| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 21 | | adverbTagCount | 1 | | adverbTags | | 0 | "they wrapped around [around]" |
| | dialogueSentences | 57 | | tagDensity | 0.368 | | leniency | 0.737 | | rawRatio | 0.048 | | effectiveRatio | 0.035 | |
| 95.48% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1107 | | totalAiIsmAdverbs | 1 | | found | | | highlights | | |
| 100.00% | AI-ism character names | Target: 0 AI-default names (16 tracked, −20% each) | | codexExemptions | | | found | (empty) | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 95.48% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1107 | | totalAiIsms | 1 | | found | | | highlights | | |
| 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 | 57 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 57 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 94 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 44 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1107 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 18 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 16 | | wordCount | 647 | | uniqueNames | 6 | | maxNameDensity | 0.93 | | worstName | "Tommy" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Tommy" | | discoveredNames | | Tommy | 6 | | Reardon | 1 | | Cardiff | 2 | | Silas | 1 | | India | 1 | | Aurora | 5 |
| | persons | | 0 | "Tommy" | | 1 | "Reardon" | | 2 | "Silas" | | 3 | "Aurora" |
| | places | | | globalScore | 1 | | windowScore | 1 | |
| 11.11% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 36 | | glossingSentenceCount | 2 | | matches | | 0 | "quite joy" | | 1 | "looked like a man reading it off a card" |
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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 | 1107 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 94 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 58 | | mean | 19.09 | | std | 16.53 | | cv | 0.866 | | sampleLengths | | 0 | 12 | | 1 | 66 | | 2 | 25 | | 3 | 1 | | 4 | 23 | | 5 | 4 | | 6 | 3 | | 7 | 44 | | 8 | 20 | | 9 | 7 | | 10 | 13 | | 11 | 6 | | 12 | 16 | | 13 | 15 | | 14 | 5 | | 15 | 38 | | 16 | 40 | | 17 | 12 | | 18 | 17 | | 19 | 3 | | 20 | 6 | | 21 | 46 | | 22 | 6 | | 23 | 6 | | 24 | 48 | | 25 | 5 | | 26 | 14 | | 27 | 4 | | 28 | 15 | | 29 | 6 | | 30 | 44 | | 31 | 6 | | 32 | 42 | | 33 | 6 | | 34 | 8 | | 35 | 20 | | 36 | 10 | | 37 | 41 | | 38 | 4 | | 39 | 15 | | 40 | 32 | | 41 | 35 | | 42 | 23 | | 43 | 4 | | 44 | 51 | | 45 | 23 | | 46 | 27 | | 47 | 2 | | 48 | 4 | | 49 | 61 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 57 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 121 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 1 | | flaggedSentences | 1 | | totalSentences | 94 | | ratio | 0.011 | | matches | | 0 | "The argument by the window reached its peak and collapsed; the couple left, the door banging behind them, and the bar fell into the particular hush of a place that has heard too many confessions to flinch at one more." |
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| 97.68% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 422 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 18 | | adverbRatio | 0.04265402843601896 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.011848341232227487 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 94 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 94 | | mean | 11.78 | | std | 9.2 | | cv | 0.781 | | sampleLengths | | 0 | 12 | | 1 | 36 | | 2 | 30 | | 3 | 5 | | 4 | 20 | | 5 | 1 | | 6 | 3 | | 7 | 20 | | 8 | 4 | | 9 | 3 | | 10 | 2 | | 11 | 19 | | 12 | 7 | | 13 | 16 | | 14 | 9 | | 15 | 11 | | 16 | 7 | | 17 | 11 | | 18 | 2 | | 19 | 6 | | 20 | 2 | | 21 | 14 | | 22 | 15 | | 23 | 5 | | 24 | 22 | | 25 | 16 | | 26 | 16 | | 27 | 24 | | 28 | 12 | | 29 | 8 | | 30 | 9 | | 31 | 3 | | 32 | 6 | | 33 | 11 | | 34 | 15 | | 35 | 20 | | 36 | 6 | | 37 | 6 | | 38 | 17 | | 39 | 31 | | 40 | 5 | | 41 | 4 | | 42 | 10 | | 43 | 4 | | 44 | 5 | | 45 | 10 | | 46 | 6 | | 47 | 5 | | 48 | 17 | | 49 | 22 |
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| 86.52% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 2 | | diversityRatio | 0.5319148936170213 | | totalSentences | 94 | | uniqueOpeners | 50 | |
| 69.44% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 48 | | matches | | 0 | "Somewhere in the back a" |
| | ratio | 0.021 | |
| 3.33% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 26 | | totalSentences | 48 | | matches | | 0 | "She nearly didn't say anything." | | 1 | "His head turned." | | 2 | "He smelled of cedar and" | | 3 | "He gestured at the stool" | | 4 | "He said it like a" | | 5 | "She watched him decide not" | | 6 | "He laughed, and even the" | | 7 | "she said, and meant the" | | 8 | "He studied her" | | 9 | "He raised his glass an" | | 10 | "He grinned, and for half" | | 11 | "He turned the tumbler a" | | 12 | "She let the quiet sit." | | 13 | "He said it flatly, the" | | 14 | "He nodded at the bottles" | | 15 | "He looked like a man" | | 16 | "It wasn't a question." | | 17 | "He shrugged, and the suit" | | 18 | "He laughed again, but it" | | 19 | "She tasted the word" |
| | ratio | 0.542 | |
| 32.92% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 41 | | totalSentences | 48 | | matches | | 0 | "The man at the end" | | 1 | "Aurora knew because she'd watched" | | 2 | "She nearly didn't say anything." | | 3 | "His head turned." | | 4 | "The face took a second" | | 5 | "The hug was the kind" | | 6 | "He smelled of cedar and" | | 7 | "The Tommy she'd known smelled" | | 8 | "He gestured at the stool" | | 9 | "He said it like a" | | 10 | "She watched him decide not" | | 11 | "He laughed, and even the" | | 12 | "The suit was charcoal and" | | 13 | "Tommy had once owned a" | | 14 | "she said, and meant the" | | 15 | "He studied her" | | 16 | "He raised his glass an" | | 17 | "Aurora signalled to the barman," | | 18 | "He grinned, and for half" | | 19 | "The grin folded itself away." |
| | ratio | 0.854 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 48 | | matches | | 0 | "Now they wrapped around a" |
| | ratio | 0.021 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 24 | | technicalSentenceCount | 1 | | matches | | 0 | "The argument by the window reached its peak and collapsed; the couple left, the door banging behind them, and the bar fell into the particular hush of a place t…" |
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| 77.38% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 21 | | uselessAdditionCount | 2 | | matches | | 0 | "He shrugged, and the suit shrugged with him, expensive fabric moving like water" | | 1 | "He looked, and the smoothness slipped, and underneath it she saw something raw and tired and twenty-three years old still" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 10 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 57 | | tagDensity | 0.175 | | leniency | 0.351 | | rawRatio | 0.1 | | effectiveRatio | 0.035 | |