| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 17 | | adverbTagCount | 1 | | adverbTags | | 0 | "Harlow said softly [softly]" |
| | dialogueSentences | 32 | | tagDensity | 0.531 | | leniency | 1 | | rawRatio | 0.059 | | effectiveRatio | 0.059 | |
| 72.86% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1474 | | totalAiIsmAdverbs | 8 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | adverb | "reluctantly" | | count | 1 |
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| | highlights | | 0 | "slowly" | | 1 | "carefully" | | 2 | "nervously" | | 3 | "tightly" | | 4 | "softly" | | 5 | "reluctantly" |
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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) | |
| 55.90% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1474 | | totalAiIsms | 13 | | found | | | highlights | | 0 | "flicker" | | 1 | "methodical" | | 2 | "silk" | | 3 | "velvet" | | 4 | "etched" | | 5 | "intricate" | | 6 | "vibrated" | | 7 | "standard" | | 8 | "echoed" | | 9 | "pulse" | | 10 | "stomach" | | 11 | "tracing" | | 12 | "stark" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "knuckles turned white" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 1 | | narrationSentences | 82 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 1 | | narrationSentences | 82 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 97 | | 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 | 3 | | markdownWords | 7 | | totalWords | 1468 | | ratio | 0.005 | | matches | | 0 | "A shadow compass," | | 1 | "into" | | 2 | "The Veil Market." |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 17 | | unquotedAttributions | 0 | | matches | (empty) | |
| 33.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 47 | | wordCount | 1078 | | uniqueNames | 15 | | maxNameDensity | 2.13 | | worstName | "Harlow" | | maxWindowNameDensity | 4 | | worstWindowName | "Harlow" | | discoveredNames | | Tube | 1 | | Camden | 1 | | Harlow | 23 | | Quinn | 1 | | London | 1 | | Miller | 6 | | Metropolitan | 1 | | Police | 1 | | Morris | 2 | | Soho | 1 | | Thames | 1 | | Latin | 1 | | Greek | 1 | | Eva | 5 | | Veil | 1 |
| | persons | | 0 | "Camden" | | 1 | "Harlow" | | 2 | "Quinn" | | 3 | "Miller" | | 4 | "Morris" | | 5 | "Eva" |
| | places | | 0 | "London" | | 1 | "Metropolitan" | | 2 | "Soho" | | 3 | "Thames" |
| | globalScore | 0.433 | | windowScore | 0.333 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 66 | | glossingSentenceCount | 1 | | matches | | 0 | "instrument that seemed to pulse against her thumb, she felt the same icy certainty settle in her stomach" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.681 | | wordCount | 1468 | | matches | | 0 | "not north, but directly down the pitch-black mouth of the northern tunnel" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 97 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 40 | | mean | 36.7 | | std | 19.47 | | cv | 0.531 | | sampleLengths | | 0 | 57 | | 1 | 28 | | 2 | 60 | | 3 | 48 | | 4 | 11 | | 5 | 1 | | 6 | 44 | | 7 | 53 | | 8 | 38 | | 9 | 46 | | 10 | 39 | | 11 | 12 | | 12 | 72 | | 13 | 35 | | 14 | 88 | | 15 | 17 | | 16 | 8 | | 17 | 74 | | 18 | 8 | | 19 | 51 | | 20 | 42 | | 21 | 50 | | 22 | 43 | | 23 | 54 | | 24 | 9 | | 25 | 24 | | 26 | 31 | | 27 | 21 | | 28 | 26 | | 29 | 16 | | 30 | 44 | | 31 | 28 | | 32 | 43 | | 33 | 41 | | 34 | 14 | | 35 | 44 | | 36 | 56 | | 37 | 30 | | 38 | 29 | | 39 | 33 |
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| 88.15% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 4 | | totalSentences | 82 | | matches | | 0 | "been arranged" | | 1 | "been made" | | 2 | "been dropped" | | 3 | "been slapped" |
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| 82.35% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 3 | | totalVerbs | 170 | | matches | | 0 | "was reading" | | 1 | "wasn't listening" | | 2 | "was standing" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 6 | | semicolonCount | 1 | | flaggedSentences | 5 | | totalSentences | 97 | | ratio | 0.052 | | matches | | 0 | "A tiny fragment of carved ivory—or polished femur—lay tagged under a plastic yellow marker." | | 1 | "She wasn't listening to Miller's narrative; she was reading the room." | | 2 | "When she tilted it toward her penlight, she saw the face was coverless—no glass—and etched with tiny, intricate sigils instead of cardinal points." | | 3 | "It felt cold—colder than the subterranean air." | | 4 | "Next to it was an impression in the dirt—the distinct rectangular outline of a heavy bag that had been dropped in haste and picked back up." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1092 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 28 | | adverbRatio | 0.02564102564102564 | | lyAdverbCount | 15 | | lyAdverbRatio | 0.013736263736263736 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 97 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 97 | | mean | 15.13 | | std | 9 | | cv | 0.595 | | sampleLengths | | 0 | 23 | | 1 | 34 | | 2 | 28 | | 3 | 26 | | 4 | 11 | | 5 | 23 | | 6 | 5 | | 7 | 13 | | 8 | 1 | | 9 | 29 | | 10 | 11 | | 11 | 1 | | 12 | 16 | | 13 | 14 | | 14 | 14 | | 15 | 18 | | 16 | 35 | | 17 | 14 | | 18 | 11 | | 19 | 8 | | 20 | 5 | | 21 | 16 | | 22 | 9 | | 23 | 21 | | 24 | 7 | | 25 | 20 | | 26 | 12 | | 27 | 12 | | 28 | 3 | | 29 | 6 | | 30 | 15 | | 31 | 23 | | 32 | 5 | | 33 | 20 | | 34 | 8 | | 35 | 20 | | 36 | 7 | | 37 | 9 | | 38 | 27 | | 39 | 17 | | 40 | 10 | | 41 | 25 | | 42 | 17 | | 43 | 4 | | 44 | 4 | | 45 | 21 | | 46 | 53 | | 47 | 8 | | 48 | 20 | | 49 | 31 |
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| 68.75% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 4 | | diversityRatio | 0.4375 | | totalSentences | 96 | | uniqueOpeners | 42 | |
| 41.67% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 80 | | matches | | 0 | "Slowly, reluctantly, she let go" |
| | ratio | 0.013 | |
| 95.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 25 | | totalSentences | 80 | | matches | | 0 | "She stood on the edge" | | 1 | "He gestured toward the center" | | 2 | "She checked the worn leather" | | 3 | "She raised her eyes, her" | | 4 | "she said, her voice dry" | | 5 | "She wasn't listening to Miller's" | | 6 | "It looked like a bazaar." | | 7 | "It was sulfur, dried lotus," | | 8 | "She stopped beside a overturned" | | 9 | "She carefully scooped up the" | | 10 | "It was a small brass" | | 11 | "It vibrated wildly, ticking to" | | 12 | "She turned the casing over" | | 13 | "It felt cold—colder than the" | | 14 | "she insisted, tracing the arc" | | 15 | "She shone her torch down." | | 16 | "It was a book." | | 17 | "She shone her light farther" | | 18 | "She wore an oversized coat" | | 19 | "She knew that girl." |
| | ratio | 0.313 | |
| 22.50% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 70 | | totalSentences | 80 | | matches | | 0 | "The damp cold of the" | | 1 | "She stood on the edge" | | 2 | "He gestured toward the center" | | 3 | "Harlow didn't answer right away." | | 4 | "She checked the worn leather" | | 5 | "She raised her eyes, her" | | 6 | "she said, her voice dry" | | 7 | "Harlow said, nodding toward the" | | 8 | "A tiny fragment of carved" | | 9 | "Miller scoffed, though he shifted" | | 10 | "Harlow walked slowly along the" | | 11 | "She wasn't listening to Miller's" | | 12 | "The space didn't look like" | | 13 | "It looked like a bazaar." | | 14 | "Dozens of folding tables and" | | 15 | "The lingering smell wasn't cheap" | | 16 | "It was sulfur, dried lotus," | | 17 | "She stopped beside a overturned" | | 18 | "A small, brass object had" | | 19 | "Harlow knelt, pulling a pair" |
| | ratio | 0.875 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 80 | | matches | (empty) | | ratio | 0 | |
| 89.29% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 40 | | technicalSentenceCount | 3 | | matches | | 0 | "Standing in this forgotten station, holding a instrument that seemed to pulse against her thumb, she felt the same icy certainty settle in her stomach." | | 1 | "Next to it was an impression in the dirt—the distinct rectangular outline of a heavy bag that had been dropped in haste and picked back up." | | 2 | "Curly red hair caught the glow, framed by round glasses that kept sliding down a freckled nose." |
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| 66.18% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 17 | | uselessAdditionCount | 2 | | matches | | 0 | "she said, her voice dry and low" | | 1 | "Harlow said, her voice dropping into a dangerous, quiet register" |
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| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 14 | | fancyCount | 5 | | fancyTags | | 0 | "Miller grumbled (grumble)" | | 1 | "she insisted (insist)" | | 2 | "Harlow called out (call out)" | | 3 | "Miller yelled (yell)" | | 4 | "Eva whispered (whisper)" |
| | dialogueSentences | 32 | | tagDensity | 0.438 | | leniency | 0.875 | | rawRatio | 0.357 | | effectiveRatio | 0.313 | |