| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 10 | | adverbTagCount | 1 | | adverbTags | | 0 | "He turned fully [fully]" |
| | dialogueSentences | 45 | | tagDensity | 0.222 | | leniency | 0.444 | | rawRatio | 0.1 | | effectiveRatio | 0.044 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 867 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 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) | |
| 76.93% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 867 | | totalAiIsms | 4 | | found | | | highlights | | 0 | "flicked" | | 1 | "eyebrow" | | 2 | "pulse" | | 3 | "tracing" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 0 | | maxInWindow | 0 | | found | (empty) | | highlights | (empty) | |
| 97.22% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 2 | | narrationSentences | 60 | | matches | | 0 | "was afraid" | | 1 | "was desperate" |
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| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 60 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 95 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 30 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 866 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 11 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 11 | | wordCount | 617 | | uniqueNames | 5 | | maxNameDensity | 0.65 | | worstName | "Rory" | | maxWindowNameDensity | 2 | | worstWindowName | "Rory" | | discoveredNames | | Eva | 1 | | Rory | 4 | | London | 1 | | Marseille | 1 | | Lucien | 4 |
| | persons | | | places | | | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 42 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 84.53% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 1.155 | | wordCount | 866 | | matches | | 0 | "not to push him away, but to hold him there" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 95 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 49 | | mean | 17.67 | | std | 16.07 | | cv | 0.909 | | sampleLengths | | 0 | 63 | | 1 | 4 | | 2 | 67 | | 3 | 6 | | 4 | 5 | | 5 | 6 | | 6 | 5 | | 7 | 23 | | 8 | 23 | | 9 | 23 | | 10 | 26 | | 11 | 4 | | 12 | 22 | | 13 | 2 | | 14 | 6 | | 15 | 30 | | 16 | 19 | | 17 | 23 | | 18 | 1 | | 19 | 2 | | 20 | 8 | | 21 | 12 | | 22 | 44 | | 23 | 26 | | 24 | 2 | | 25 | 57 | | 26 | 16 | | 27 | 4 | | 28 | 3 | | 29 | 1 | | 30 | 12 | | 31 | 5 | | 32 | 29 | | 33 | 8 | | 34 | 7 | | 35 | 12 | | 36 | 34 | | 37 | 7 | | 38 | 29 | | 39 | 21 | | 40 | 3 | | 41 | 25 | | 42 | 15 | | 43 | 49 | | 44 | 5 | | 45 | 17 | | 46 | 25 | | 47 | 17 | | 48 | 13 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 60 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 110 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 1 | | semicolonCount | 0 | | flaggedSentences | 1 | | totalSentences | 95 | | ratio | 0.011 | | matches | | 0 | "His suit was immaculate, as always—charcoal wool, tailored to perfection, the faintest sheen of rain still clinging to the shoulders." |
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| 95.36% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 618 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 28 | | adverbRatio | 0.045307443365695796 | | lyAdverbCount | 1 | | lyAdverbRatio | 0.0016181229773462784 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 95 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 95 | | mean | 9.12 | | std | 6.36 | | cv | 0.698 | | sampleLengths | | 0 | 10 | | 1 | 15 | | 2 | 24 | | 3 | 14 | | 4 | 4 | | 5 | 19 | | 6 | 28 | | 7 | 20 | | 8 | 6 | | 9 | 5 | | 10 | 3 | | 11 | 3 | | 12 | 5 | | 13 | 14 | | 14 | 9 | | 15 | 11 | | 16 | 8 | | 17 | 4 | | 18 | 18 | | 19 | 5 | | 20 | 9 | | 21 | 14 | | 22 | 3 | | 23 | 4 | | 24 | 7 | | 25 | 12 | | 26 | 3 | | 27 | 2 | | 28 | 6 | | 29 | 16 | | 30 | 8 | | 31 | 3 | | 32 | 3 | | 33 | 14 | | 34 | 5 | | 35 | 12 | | 36 | 11 | | 37 | 1 | | 38 | 2 | | 39 | 8 | | 40 | 6 | | 41 | 6 | | 42 | 10 | | 43 | 25 | | 44 | 9 | | 45 | 10 | | 46 | 16 | | 47 | 2 | | 48 | 13 | | 49 | 2 |
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| 58.60% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 6 | | diversityRatio | 0.3894736842105263 | | totalSentences | 95 | | uniqueOpeners | 37 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 54 | | matches | | 0 | "Then she saw him." | | 1 | "Then the way he’d walked" | | 2 | "Then his mouth was on" |
| | ratio | 0.056 | |
| 0.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 31 | | totalSentences | 54 | | matches | | 0 | "His suit was immaculate, as" | | 1 | "His mouth quirked." | | 2 | "He turned fully toward her," | | 3 | "They skidded across a stack" | | 4 | "She pulled her phone from" | | 5 | "She tugged it down, but" | | 6 | "His jaw tightened." | | 7 | "She crossed her arms" | | 8 | "He exhaled through his nose," | | 9 | "His fingers tightened around the" | | 10 | "She could still feel the" | | 11 | "She turned toward the kitchenette," | | 12 | "She pulled a bottle from" | | 13 | "She poured, the liquid catching" | | 14 | "He took the glass." | | 15 | "Their fingers didn’t touch, but" | | 16 | "His mouth twisted." | | 17 | "He set the glass down" | | 18 | "She didn’t answer." | | 19 | "She didn’t have to." |
| | ratio | 0.574 | |
| 24.81% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 47 | | totalSentences | 54 | | matches | | 0 | "The key turned in the" | | 1 | "Rory hesitated, her fingers still" | | 2 | "The scent of cardamom and" | | 3 | "Ptolemy uncurled from the armchair," | | 4 | "Lucien stood by the window," | | 5 | "The late afternoon light caught" | | 6 | "His suit was immaculate, as" | | 7 | "Rory’s breath stuck in her" | | 8 | "His mouth quirked." | | 9 | "He turned fully toward her," | | 10 | "Rory stepped inside, shutting the" | | 11 | "The locks slid home with" | | 12 | "Rory tossed her keys onto" | | 13 | "They skidded across a stack" | | 14 | "She pulled her phone from" | | 15 | "Lucien’s gaze flicked to her" | | 16 | "She tugged it down, but" | | 17 | "His jaw tightened." | | 18 | "She crossed her arms" | | 19 | "He exhaled through his nose," |
| | ratio | 0.87 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 54 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 28 | | technicalSentenceCount | 1 | | matches | | 0 | "She kissed him back just as hard, her fingers tangling in his hair, pulling him closer." |
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| 75.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 10 | | uselessAdditionCount | 1 | | matches | | 0 | "He turned fully, the black eye swallowing the light" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 4 | | fancyCount | 2 | | fancyTags | | 0 | "he murmured (murmur)" | | 1 | "She pressed (press)" |
| | dialogueSentences | 45 | | tagDensity | 0.089 | | leniency | 0.178 | | rawRatio | 0.5 | | effectiveRatio | 0.089 | |