| 9.52% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 18 | | adverbTagCount | 4 | | adverbTags | | 0 | "She gestured vaguely [vaguely]" | | 1 | "Quinn repeated flatly [flatly]" | | 2 | "Quinn turned back [back]" | | 3 | "Quinn asked abruptly [abruptly]" |
| | dialogueSentences | 42 | | tagDensity | 0.429 | | leniency | 0.857 | | rawRatio | 0.222 | | effectiveRatio | 0.19 | |
| 96.67% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1502 | | totalAiIsmAdverbs | 1 | | 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) | |
| 46.74% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1502 | | totalAiIsms | 16 | | found | | | highlights | | 0 | "shattered" | | 1 | "shimmered" | | 2 | "determined" | | 3 | "etched" | | 4 | "intricate" | | 5 | "raced" | | 6 | "familiar" | | 7 | "resolving" | | 8 | "chill" | | 9 | "pulse" | | 10 | "gloom" | | 11 | "unwavering" | | 12 | "whisper" | | 13 | "weight" |
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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 | 97 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 1 | | narrationSentences | 97 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 120 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 59 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 1 | | markdownWords | 2 | | totalWords | 1498 | | ratio | 0.001 | | matches | | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 6 | | unquotedAttributions | 0 | | matches | (empty) | |
| 47.96% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 48 | | wordCount | 931 | | uniqueNames | 10 | | maxNameDensity | 2.04 | | worstName | "Quinn" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Quinn" | | discoveredNames | | Camden | 1 | | Tube | 1 | | Harlow | 1 | | Quinn | 19 | | Veil | 1 | | Market | 1 | | Kowalski | 1 | | Aurora | 3 | | Morris | 3 | | Eva | 17 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Market" | | 3 | "Kowalski" | | 4 | "Aurora" | | 5 | "Morris" | | 6 | "Eva" |
| | places | (empty) | | globalScore | 0.48 | | windowScore | 0.5 | |
| 30.95% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 63 | | glossingSentenceCount | 3 | | matches | | 0 | "as if clutching something that was no longer there" | | 1 | "as if acting it out" | | 2 | "felt like a performance" |
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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 | 1498 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 120 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 37 | | mean | 40.49 | | std | 23.72 | | cv | 0.586 | | sampleLengths | | 0 | 69 | | 1 | 71 | | 2 | 45 | | 3 | 1 | | 4 | 38 | | 5 | 10 | | 6 | 58 | | 7 | 62 | | 8 | 14 | | 9 | 24 | | 10 | 56 | | 11 | 44 | | 12 | 27 | | 13 | 54 | | 14 | 12 | | 15 | 32 | | 16 | 62 | | 17 | 38 | | 18 | 11 | | 19 | 12 | | 20 | 40 | | 21 | 72 | | 22 | 28 | | 23 | 50 | | 24 | 11 | | 25 | 79 | | 26 | 24 | | 27 | 17 | | 28 | 63 | | 29 | 61 | | 30 | 18 | | 31 | 100 | | 32 | 22 | | 33 | 36 | | 34 | 16 | | 35 | 58 | | 36 | 63 |
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| 87.18% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 5 | | totalSentences | 97 | | matches | | 0 | "was gone" | | 1 | "was stained" | | 2 | "was determined" | | 3 | "was etched" | | 4 | "was staged" |
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| 0.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 5 | | totalVerbs | 164 | | matches | | 0 | "was studying" | | 1 | "was looking" | | 2 | "was staring" | | 3 | "was pointing" | | 4 | "was leading" |
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| 71.43% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 4 | | semicolonCount | 0 | | flaggedSentences | 3 | | totalSentences | 120 | | ratio | 0.025 | | matches | | 0 | "The air in the abandoned Camden Tube station tasted of rust, damp earth, and something else—ozone, maybe, or the sharp tang of a spent firework." | | 1 | "The scattered stall, the dropped token—all theater." | | 2 | "A body left in the one place certain people—people like Eva, like Aurora—would know to look." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 938 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 22 | | adverbRatio | 0.023454157782515993 | | lyAdverbCount | 9 | | lyAdverbRatio | 0.009594882729211088 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 120 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 120 | | mean | 12.48 | | std | 9.33 | | cv | 0.747 | | sampleLengths | | 0 | 25 | | 1 | 20 | | 2 | 5 | | 3 | 14 | | 4 | 5 | | 5 | 3 | | 6 | 5 | | 7 | 10 | | 8 | 16 | | 9 | 13 | | 10 | 18 | | 11 | 6 | | 12 | 16 | | 13 | 7 | | 14 | 3 | | 15 | 19 | | 16 | 1 | | 17 | 6 | | 18 | 21 | | 19 | 11 | | 20 | 10 | | 21 | 13 | | 22 | 12 | | 23 | 9 | | 24 | 24 | | 25 | 5 | | 26 | 5 | | 27 | 9 | | 28 | 26 | | 29 | 17 | | 30 | 4 | | 31 | 10 | | 32 | 12 | | 33 | 12 | | 34 | 17 | | 35 | 9 | | 36 | 27 | | 37 | 3 | | 38 | 12 | | 39 | 8 | | 40 | 24 | | 41 | 8 | | 42 | 19 | | 43 | 10 | | 44 | 13 | | 45 | 31 | | 46 | 6 | | 47 | 4 | | 48 | 2 | | 49 | 12 |
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| 49.17% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 6 | | diversityRatio | 0.325 | | totalSentences | 120 | | uniqueOpeners | 39 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 92 | | matches | (empty) | | ratio | 0 | |
| 93.91% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 29 | | totalSentences | 92 | | matches | | 0 | "Her sharp jaw was set." | | 1 | "They hadn’t mentioned the market." | | 2 | "It had left a corpse" | | 3 | "He wore expensive but now-torn" | | 4 | "She didn’t turn at the" | | 5 | "She was studying the placement" | | 6 | "She hugged her worn leather" | | 7 | "Her freckled complexion looked pale" | | 8 | "She gestured vaguely at the" | | 9 | "Her worn leather watch strap" | | 10 | "She pointed at the green" | | 11 | "She didn’t get too close" | | 12 | "She was looking past the" | | 13 | "She stood, her knees popping." | | 14 | "She walked a slow circuit" | | 15 | "She moved to it, careful" | | 16 | "It was a compass." | | 17 | "She didn’t touch it." | | 18 | "She hurried over." | | 19 | "She looked from the compass" |
| | ratio | 0.315 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 85 | | totalSentences | 92 | | matches | | 0 | "The air in the abandoned" | | 1 | "Detective Harlow Quinn stood at" | | 2 | "Her sharp jaw was set." | | 3 | "The call had been cryptic:" | | 4 | "They hadn’t mentioned the market." | | 5 | "The scattered remnants were telltale." | | 6 | "A stall’s canvas awning lay" | | 7 | "A single, carved bone token," | | 8 | "The Veil Market had been" | | 9 | "It had left a corpse" | | 10 | "The body was a man," | | 11 | "He wore expensive but now-torn" | | 12 | "She didn’t turn at the" | | 13 | "She was studying the placement" | | 14 | "The skin around the nails" | | 15 | "Eva Kowalski stepped into the" | | 16 | "She hugged her worn leather" | | 17 | "Her freckled complexion looked pale" | | 18 | "She gestured vaguely at the" | | 19 | "Quinn finally glanced at her." |
| | ratio | 0.924 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 92 | | matches | (empty) | | ratio | 0 | |
| 67.67% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 38 | | technicalSentenceCount | 4 | | matches | | 0 | "Shattered glass vials leaked iridescent fluids that pooled and shimmered under the beam of her torch." | | 1 | "She was studying the placement of the victim’s left hand, fingers curled as if clutching something that was no longer there." | | 2 | "Aurora and her little clique were a puzzle she was determined to solve, a lead that felt connected to the hollow, unexplained ache of Morris’s death." | | 3 | "She looked at Eva, who was staring at the body with dawning horror, likely reaching the same conclusion." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 18 | | uselessAdditionCount | 6 | | matches | | 0 | "Eva said, but her voice lacked conviction" | | 1 | "Quinn said, her tone cool" | | 2 | "Quinn said, her voice low" | | 3 | "She looked, its etched face seeming to pulse in the gloom" | | 4 | "Eva finished, her voice barely a whisper" | | 5 | "Quinn said, not asking" |
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| 78.57% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 8 | | fancyCount | 3 | | fancyTags | | 0 | "Quinn repeated flatly (repeat)" | | 1 | "Quinn probed (probe)" | | 2 | "Eva murmured (murmur)" |
| | dialogueSentences | 42 | | tagDensity | 0.19 | | leniency | 0.381 | | rawRatio | 0.375 | | effectiveRatio | 0.143 | |