| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 10 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 24 | | tagDensity | 0.417 | | leniency | 0.833 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 92.90% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 704 | | 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) | |
| 71.59% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 704 | | totalAiIsms | 4 | | found | | | highlights | | 0 | "silence" | | 1 | "weight" | | 2 | "pulse" | | 3 | "flickered" |
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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 | 36 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 36 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 50 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 57 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 704 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 14 | | unquotedAttributions | 0 | | matches | (empty) | |
| 74.62% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 11 | | wordCount | 398 | | uniqueNames | 4 | | maxNameDensity | 1.51 | | worstName | "Rory" | | maxWindowNameDensity | 2 | | worstWindowName | "Rory" | | discoveredNames | | Rory | 6 | | Moreau | 1 | | London | 1 | | Lucien | 3 |
| | persons | | 0 | "Rory" | | 1 | "Moreau" | | 2 | "Lucien" |
| | places | | | globalScore | 0.746 | | windowScore | 1 | |
| 41.30% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 23 | | glossingSentenceCount | 1 | | matches | | 0 | "breath that seemed to cost him" |
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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 | 704 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 50 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 24 | | mean | 29.33 | | std | 21.34 | | cv | 0.728 | | sampleLengths | | 0 | 62 | | 1 | 19 | | 2 | 50 | | 3 | 14 | | 4 | 19 | | 5 | 70 | | 6 | 5 | | 7 | 42 | | 8 | 44 | | 9 | 3 | | 10 | 37 | | 11 | 5 | | 12 | 56 | | 13 | 4 | | 14 | 43 | | 15 | 14 | | 16 | 78 | | 17 | 16 | | 18 | 14 | | 19 | 31 | | 20 | 21 | | 21 | 23 | | 22 | 22 | | 23 | 12 |
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| 95.52% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 36 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 64 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 50 | | ratio | 0 | | matches | (empty) | |
| 97.72% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 399 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 17 | | adverbRatio | 0.042606516290726815 | | lyAdverbCount | 4 | | lyAdverbRatio | 0.010025062656641603 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 50 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 50 | | mean | 14.08 | | std | 11.64 | | cv | 0.827 | | sampleLengths | | 0 | 25 | | 1 | 24 | | 2 | 2 | | 3 | 2 | | 4 | 9 | | 5 | 6 | | 6 | 13 | | 7 | 14 | | 8 | 36 | | 9 | 10 | | 10 | 4 | | 11 | 11 | | 12 | 8 | | 13 | 12 | | 14 | 33 | | 15 | 8 | | 16 | 17 | | 17 | 5 | | 18 | 14 | | 19 | 28 | | 20 | 25 | | 21 | 19 | | 22 | 3 | | 23 | 12 | | 24 | 16 | | 25 | 9 | | 26 | 5 | | 27 | 17 | | 28 | 39 | | 29 | 3 | | 30 | 1 | | 31 | 5 | | 32 | 38 | | 33 | 14 | | 34 | 21 | | 35 | 57 | | 36 | 12 | | 37 | 4 | | 38 | 5 | | 39 | 3 | | 40 | 6 | | 41 | 5 | | 42 | 26 | | 43 | 5 | | 44 | 16 | | 45 | 5 | | 46 | 18 | | 47 | 22 | | 48 | 3 | | 49 | 9 |
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| 68.67% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 4 | | diversityRatio | 0.46 | | totalSentences | 50 | | uniqueOpeners | 23 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 30 | | matches | (empty) | | ratio | 0 | |
| 60.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 12 | | totalSentences | 30 | | matches | | 0 | "She had a mug of" | | 1 | "She didn't get up right" | | 2 | "She let the silence stretch" | | 3 | "She knew who it was" | | 4 | "She undid the first chain," | | 5 | "She left the third sliding" | | 6 | "He hadn't bothered with an" | | 7 | "His gaze dropped to her" | | 8 | "He shifted his weight onto" | | 9 | "He said it quietly, as" | | 10 | "He took a breath that" | | 11 | "He didn't argue" |
| | ratio | 0.4 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 28 | | totalSentences | 30 | | matches | | 0 | "The bar's bass thudded through" | | 1 | "She had a mug of" | | 2 | "Nobody who lived in this" | | 3 | "She didn't get up right" | | 4 | "She let the silence stretch" | | 5 | "Rory crossed the room in" | | 6 | "The hallway bulb had burned" | | 7 | "She knew who it was" | | 8 | "That was the problem." | | 9 | "She undid the first chain," | | 10 | "She left the third sliding" | | 11 | "Lucien Moreau stood on the" | | 12 | "He hadn't bothered with an" | | 13 | "The other was black, the" | | 14 | "Rory folded her arms over" | | 15 | "His gaze dropped to her" | | 16 | "He shifted his weight onto" | | 17 | "The blade inside it was" | | 18 | "He said it quietly, as" | | 19 | "Rory's jaw tightened." |
| | ratio | 0.933 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 30 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 15 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 75.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 10 | | uselessAdditionCount | 1 | | matches | | 0 | "He said, as if the hallway might be listening" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 5 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 24 | | tagDensity | 0.208 | | leniency | 0.417 | | rawRatio | 0 | | effectiveRatio | 0 | |