| 40.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 8 | | adverbTagCount | 2 | | adverbTags | | 0 | "Eva leaned back [back]" | | 1 | "Eva said softly [softly]" |
| | dialogueSentences | 25 | | tagDensity | 0.32 | | leniency | 0.64 | | rawRatio | 0.25 | | effectiveRatio | 0.16 | |
| 57.48% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 588 | | totalAiIsmAdverbs | 5 | | found | | | highlights | | 0 | "slightly" | | 1 | "slowly" | | 2 | "lazily" | | 3 | "sharply" | | 4 | "softly" |
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| 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) | |
| 31.97% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 588 | | totalAiIsms | 8 | | found | | | highlights | | 0 | "weight" | | 1 | "chaotic" | | 2 | "flickered" | | 3 | "silence" | | 4 | "flicked" | | 5 | "jaw clenched" | | 6 | "stomach" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "jaw/fists clenched" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 44 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 44 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 61 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 28 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 582 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 9 | | unquotedAttributions | 0 | | matches | (empty) | |
| 12.87% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 28 | | wordCount | 474 | | uniqueNames | 5 | | maxNameDensity | 2.74 | | worstName | "Eva" | | maxWindowNameDensity | 4.5 | | worstWindowName | "Eva" | | discoveredNames | | Eva | 13 | | Carter | 1 | | Lucien | 1 | | Aurora | 12 | | Ptolemy | 1 |
| | persons | | 0 | "Eva" | | 1 | "Carter" | | 2 | "Lucien" | | 3 | "Aurora" | | 4 | "Ptolemy" |
| | places | (empty) | | globalScore | 0.129 | | windowScore | 0.167 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 31 | | 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 | 582 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 61 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 29 | | mean | 20.07 | | std | 20.51 | | cv | 1.022 | | sampleLengths | | 0 | 68 | | 1 | 72 | | 2 | 67 | | 3 | 6 | | 4 | 64 | | 5 | 18 | | 6 | 6 | | 7 | 15 | | 8 | 12 | | 9 | 8 | | 10 | 17 | | 11 | 12 | | 12 | 6 | | 13 | 4 | | 14 | 10 | | 15 | 9 | | 16 | 6 | | 17 | 6 | | 18 | 37 | | 19 | 17 | | 20 | 25 | | 21 | 31 | | 22 | 11 | | 23 | 8 | | 24 | 10 | | 25 | 5 | | 26 | 13 | | 27 | 12 | | 28 | 7 |
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| 97.29% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 44 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 88 | | matches | (empty) | |
| 2.34% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 3 | | semicolonCount | 0 | | flaggedSentences | 3 | | totalSentences | 61 | | ratio | 0.049 | | matches | | 0 | "The air smelled of damp wool and something faintly metallic—old coffee, maybe, or the faintest trace of the demon’s perfume she’d caught on Lucien’s suit jacket earlier." | | 1 | "The flat was always like this—chaotic, alive with the hum of forgotten ideas and the quiet, stubborn energy of someone who refused to let things die." | | 2 | "The fridge hummed, its contents untouched—milk, a half-eaten sandwich, a bottle of water that had been there since last week." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 480 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 19 | | adverbRatio | 0.03958333333333333 | | lyAdverbCount | 7 | | lyAdverbRatio | 0.014583333333333334 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 61 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 61 | | mean | 9.54 | | std | 6.87 | | cv | 0.72 | | sampleLengths | | 0 | 22 | | 1 | 19 | | 2 | 27 | | 3 | 7 | | 4 | 26 | | 5 | 17 | | 6 | 22 | | 7 | 24 | | 8 | 23 | | 9 | 20 | | 10 | 6 | | 11 | 2 | | 12 | 22 | | 13 | 12 | | 14 | 17 | | 15 | 11 | | 16 | 18 | | 17 | 4 | | 18 | 2 | | 19 | 8 | | 20 | 7 | | 21 | 7 | | 22 | 5 | | 23 | 8 | | 24 | 4 | | 25 | 13 | | 26 | 10 | | 27 | 2 | | 28 | 3 | | 29 | 3 | | 30 | 4 | | 31 | 10 | | 32 | 6 | | 33 | 3 | | 34 | 3 | | 35 | 3 | | 36 | 4 | | 37 | 2 | | 38 | 11 | | 39 | 15 | | 40 | 11 | | 41 | 12 | | 42 | 5 | | 43 | 3 | | 44 | 14 | | 45 | 8 | | 46 | 9 | | 47 | 16 | | 48 | 6 | | 49 | 7 |
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| 43.44% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 4 | | diversityRatio | 0.29508196721311475 | | totalSentences | 61 | | uniqueOpeners | 18 | |
| 79.37% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 42 | | matches | | 0 | "Instead, she reached into her" |
| | ratio | 0.024 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 7 | | totalSentences | 42 | | matches | | 0 | "She didn’t look back at" | | 1 | "She moved toward the kitchen," | | 2 | "She turned slowly, her fingers" | | 3 | "She poured herself a cup," | | 4 | "she said, voice rough" | | 5 | "She handed it to Aurora" | | 6 | "It was a map, crudely" |
| | ratio | 0.167 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 41 | | totalSentences | 42 | | matches | | 0 | "The front door of Eva’s" | | 1 | "Aurora Carter stepped inside, her" | | 2 | "The air smelled of damp" | | 3 | "She didn’t look back at" | | 4 | "The flat was always like" | | 5 | "The walls were lined with" | | 6 | "A single lamp flickered, casting" | | 7 | "Aurora kicked off her shoes" | | 8 | "She moved toward the kitchen," | | 9 | "The fridge hummed, its contents" | | 10 | "Eva said without turning" | | 11 | "The voice was low, rough," | | 12 | "She turned slowly, her fingers" | | 13 | "Eva sat at the table," | | 14 | "The cat, Ptolemy, watched her" | | 15 | "Aurora said, voice steady despite" | | 16 | "Eva didn’t look away." | | 17 | "Aurora exhaled sharply, her breath" | | 18 | "Eva leaned back, the chair" | | 19 | "A beat of silence." |
| | ratio | 0.976 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 42 | | matches | (empty) | | ratio | 0 | |
| 67.67% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 19 | | technicalSentenceCount | 2 | | matches | | 0 | "The flat was always like this—chaotic, alive with the hum of forgotten ideas and the quiet, stubborn energy of someone who refused to let things die." | | 1 | "The fridge hummed, its contents untouched—milk, a half-eaten sandwich, a bottle of water that had been there since last week." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 8 | | uselessAdditionCount | 4 | | matches | | 0 | "Aurora said, voice steady despite the way her chest tightened" | | 1 | "Eva leaned back, the chair creaking" | | 2 | "Eva said, voice quieter now, almost sad" | | 3 | "she said, voice rough" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 7 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 25 | | tagDensity | 0.28 | | leniency | 0.56 | | rawRatio | 0 | | effectiveRatio | 0 | |