| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 9 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 13 | | tagDensity | 0.692 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 94.93% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 986 | | totalAiIsmAdverbs | 1 | | 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) | |
| 49.29% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 986 | | totalAiIsms | 10 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | word | "down her spine" | | count | 1 |
| | 5 | | | 6 | | | 7 | |
| | highlights | | 0 | "pulsed" | | 1 | "charged" | | 2 | "echo" | | 3 | "long shadow" | | 4 | "down her spine" | | 5 | "shimmered" | | 6 | "pulse" | | 7 | "warmth" |
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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 | 103 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 2 | | narrationSentences | 103 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 106 | | 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 | 2 | | markdownWords | 13 | | totalWords | 986 | | ratio | 0.013 | | matches | | 0 | "Richmond grove. Midnight. Come alone." | | 1 | "Never turn. Never eat. Never give your name." |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 4 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 18 | | wordCount | 949 | | uniqueNames | 7 | | maxNameDensity | 0.63 | | worstName | "Eva" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Eva" | | discoveredNames | | Heartstone | 4 | | Laila | 1 | | Eva | 6 | | Aurora | 4 | | Silas | 1 | | Pleading | 1 | | London | 1 |
| | persons | | 0 | "Heartstone" | | 1 | "Laila" | | 2 | "Eva" | | 3 | "Aurora" | | 4 | "Silas" |
| | places | | | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 70 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 98.58% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 1.014 | | wordCount | 986 | | matches | | 0 | "not like wood, but like intestines" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 106 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 28 | | mean | 35.21 | | std | 25.12 | | cv | 0.713 | | sampleLengths | | 0 | 66 | | 1 | 41 | | 2 | 52 | | 3 | 41 | | 4 | 52 | | 5 | 59 | | 6 | 57 | | 7 | 17 | | 8 | 36 | | 9 | 4 | | 10 | 63 | | 11 | 54 | | 12 | 32 | | 13 | 11 | | 14 | 102 | | 15 | 5 | | 16 | 38 | | 17 | 52 | | 18 | 9 | | 19 | 11 | | 20 | 59 | | 21 | 9 | | 22 | 7 | | 23 | 61 | | 24 | 23 | | 25 | 14 | | 26 | 8 | | 27 | 3 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 103 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 158 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 1 | | flaggedSentences | 1 | | totalSentences | 106 | | ratio | 0.009 | | matches | | 0 | "Her palm found the Heartstone pendant under her shirt; it pulsed against her ribs, warm as a living heartbeat." |
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| 98.27% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 953 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 40 | | adverbRatio | 0.04197271773347324 | | lyAdverbCount | 6 | | lyAdverbRatio | 0.0062959076600209865 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 106 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 106 | | mean | 9.3 | | std | 6.44 | | cv | 0.692 | | sampleLengths | | 0 | 9 | | 1 | 17 | | 2 | 6 | | 3 | 4 | | 4 | 19 | | 5 | 11 | | 6 | 6 | | 7 | 2 | | 8 | 1 | | 9 | 25 | | 10 | 7 | | 11 | 20 | | 12 | 16 | | 13 | 16 | | 14 | 9 | | 15 | 10 | | 16 | 6 | | 17 | 7 | | 18 | 9 | | 19 | 6 | | 20 | 16 | | 21 | 7 | | 22 | 9 | | 23 | 3 | | 24 | 11 | | 25 | 8 | | 26 | 3 | | 27 | 17 | | 28 | 4 | | 29 | 14 | | 30 | 13 | | 31 | 8 | | 32 | 19 | | 33 | 2 | | 34 | 5 | | 35 | 23 | | 36 | 5 | | 37 | 8 | | 38 | 4 | | 39 | 5 | | 40 | 5 | | 41 | 13 | | 42 | 13 | | 43 | 4 | | 44 | 15 | | 45 | 14 | | 46 | 9 | | 47 | 25 | | 48 | 3 | | 49 | 17 |
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| 61.01% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 12 | | diversityRatio | 0.4339622641509434 | | totalSentences | 106 | | uniqueOpeners | 46 | |
| 73.26% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 91 | | matches | | 0 | "Only the flowers answered, rotating" | | 1 | "Then the child-voice, playful:" |
| | ratio | 0.022 | |
| 96.92% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 28 | | totalSentences | 91 | | matches | | 0 | "She forced herself to keep" | | 1 | "Her palm found the Heartstone" | | 2 | "She clicked the dead torch" | | 3 | "Her voice came out thinner" | | 4 | "She stepped deeper into the" | | 5 | "They should have been closed" | | 6 | "They should have bowed when" | | 7 | "They did not." | | 8 | "It moved against the breeze," | | 9 | "Its inner glow waxed bright," | | 10 | "Her fingers tightened around the" | | 11 | "She stepped back and crushed" | | 12 | "She refused to look at" | | 13 | "She aimed her voice at" | | 14 | "She took another step forward." | | 15 | "Her eyes were glass." | | 16 | "Her mouth moved, but the" | | 17 | "Her knees turned loose, but" | | 18 | "She remembered the old stories" | | 19 | "She saw the oak roots" |
| | ratio | 0.308 | |
| 31.43% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 78 | | totalSentences | 91 | | matches | | 0 | "The torch died three steps" | | 1 | "Aurora shook it once, twice," | | 2 | "She forced herself to keep" | | 3 | "Her palm found the Heartstone" | | 4 | "That was the only reason" | | 5 | "Eva’s message had sent her" | | 6 | "The grove did not care" | | 7 | "The air tasted wrong, pollen-sweet" | | 8 | "She clicked the dead torch" | | 9 | "Her voice came out thinner" | | 10 | "The name folded into the" | | 11 | "That was the first wrong" | | 12 | "A shout in a wood" | | 13 | "Here it vanished like a" | | 14 | "She stepped deeper into the" | | 15 | "Wildflowers brushed her ankles, white" | | 16 | "They should have been closed" | | 17 | "They should have bowed when" | | 18 | "They did not." | | 19 | "Each bloom turned toward her" |
| | ratio | 0.857 | |
| 54.95% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 91 | | matches | | 0 | "Now the oaks rose around" |
| | ratio | 0.011 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 37 | | technicalSentenceCount | 2 | | matches | | 0 | "Shapes shimmered at the edge of her vision, figures that vanished the moment she turned her eyes." | | 1 | "The ground under her boots softened, then shifted, as if something beneath the soil was breathing." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 9 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 6 | | fancyCount | 3 | | fancyTags | | 0 | "Eva whispered (whisper)" | | 1 | "Eva’s voice whispered (whisper)" | | 2 | "the voice repeated (repeat)" |
| | dialogueSentences | 13 | | tagDensity | 0.462 | | leniency | 0.923 | | rawRatio | 0.5 | | effectiveRatio | 0.462 | |