| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 1 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 48 | | tagDensity | 0.021 | | leniency | 0.042 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 85.92% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1420 | | totalAiIsmAdverbs | 4 | | found | | | highlights | | 0 | "slightly" | | 1 | "truly" | | 2 | "really" |
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| 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) | |
| 64.79% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1420 | | totalAiIsms | 10 | | found | | | highlights | | 0 | "traced" | | 1 | "measured" | | 2 | "rhythmic" | | 3 | "scanning" | | 4 | "gloom" | | 5 | "weight" | | 6 | "warmth" | | 7 | "familiar" | | 8 | "silence" |
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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 | 70 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 70 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 117 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 43 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1419 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 5 | | unquotedAttributions | 0 | | matches | (empty) | |
| 50.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 38 | | wordCount | 850 | | uniqueNames | 8 | | maxNameDensity | 1.53 | | worstName | "Julian" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Julian" | | discoveredNames | | Raven | 1 | | Nest | 1 | | Soho | 1 | | Rory | 11 | | Cardiff | 1 | | Oxfords | 1 | | Silas | 9 | | Julian | 13 |
| | persons | | 0 | "Raven" | | 1 | "Nest" | | 2 | "Rory" | | 3 | "Oxfords" | | 4 | "Silas" | | 5 | "Julian" |
| | places | | | globalScore | 0.735 | | windowScore | 0.5 | |
| 66.67% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 60 | | glossingSentenceCount | 2 | | matches | | 0 | "quite a sneer but lacked any warmth" | | 1 | "looked like he wanted to say something—so" |
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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 | 1419 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 117 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 81 | | mean | 17.52 | | std | 14.72 | | cv | 0.84 | | sampleLengths | | 0 | 65 | | 1 | 54 | | 2 | 66 | | 3 | 8 | | 4 | 43 | | 5 | 1 | | 6 | 20 | | 7 | 1 | | 8 | 38 | | 9 | 23 | | 10 | 6 | | 11 | 10 | | 12 | 2 | | 13 | 20 | | 14 | 4 | | 15 | 31 | | 16 | 14 | | 17 | 14 | | 18 | 3 | | 19 | 34 | | 20 | 12 | | 21 | 19 | | 22 | 3 | | 23 | 20 | | 24 | 20 | | 25 | 3 | | 26 | 28 | | 27 | 17 | | 28 | 6 | | 29 | 33 | | 30 | 31 | | 31 | 8 | | 32 | 35 | | 33 | 1 | | 34 | 7 | | 35 | 8 | | 36 | 9 | | 37 | 23 | | 38 | 14 | | 39 | 11 | | 40 | 5 | | 41 | 11 | | 42 | 24 | | 43 | 12 | | 44 | 29 | | 45 | 9 | | 46 | 12 | | 47 | 8 | | 48 | 42 | | 49 | 31 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 70 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 136 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 1 | | semicolonCount | 0 | | flaggedSentences | 1 | | totalSentences | 117 | | ratio | 0.009 | | matches | | 0 | "He looked like he wanted to say something—something about the letters he’d written and never sent, or the way he still checked the guest lists of every legal seminar for her name." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 857 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 18 | | adverbRatio | 0.021003500583430573 | | lyAdverbCount | 6 | | lyAdverbRatio | 0.007001166861143524 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 117 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 117 | | mean | 12.13 | | std | 8.23 | | cv | 0.679 | | sampleLengths | | 0 | 20 | | 1 | 10 | | 2 | 20 | | 3 | 15 | | 4 | 10 | | 5 | 22 | | 6 | 22 | | 7 | 4 | | 8 | 18 | | 9 | 10 | | 10 | 17 | | 11 | 17 | | 12 | 2 | | 13 | 6 | | 14 | 6 | | 15 | 16 | | 16 | 10 | | 17 | 11 | | 18 | 1 | | 19 | 20 | | 20 | 1 | | 21 | 8 | | 22 | 15 | | 23 | 15 | | 24 | 5 | | 25 | 18 | | 26 | 6 | | 27 | 10 | | 28 | 2 | | 29 | 20 | | 30 | 4 | | 31 | 20 | | 32 | 11 | | 33 | 14 | | 34 | 14 | | 35 | 3 | | 36 | 34 | | 37 | 12 | | 38 | 13 | | 39 | 6 | | 40 | 3 | | 41 | 9 | | 42 | 11 | | 43 | 20 | | 44 | 3 | | 45 | 28 | | 46 | 17 | | 47 | 6 | | 48 | 19 | | 49 | 14 |
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| 42.31% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 9 | | diversityRatio | 0.2564102564102564 | | totalSentences | 117 | | uniqueOpeners | 30 | |
| 49.02% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 68 | | matches | | 0 | "Instead, he drained the rest" |
| | ratio | 0.015 | |
| 49.41% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 29 | | totalSentences | 68 | | matches | | 0 | "She traced the crescent-shaped scar" | | 1 | "His left leg dragged slightly," | | 2 | "He polished a highball glass" | | 3 | "He wore a tailored navy" | | 4 | "His frame had filled out," | | 5 | "He squinted through the gloom," | | 6 | "He approached the bar, his" | | 7 | "He stopped three feet away," | | 8 | "His face had sharpened, the" | | 9 | "He didn't speak, but his" | | 10 | "He looked at the peeling" | | 11 | "He didn't look at the" | | 12 | "He smelled of sandalwood and" | | 13 | "He reached out, his fingers" | | 14 | "He looked at her wrist," | | 15 | "He downed half of it" | | 16 | "He set the glass down" | | 17 | "He didn't move from his" | | 18 | "She thought of the quiet" | | 19 | "He looked like he wanted" |
| | ratio | 0.426 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 63 | | totalSentences | 68 | | matches | | 0 | "The green neon sign of" | | 1 | "Aurora leaned against the mahogany" | | 2 | "She traced the crescent-shaped scar" | | 3 | "Silas moved behind the counter" | | 4 | "His left leg dragged slightly," | | 5 | "He polished a highball glass" | | 6 | "The door creaked open." | | 7 | "A gust of damp night" | | 8 | "A man stepped inside, pausing" | | 9 | "He wore a tailored navy" | | 10 | "His frame had filled out," | | 11 | "The glass in her hand" | | 12 | "Julian didn't see her at" | | 13 | "He squinted through the gloom," | | 14 | "The umbrella slipped from his" | | 15 | "The name sounded foreign in" | | 16 | "He approached the bar, his" | | 17 | "He stopped three feet away," | | 18 | "His face had sharpened, the" | | 19 | "Silas set the glass down." |
| | ratio | 0.926 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 68 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 49 | | technicalSentenceCount | 2 | | matches | | 0 | "His left leg dragged slightly, a rhythmic scuff that punctuated the low murmur of the few patrons scattered among the dim booths." | | 1 | "He didn't speak, but his presence shifted, a subtle narrowing of his shoulders that signaled he was watching." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 1 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 1 | | fancyCount | 1 | | fancyTags | | 0 | "Julian whispered (whisper)" |
| | dialogueSentences | 48 | | tagDensity | 0.021 | | leniency | 0.042 | | rawRatio | 1 | | effectiveRatio | 0.042 | |