| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 13 | | adverbTagCount | 2 | | adverbTags | | 0 | "that faint French accent she’d always [always]" | | 1 | "She swallowed hard [hard]" |
| | dialogueSentences | 41 | | tagDensity | 0.317 | | leniency | 0.634 | | rawRatio | 0.154 | | effectiveRatio | 0.098 | |
| 84.83% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 989 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | 0 | "softly" | | 1 | "really" | | 2 | "slowly" |
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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) | |
| 34.28% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 989 | | totalAiIsms | 13 | | found | | | highlights | | 0 | "intensity" | | 1 | "stomach" | | 2 | "flicked" | | 3 | "flicker" | | 4 | "echoed" | | 5 | "warmth" | | 6 | "could feel" | | 7 | "silence" | | 8 | "traced" | | 9 | "weight" | | 10 | "unreadable" |
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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 | 1 | | narrationSentences | 55 | | matches | | |
| 90.91% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 2 | | narrationSentences | 55 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 82 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 24 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 980 | | ratio | 0 | | matches | (empty) | |
| 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 | 8 | | wordCount | 707 | | uniqueNames | 4 | | maxNameDensity | 0.42 | | worstName | "Eva" | | maxWindowNameDensity | 1 | | worstWindowName | "Lucien" | | discoveredNames | | Eva | 3 | | French | 1 | | Lucien | 2 | | Ptolemy | 2 |
| | persons | | 0 | "Eva" | | 1 | "Lucien" | | 2 | "Ptolemy" |
| | places | (empty) | | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 53 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 0.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 2 | | per1kWords | 2.041 | | wordCount | 980 | | matches | | 0 | "Not just for me, but for everyone" | | 1 | "neither time nor" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 82 | | matches | (empty) | |
| 96.26% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 34 | | mean | 28.82 | | std | 14.03 | | cv | 0.487 | | sampleLengths | | 0 | 81 | | 1 | 14 | | 2 | 53 | | 3 | 35 | | 4 | 20 | | 5 | 17 | | 6 | 14 | | 7 | 19 | | 8 | 45 | | 9 | 42 | | 10 | 27 | | 11 | 41 | | 12 | 31 | | 13 | 21 | | 14 | 36 | | 15 | 27 | | 16 | 31 | | 17 | 20 | | 18 | 17 | | 19 | 19 | | 20 | 33 | | 21 | 27 | | 22 | 36 | | 23 | 21 | | 24 | 27 | | 25 | 36 | | 26 | 27 | | 27 | 48 | | 28 | 28 | | 29 | 23 | | 30 | 12 | | 31 | 28 | | 32 | 4 | | 33 | 20 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 55 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 120 | | matches | (empty) | |
| 3.48% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 6 | | semicolonCount | 0 | | flaggedSentences | 4 | | totalSentences | 82 | | ratio | 0.049 | | matches | | 0 | "His heterochromatic eyes—one amber, one black—locked onto hers with an intensity that made her stomach twist." | | 1 | "The scent of curry from downstairs mingled with the faint hint of Lucien’s cologne—something woody and expensive." | | 2 | "The memory of their last argument played in her mind—sharp words, accusations, the sting of betrayal." | | 3 | "His expression was unreadable, but there was something in his gaze—something raw and vulnerable—that made her chest tighten." |
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| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 716 | | adjectiveStacks | 1 | | stackExamples | | 0 | "small crescent-shaped scar" |
| | adverbCount | 26 | | adverbRatio | 0.036312849162011177 | | lyAdverbCount | 6 | | lyAdverbRatio | 0.008379888268156424 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 82 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 82 | | mean | 11.95 | | std | 5.22 | | cv | 0.437 | | sampleLengths | | 0 | 8 | | 1 | 12 | | 2 | 16 | | 3 | 19 | | 4 | 23 | | 5 | 3 | | 6 | 13 | | 7 | 1 | | 8 | 17 | | 9 | 20 | | 10 | 16 | | 11 | 13 | | 12 | 22 | | 13 | 14 | | 14 | 6 | | 15 | 9 | | 16 | 8 | | 17 | 10 | | 18 | 4 | | 19 | 12 | | 20 | 7 | | 21 | 13 | | 22 | 10 | | 23 | 22 | | 24 | 9 | | 25 | 17 | | 26 | 16 | | 27 | 11 | | 28 | 16 | | 29 | 17 | | 30 | 24 | | 31 | 10 | | 32 | 14 | | 33 | 7 | | 34 | 10 | | 35 | 11 | | 36 | 11 | | 37 | 20 | | 38 | 5 | | 39 | 19 | | 40 | 8 | | 41 | 21 | | 42 | 10 | | 43 | 15 | | 44 | 5 | | 45 | 13 | | 46 | 4 | | 47 | 7 | | 48 | 12 | | 49 | 19 |
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| 76.02% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 1 | | diversityRatio | 0.4634146341463415 | | totalSentences | 82 | | uniqueOpeners | 38 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 55 | | matches | | 0 | "Too late for a delivery," | | 1 | "Then he reached out, his" | | 2 | "Instead, he stepped closer, his" |
| | ratio | 0.055 | |
| 0.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 36 | | totalSentences | 55 | | matches | | 0 | "She set the bag on" | | 1 | "Her breath hitched." | | 2 | "She unlocked the three deadbolts" | | 3 | "His voice was smooth, low," | | 4 | "He stood in the hallway," | | 5 | "His heterochromatic eyes—one amber, one" | | 6 | "She crossed her arms, leaning" | | 7 | "Her tone was sharper than" | | 8 | "His gaze flicked over her" | | 9 | "She shrugged, feigning nonchalance" | | 10 | "His lips thinned, a flicker" | | 11 | "She pushed off the doorframe," | | 12 | "He followed her inside, closing" | | 13 | "He stepped closer, his cane" | | 14 | "She turned her back to" | | 15 | "His voice was closer now," | | 16 | "She could feel the heat" | | 17 | "She spun around, the takeaway" | | 18 | "His gaze darkened, and for" | | 19 | "She glanced down at the" |
| | ratio | 0.655 | |
| 14.55% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 49 | | totalSentences | 55 | | matches | | 0 | "The knock at the door" | | 1 | "Rory froze mid-step, takeaway bag" | | 2 | "She set the bag on" | | 3 | "Her breath hitched." | | 4 | "She unlocked the three deadbolts" | | 5 | "His voice was smooth, low," | | 6 | "He stood in the hallway," | | 7 | "His heterochromatic eyes—one amber, one" | | 8 | "She crossed her arms, leaning" | | 9 | "Her tone was sharper than" | | 10 | "His gaze flicked over her" | | 11 | "She shrugged, feigning nonchalance" | | 12 | "His lips thinned, a flicker" | | 13 | "She pushed off the doorframe," | | 14 | "He followed her inside, closing" | | 15 | "The click of the latch" | | 16 | "Ptolemy, Eva’s tabby cat, darted" | | 17 | "Rory leaned against the kitchen" | | 18 | "The scent of curry from" | | 19 | "He stepped closer, his cane" |
| | ratio | 0.891 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 55 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 32 | | technicalSentenceCount | 1 | | matches | | 0 | "His heterochromatic eyes—one amber, one black—locked onto hers with an intensity that made her stomach twist." |
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| 86.54% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 13 | | uselessAdditionCount | 1 | | matches | | 0 | "He stepped, his cane tapping softly against the floor" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |