| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 5 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 35 | | tagDensity | 0.143 | | leniency | 0.286 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 86.16% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1084 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | 0 | "suddenly" | | 1 | "precisely" | | 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) | |
| 0.00% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1084 | | totalAiIsms | 23 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | | | 13 | | | 14 | | | 15 | | | 16 | | | 17 | | | 18 | |
| | highlights | | 0 | "pristine" | | 1 | "intensity" | | 2 | "tracing" | | 3 | "familiar" | | 4 | "scanned" | | 5 | "vibrated" | | 6 | "resonance" | | 7 | "chill" | | 8 | "charged" | | 9 | "measured" | | 10 | "rhythmic" | | 11 | "pounding" | | 12 | "chaotic" | | 13 | "symphony" | | 14 | "stark" | | 15 | "silence" | | 16 | "pulse" | | 17 | "flicker" | | 18 | "gloom" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "air was thick with" | | count | 1 |
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| | highlights | | 0 | "The air was thick with" |
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| 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 | 1 | | hedgeCount | 0 | | narrationSentences | 36 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 66 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 48 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1080 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 5 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 9 | | wordCount | 639 | | uniqueNames | 7 | | maxNameDensity | 0.47 | | worstName | "Lucien" | | maxWindowNameDensity | 1 | | worstWindowName | "Lucien" | | discoveredNames | | Lucien | 3 | | Ritz | 1 | | East | 1 | | London | 1 | | Eva | 1 | | Brick | 1 | | Lane | 1 |
| | persons | | | places | | 0 | "East" | | 1 | "London" | | 2 | "Brick" | | 3 | "Lane" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 32 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.926 | | wordCount | 1080 | | matches | | 0 | "not past me, but closer" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 66 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 44 | | mean | 24.55 | | std | 18.93 | | cv | 0.771 | | sampleLengths | | 0 | 85 | | 1 | 8 | | 2 | 28 | | 3 | 16 | | 4 | 28 | | 5 | 11 | | 6 | 9 | | 7 | 38 | | 8 | 27 | | 9 | 6 | | 10 | 2 | | 11 | 21 | | 12 | 48 | | 13 | 12 | | 14 | 10 | | 15 | 33 | | 16 | 2 | | 17 | 73 | | 18 | 19 | | 19 | 5 | | 20 | 26 | | 21 | 38 | | 22 | 15 | | 23 | 5 | | 24 | 81 | | 25 | 26 | | 26 | 16 | | 27 | 36 | | 28 | 31 | | 29 | 11 | | 30 | 17 | | 31 | 36 | | 32 | 22 | | 33 | 10 | | 34 | 44 | | 35 | 11 | | 36 | 22 | | 37 | 32 | | 38 | 22 | | 39 | 27 | | 40 | 34 | | 41 | 12 | | 42 | 4 | | 43 | 21 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 36 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 90 | | matches | | |
| 12.99% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 3 | | semicolonCount | 1 | | flaggedSentences | 3 | | totalSentences | 66 | | ratio | 0.045 | | matches | | 0 | "He tilted his head, a ghost of a smile—sharp, predatory, and entirely too familiar—playing at his mouth." | | 1 | "\"It pays the bills. It doesn't ask questions. You should try it sometime; the simplicity might do wonders for your disposition.\"" | | 2 | "He moved then, not past me, but closer—close enough that the scent of him, sandalwood and something metallic, like an approaching storm, crowded out the smell of curry from the flat below." |
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| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 648 | | adjectiveStacks | 1 | | stackExamples | | 0 | "jagged, crescent-shaped scar" |
| | adverbCount | 21 | | adverbRatio | 0.032407407407407406 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.007716049382716049 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 66 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 66 | | mean | 16.36 | | std | 8.65 | | cv | 0.528 | | sampleLengths | | 0 | 33 | | 1 | 5 | | 2 | 47 | | 3 | 8 | | 4 | 4 | | 5 | 24 | | 6 | 16 | | 7 | 18 | | 8 | 10 | | 9 | 11 | | 10 | 9 | | 11 | 17 | | 12 | 21 | | 13 | 27 | | 14 | 6 | | 15 | 2 | | 16 | 21 | | 17 | 32 | | 18 | 16 | | 19 | 12 | | 20 | 10 | | 21 | 11 | | 22 | 22 | | 23 | 2 | | 24 | 37 | | 25 | 16 | | 26 | 20 | | 27 | 13 | | 28 | 3 | | 29 | 3 | | 30 | 5 | | 31 | 26 | | 32 | 16 | | 33 | 22 | | 34 | 15 | | 35 | 5 | | 36 | 18 | | 37 | 21 | | 38 | 22 | | 39 | 20 | | 40 | 18 | | 41 | 8 | | 42 | 16 | | 43 | 17 | | 44 | 19 | | 45 | 31 | | 46 | 11 | | 47 | 17 | | 48 | 16 | | 49 | 20 |
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| 50.51% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 10 | | diversityRatio | 0.3939393939393939 | | totalSentences | 66 | | uniqueOpeners | 26 | |
| 92.59% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 36 | | matches | | 0 | "Instead, the frame held Lucien." |
| | ratio | 0.028 | |
| 0.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 25 | | totalSentences | 36 | | matches | | 0 | "He stood in the narrow" | | 1 | "He didn't step back." | | 2 | "He didn't even blink, his" | | 3 | "I blocked the threshold, my" | | 4 | "He tilted his head, a" | | 5 | "He scanned the cramped entryway" | | 6 | "He moved then, not past" | | 7 | "He pressed the ivory head" | | 8 | "He laughed, a low, rasping" | | 9 | "He pulled a folded scrap" | | 10 | "His skin was cold, a" | | 11 | "I stared at the paper," | | 12 | "It wasn't mine." | | 13 | "It was Eva's." | | 14 | "I let the door widen" | | 15 | "I swept past him, the" | | 16 | "He followed, his pace measured," | | 17 | "We hit the Brick Lane" | | 18 | "I muttered, not looking back" | | 19 | "He caught my arm near" |
| | ratio | 0.694 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 35 | | totalSentences | 36 | | matches | | 0 | "The third deadbolt slid back" | | 1 | "He stood in the narrow" | | 2 | "He didn't step back." | | 3 | "He didn't even blink, his" | | 4 | "I blocked the threshold, my" | | 5 | "He tilted his head, a" | | 6 | "He scanned the cramped entryway" | | 7 | "He moved then, not past" | | 8 | "He pressed the ivory head" | | 9 | "He laughed, a low, rasping" | | 10 | "He pulled a folded scrap" | | 11 | "His skin was cold, a" | | 12 | "I stared at the paper," | | 13 | "It wasn't mine." | | 14 | "It was Eva's." | | 15 | "I let the door widen" | | 16 | "Ptolemy, the tabby, wound around" | | 17 | "I swept past him, the" | | 18 | "He followed, his pace measured," | | 19 | "We hit the Brick Lane" |
| | ratio | 0.972 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 36 | | matches | (empty) | | ratio | 0 | |
| 37.04% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 27 | | technicalSentenceCount | 4 | | matches | | 0 | "He stood in the narrow light of the stairwell, charcoal wool coat pristine, one hand resting atop the ivory head of his cane as if he were waiting for a carriag…" | | 1 | "He didn't even blink, his heterochromatic eyes locking onto mine with an intensity that made the stale air in the corridor feel suddenly thin." | | 2 | "He laughed, a low, rasping sound that vibrated against my ribs." | | 3 | "His skin was cold, a chill that seeped beneath my sleeves and settled in my marrow." |
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| 25.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 5 | | uselessAdditionCount | 1 | | matches | | 0 | "Lucien commanded, his thumb sliding the concealed spring on his cane" |
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| 92.86% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 2 | | fancyCount | 2 | | fancyTags | | 0 | "I muttered (mutter)" | | 1 | "I whispered (whisper)" |
| | dialogueSentences | 35 | | tagDensity | 0.057 | | leniency | 0.114 | | rawRatio | 1 | | effectiveRatio | 0.114 | |