | 0 | "she whispered (whisper)" | | 1 | "she muttered (mutter)" | | 2 | "Nyx murmured (murmur)" | | 3 | "Nyx breathed (breathe)" |
| | dialogueSentences | 47 | | tagDensity | 0.128 | | leniency | 0.255 | | rawRatio | 0.667 | | effectiveRatio | 0.17 | |