| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 8 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 29 | | tagDensity | 0.276 | | leniency | 0.552 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 91.67% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1200 | | totalAiIsmAdverbs | 2 | | 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) | |
| 45.83% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1200 | | totalAiIsms | 13 | | found | | | highlights | | 0 | "gloom" | | 1 | "glint" | | 2 | "shattered" | | 3 | "echoing" | | 4 | "could feel" | | 5 | "tinged" | | 6 | "etched" | | 7 | "chill" | | 8 | "shimmered" | | 9 | "pulsed" | | 10 | "spectral" |
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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 | 125 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 0 | | narrationSentences | 125 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 146 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 37 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 2 | | markdownWords | 10 | | totalWords | 1182 | | ratio | 0.008 | | matches | | 0 | "“Next train: never.”" | | 1 | "“It’s not locked. But it should be.”" |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 12 | | unquotedAttributions | 0 | | matches | (empty) | |
| 66.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 32 | | wordCount | 906 | | uniqueNames | 11 | | maxNameDensity | 1.1 | | worstName | "Lyle" | | maxWindowNameDensity | 3 | | worstWindowName | "Lyle" | | discoveredNames | | Camden | 1 | | Town | 1 | | Underground | 1 | | Station | 1 | | Jubilee | 1 | | Harlow | 1 | | Quinn | 7 | | Morris | 4 | | July | 1 | | Lyle | 10 | | Three | 4 |
| | persons | | 0 | "Station" | | 1 | "Harlow" | | 2 | "Quinn" | | 3 | "Morris" | | 4 | "Lyle" |
| | places | | 0 | "Camden" | | 1 | "Town" | | 2 | "Underground" | | 3 | "July" |
| | globalScore | 0.948 | | windowScore | 0.667 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 55 | | glossingSentenceCount | 1 | | matches | | 0 | "looked like a nail or a knife" |
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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 | 1182 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 146 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 75 | | mean | 15.76 | | std | 17.07 | | cv | 1.083 | | sampleLengths | | 0 | 98 | | 1 | 16 | | 2 | 55 | | 3 | 28 | | 4 | 5 | | 5 | 3 | | 6 | 50 | | 7 | 37 | | 8 | 4 | | 9 | 7 | | 10 | 35 | | 11 | 28 | | 12 | 41 | | 13 | 5 | | 14 | 3 | | 15 | 8 | | 16 | 42 | | 17 | 3 | | 18 | 3 | | 19 | 6 | | 20 | 13 | | 21 | 55 | | 22 | 4 | | 23 | 2 | | 24 | 30 | | 25 | 2 | | 26 | 4 | | 27 | 25 | | 28 | 4 | | 29 | 2 | | 30 | 27 | | 31 | 1 | | 32 | 16 | | 33 | 41 | | 34 | 19 | | 35 | 23 | | 36 | 7 | | 37 | 13 | | 38 | 6 | | 39 | 8 | | 40 | 4 | | 41 | 2 | | 42 | 1 | | 43 | 5 | | 44 | 3 | | 45 | 37 | | 46 | 5 | | 47 | 4 | | 48 | 5 | | 49 | 35 |
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| 91.23% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 5 | | totalSentences | 125 | | matches | | 0 | "been assigned" | | 1 | "was shattered" | | 2 | "was etched" | | 3 | "been pried" | | 4 | "was pulled" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 161 | | matches | (empty) | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 18 | | semicolonCount | 0 | | flaggedSentences | 12 | | totalSentences | 146 | | ratio | 0.082 | | matches | | 0 | "The torch strapped to her belt cut a narrow beam through the gloom, catching the glint of rusted rails and the shattered face of an old station sign—*“Next train: never.”*" | | 1 | "She could feel it—the wrongness." | | 2 | "Not in graffiti—though there was spray paint—but in symbols." | | 3 | "Fingertips slightly wrinkled—consistent with exposure to moisture, yes." | | 4 | "Ash with flecks of red thread embedded in it—like fabric, but finely ground." | | 5 | "The face was etched with tiny sigils—geometric patterns that made her eyes ache if she stared too long." | | 6 | "And it pointed—unerringly—toward the back wall of the ticket booth, where a section of plaster had crumbled away, revealing a dark fissure in the brickwork." | | 7 | "And the temperature—she held her hand near it—dropped ten degrees in that space." | | 8 | "And beneath—embedded in the concrete—a shallow metal grate, rust-eaten but still functional." | | 9 | "The smell—ozone and wet stone and something sickly sweet—rose from it like breath." | | 10 | "She saw Lyle’s expression—skepticism, thinly veiled." | | 11 | "But she remembered the symbol he’d scrawled on the warehouse floor in his own blood before he was pulled—literally pulled—through a wall that hadn’t opened." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 321 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 8 | | adverbRatio | 0.024922118380062305 | | lyAdverbCount | 2 | | lyAdverbRatio | 0.006230529595015576 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 146 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 146 | | mean | 8.1 | | std | 7.33 | | cv | 0.905 | | sampleLengths | | 0 | 31 | | 1 | 16 | | 2 | 21 | | 3 | 30 | | 4 | 11 | | 5 | 5 | | 6 | 21 | | 7 | 9 | | 8 | 3 | | 9 | 2 | | 10 | 20 | | 11 | 9 | | 12 | 11 | | 13 | 6 | | 14 | 2 | | 15 | 5 | | 16 | 3 | | 17 | 9 | | 18 | 16 | | 19 | 3 | | 20 | 5 | | 21 | 17 | | 22 | 10 | | 23 | 5 | | 24 | 22 | | 25 | 4 | | 26 | 7 | | 27 | 2 | | 28 | 18 | | 29 | 7 | | 30 | 5 | | 31 | 3 | | 32 | 8 | | 33 | 20 | | 34 | 3 | | 35 | 6 | | 36 | 9 | | 37 | 23 | | 38 | 5 | | 39 | 3 | | 40 | 8 | | 41 | 3 | | 42 | 5 | | 43 | 3 | | 44 | 5 | | 45 | 8 | | 46 | 14 | | 47 | 2 | | 48 | 2 | | 49 | 3 |
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| 61.64% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 10 | | diversityRatio | 0.410958904109589 | | totalSentences | 146 | | uniqueOpeners | 60 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 5 | | totalSentences | 101 | | matches | | 0 | "Just a faint silver powder" | | 1 | "Instead, she studied the walls." | | 2 | "Then the temperature dropped." | | 3 | "Then he screamed." | | 4 | "Somewhere the needle knew." |
| | ratio | 0.05 | |
| 97.23% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 31 | | totalSentences | 101 | | matches | | 0 | "She didn’t need the radio" | | 1 | "She could feel it—the wrongness." | | 2 | "They were covered." | | 3 | "Her fingers brushed the worn" | | 4 | "He'd been assigned to her" | | 5 | "She hadn’t asked for him." | | 6 | "She stepped toward the body," | | 7 | "She reached into her coat," | | 8 | "She examined the man’s hands." | | 9 | "She leaned closer." | | 10 | "It was ash." | | 11 | "Her gaze lifted, sweeping across" | | 12 | "She stood, walked to it," | | 13 | "She picked it up." | | 14 | "Her breath fogged." | | 15 | "He hadn’t noticed the crack." | | 16 | "He hadn’t noticed the compass." | | 17 | "He gestured at the body" | | 18 | "She turned the compass in" | | 19 | "She’d found his notebook later." |
| | ratio | 0.307 | |
| 100.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 63 | | totalSentences | 101 | | matches | | 0 | "Rainwater dripped through a collapsed" | | 1 | "The air carried a fungal" | | 2 | "Detective Harlow Quinn stepped over" | | 3 | "The torch strapped to her" | | 4 | "She didn’t need the radio" | | 5 | "She could feel it—the wrongness." | | 6 | "The body lay sprawled beside" | | 7 | "Forensics techs in white suits" | | 8 | "They were covered." | | 9 | "Crude, hurried things etched into" | | 10 | "Lines that spiraled and stopped." | | 11 | "Her fingers brushed the worn" | | 12 | "This felt like that." | | 13 | "DS Lyle, young, eager, already" | | 14 | "He'd been assigned to her" | | 15 | "She hadn’t asked for him." | | 16 | "Lyle said, flipping a page" | | 17 | "Quinn didn’t answer." | | 18 | "She stepped toward the body," | | 19 | "The silver dust was finer" |
| | ratio | 0.624 | |
| 49.50% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 101 | | matches | | 0 | "Because they called it stress." |
| | ratio | 0.01 | |
| 95.24% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 30 | | technicalSentenceCount | 2 | | matches | | 0 | "The face was etched with tiny sigils—geometric patterns that made her eyes ache if she stared too long." | | 1 | "But she remembered the symbol he’d scrawled on the warehouse floor in his own blood before he was pulled—literally pulled—through a wall that hadn’t opened." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 8 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 81.03% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 6 | | fancyCount | 2 | | fancyTags | | 0 | "He’d (would)" | | 1 | "she added (add)" |
| | dialogueSentences | 29 | | tagDensity | 0.207 | | leniency | 0.414 | | rawRatio | 0.333 | | effectiveRatio | 0.138 | |