| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 5 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 20 | | tagDensity | 0.25 | | leniency | 0.5 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 87.94% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1244 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | 0 | "slightly" | | 1 | "slowly" | | 2 | "really" |
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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) | |
| 63.83% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1244 | | totalAiIsms | 9 | | found | | | highlights | | 0 | "gloom" | | 1 | "weight" | | 2 | "silence" | | 3 | "standard" | | 4 | "vibrated" | | 5 | "velvet" | | 6 | "scanned" | | 7 | "echoing" |
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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 | 80 | | matches | (empty) | |
| 89.29% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 2 | | narrationSentences | 80 | | filterMatches | | | hedgeMatches | | |
| 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 | 32 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1242 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 4 | | unquotedAttributions | 0 | | matches | (empty) | |
| 66.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 40 | | wordCount | 1070 | | uniqueNames | 12 | | maxNameDensity | 1.5 | | worstName | "Harlow" | | maxWindowNameDensity | 3 | | worstWindowName | "Harlow" | | discoveredNames | | Harlow | 16 | | Quinn | 1 | | Herrera | 1 | | Saint | 1 | | Christopher | 1 | | Camden | 1 | | Tube | 1 | | Tommy | 14 | | Morris | 1 | | London | 1 | | Veil | 1 | | Market | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Herrera" | | 3 | "Saint" | | 4 | "Christopher" | | 5 | "Tommy" | | 6 | "Morris" | | 7 | "Market" |
| | places | | | globalScore | 0.752 | | windowScore | 0.667 | |
| 45.83% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 72 | | glossingSentenceCount | 3 | | matches | | 0 | "sounded like a thousand whispered conversa" | | 1 | "looked like dried human tongues" | | 2 | "looked like weathered parchment" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.805 | | wordCount | 1242 | | matches | | 0 | "not by electricity, but by hundreds of flickering glass lanterns suspended from the" |
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| 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 | 43 | | mean | 28.88 | | std | 18.45 | | cv | 0.639 | | sampleLengths | | 0 | 46 | | 1 | 54 | | 2 | 2 | | 3 | 49 | | 4 | 59 | | 5 | 14 | | 6 | 61 | | 7 | 15 | | 8 | 13 | | 9 | 56 | | 10 | 9 | | 11 | 17 | | 12 | 30 | | 13 | 10 | | 14 | 16 | | 15 | 8 | | 16 | 8 | | 17 | 62 | | 18 | 37 | | 19 | 27 | | 20 | 16 | | 21 | 55 | | 22 | 9 | | 23 | 31 | | 24 | 64 | | 25 | 33 | | 26 | 6 | | 27 | 13 | | 28 | 39 | | 29 | 47 | | 30 | 44 | | 31 | 11 | | 32 | 21 | | 33 | 50 | | 34 | 21 | | 35 | 18 | | 36 | 44 | | 37 | 29 | | 38 | 37 | | 39 | 11 | | 40 | 17 | | 41 | 8 | | 42 | 25 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 80 | | matches | (empty) | |
| 80.95% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 3 | | totalVerbs | 168 | | matches | | 0 | "was heading" | | 1 | "was speaking" | | 2 | "was handing" |
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| 82.07% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 2 | | semicolonCount | 1 | | flaggedSentences | 2 | | totalSentences | 94 | | ratio | 0.021 | | matches | | 0 | "Crowds of people—and things that only wore the shape of people—jostled through tight lanes of makeshift stalls." | | 1 | "Every instinct told her she was a foreign cell in a hostile body; the market seemed to quiet as she passed, eyes tracking her badge-less trench coat, recognizing the scent of law." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1075 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 17 | | adverbRatio | 0.01581395348837209 | | lyAdverbCount | 13 | | lyAdverbRatio | 0.012093023255813953 | |
| 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 | 13.21 | | std | 5.93 | | cv | 0.449 | | sampleLengths | | 0 | 20 | | 1 | 9 | | 2 | 17 | | 3 | 22 | | 4 | 20 | | 5 | 8 | | 6 | 4 | | 7 | 2 | | 8 | 5 | | 9 | 4 | | 10 | 17 | | 11 | 23 | | 12 | 13 | | 13 | 12 | | 14 | 15 | | 15 | 19 | | 16 | 14 | | 17 | 14 | | 18 | 15 | | 19 | 12 | | 20 | 8 | | 21 | 12 | | 22 | 15 | | 23 | 13 | | 24 | 8 | | 25 | 16 | | 26 | 20 | | 27 | 12 | | 28 | 9 | | 29 | 17 | | 30 | 20 | | 31 | 10 | | 32 | 10 | | 33 | 10 | | 34 | 6 | | 35 | 8 | | 36 | 8 | | 37 | 13 | | 38 | 16 | | 39 | 23 | | 40 | 7 | | 41 | 3 | | 42 | 8 | | 43 | 12 | | 44 | 17 | | 45 | 7 | | 46 | 20 | | 47 | 16 | | 48 | 21 | | 49 | 9 |
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| 52.13% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 6 | | diversityRatio | 0.35106382978723405 | | totalSentences | 94 | | uniqueOpeners | 33 | |
| 84.39% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 79 | | matches | | 0 | "Instead, he withdrew a small," | | 1 | "Gradually, a low hum vibrated" |
| | ratio | 0.025 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 21 | | totalSentences | 79 | | matches | | 0 | "Her worn leather watch scraped" | | 1 | "She didn't slow down." | | 2 | "He leaped over a pile" | | 3 | "She closed the distance, her" | | 4 | "He was heading toward the" | | 5 | "He pressed the bone shard" | | 6 | "He turned his head slowly," | | 7 | "His warm brown eyes showed" | | 8 | "He slipped through the narrow" | | 9 | "He dropped into the blackness" | | 10 | "It was the same scent" | | 11 | "She pulled a heavy tactical" | | 12 | "She gripped her flashlight tighter," | | 13 | "It sounded like a thousand" | | 14 | "She scanned the sea of" | | 15 | "She broke into a fast" | | 16 | "She spotted Tommy near a" | | 17 | "He was speaking urgently to" | | 18 | "He snatched the bottle, shoved" | | 19 | "She ignored the hiss of" |
| | ratio | 0.266 | |
| 16.96% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 70 | | totalSentences | 79 | | matches | | 0 | "Rain sliced through the yellow" | | 1 | "Water pooled in the collars" | | 2 | "Tommy Herrera was fast, but" | | 3 | "Harlow reached out, her fingers" | | 4 | "Her worn leather watch scraped" | | 5 | "She didn't slow down." | | 6 | "The wind swallowed her voice." | | 7 | "Tommy didn't look back." | | 8 | "He leaped over a pile" | | 9 | "A silver Saint Christopher medallion" | | 10 | "Harlow vaulted the debris, landing" | | 11 | "The impact rattled up her" | | 12 | "She closed the distance, her" | | 13 | "He was heading toward the" | | 14 | "Tommy slid down a concrete" | | 15 | "A massive padlock hung from" | | 16 | "He pressed the bone shard" | | 17 | "The metal shrieked, the heavy" | | 18 | "Harlow skidded to the top" | | 19 | "Tommy paused, his hand gripping" |
| | ratio | 0.886 | |
| 63.29% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 79 | | matches | | 0 | "If she went down there," |
| | ratio | 0.013 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 53 | | technicalSentenceCount | 2 | | matches | | 0 | "Tommy Herrera was fast, but his left leg dragged slightly, a subtle hitch in his stride that kept him within her sights." | | 1 | "A silver Saint Christopher medallion bounced against his chest, catching the neon glow of a distant billboard before vanishing back under his jacket." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 5 | | uselessAdditionCount | 2 | | matches | | 0 | "Harlow yelled, her boots splashing through thick, stagnant water" | | 1 | "Tommy said, his voice echoing off the curved brick walls" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 4 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 20 | | tagDensity | 0.2 | | leniency | 0.4 | | rawRatio | 0.25 | | effectiveRatio | 0.1 | |