| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 9 | | adverbTagCount | 1 | | adverbTags | | 0 | "Ruiz said again [again]" |
| | dialogueSentences | 25 | | tagDensity | 0.36 | | leniency | 0.72 | | rawRatio | 0.111 | | effectiveRatio | 0.08 | |
| 73.68% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1140 | | totalAiIsmAdverbs | 6 | | found | | | highlights | | 0 | "slightly" | | 1 | "nervously" | | 2 | "lazily" | | 3 | "perfectly" | | 4 | "suddenly" | | 5 | "very" |
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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) | |
| 60.53% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1140 | | totalAiIsms | 9 | | found | | | highlights | | 0 | "echoing" | | 1 | "velvet" | | 2 | "pristine" | | 3 | "crystal" | | 4 | "measured" | | 5 | "etched" | | 6 | "intricate" | | 7 | "standard" | | 8 | "weight" |
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| 66.67% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 2 | | maxInWindow | 2 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 1 |
| | 1 | | label | "clenched jaw/fists" | | count | 1 |
|
| | highlights | | 0 | "eyes narrowed" | | 1 | "clenched fist" |
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| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 81 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 81 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 95 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 53 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1138 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 11 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 35 | | wordCount | 857 | | uniqueNames | 11 | | maxNameDensity | 0.93 | | worstName | "Quinn" | | maxWindowNameDensity | 2 | | worstWindowName | "Quinn" | | discoveredNames | | Camden | 1 | | Tube | 1 | | Harlow | 1 | | Quinn | 8 | | Veil | 2 | | Market | 2 | | Ruiz | 8 | | Kowalski | 1 | | Eva | 6 | | Finn | 3 | | Shade | 2 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Market" | | 3 | "Ruiz" | | 4 | "Kowalski" | | 5 | "Eva" | | 6 | "Finn" | | 7 | "Shade" |
| | places | (empty) | | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 65 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.879 | | wordCount | 1138 | | matches | | 0 | "not a weapon or a token, but a single, dark grey feather, about four inches long" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 95 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 30 | | mean | 37.93 | | std | 26.3 | | cv | 0.693 | | sampleLengths | | 0 | 95 | | 1 | 3 | | 2 | 56 | | 3 | 60 | | 4 | 40 | | 5 | 42 | | 6 | 6 | | 7 | 14 | | 8 | 39 | | 9 | 9 | | 10 | 78 | | 11 | 14 | | 12 | 9 | | 13 | 55 | | 14 | 4 | | 15 | 38 | | 16 | 21 | | 17 | 47 | | 18 | 28 | | 19 | 19 | | 20 | 70 | | 21 | 31 | | 22 | 5 | | 23 | 57 | | 24 | 22 | | 25 | 89 | | 26 | 58 | | 27 | 44 | | 28 | 12 | | 29 | 73 |
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| 87.94% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 4 | | totalSentences | 81 | | matches | | 0 | "been deserted" | | 1 | "was clenched" | | 2 | "was etched" | | 3 | "been pulled" |
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| 62.07% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 3 | | totalVerbs | 145 | | matches | | 0 | "wasn’t looking" | | 1 | "was looking" | | 2 | "were rearranging" |
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| 22.56% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 2 | | semicolonCount | 2 | | flaggedSentences | 4 | | totalSentences | 95 | | ratio | 0.042 | | matches | | 0 | "He found the usual—wallet with mundane ID, a mobile phone with a wiped memory, a keyring with no keys." | | 1 | "The compass hadn’t been pointing to a rift; it had been tracking the supernatural energy signature of the feather itself, the very thing that killed him." | | 2 | "The client, the safe passage, the expensive suit—it was all misdirection." | | 3 | "The market wasn’t the scene of the crime; it was the drop point." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 864 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 32 | | adverbRatio | 0.037037037037037035 | | lyAdverbCount | 9 | | lyAdverbRatio | 0.010416666666666666 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 95 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 95 | | mean | 11.98 | | std | 8.08 | | cv | 0.674 | | sampleLengths | | 0 | 15 | | 1 | 33 | | 2 | 1 | | 3 | 8 | | 4 | 26 | | 5 | 12 | | 6 | 3 | | 7 | 14 | | 8 | 13 | | 9 | 16 | | 10 | 7 | | 11 | 6 | | 12 | 31 | | 13 | 12 | | 14 | 2 | | 15 | 15 | | 16 | 8 | | 17 | 32 | | 18 | 9 | | 19 | 5 | | 20 | 11 | | 21 | 5 | | 22 | 11 | | 23 | 1 | | 24 | 6 | | 25 | 14 | | 26 | 5 | | 27 | 10 | | 28 | 24 | | 29 | 2 | | 30 | 7 | | 31 | 18 | | 32 | 16 | | 33 | 24 | | 34 | 2 | | 35 | 8 | | 36 | 10 | | 37 | 6 | | 38 | 8 | | 39 | 9 | | 40 | 8 | | 41 | 7 | | 42 | 21 | | 43 | 19 | | 44 | 4 | | 45 | 27 | | 46 | 11 | | 47 | 3 | | 48 | 12 | | 49 | 6 |
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| 69.15% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 5 | | diversityRatio | 0.44680851063829785 | | totalSentences | 94 | | uniqueOpeners | 42 | |
| 88.89% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 75 | | matches | | 0 | "Instead, a dozen figures in" | | 1 | "Then, in the waistcoat’s inner" |
| | ratio | 0.027 | |
| 65.33% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 29 | | totalSentences | 75 | | matches | | 0 | "He stood by a stall" | | 1 | "He was looking at the" | | 2 | "She didn’t touch the body." | | 3 | "Her gaze swept from the" | | 4 | "His right hand was clenched" | | 5 | "she asked, her voice low" | | 6 | "She pointed with a penlight" | | 7 | "She shifted her attention to" | | 8 | "Her round glasses reflected the" | | 9 | "Her worn leather satchel was" | | 10 | "She walked toward Eva, her" | | 11 | "She pushed her glasses up" | | 12 | "Her eyes darted to the" | | 13 | "She turned back to the" | | 14 | "He found the usual—wallet with" | | 15 | "He pulled it out and" | | 16 | "Its face was etched with" | | 17 | "She held it still, felt" | | 18 | "She moved back to the" | | 19 | "It took effort to pry" |
| | ratio | 0.387 | |
| 26.67% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 65 | | totalSentences | 75 | | matches | | 0 | "The air in the abandoned" | | 1 | "Detective Harlow Quinn stood at" | | 2 | "The Market should have been" | | 3 | "The usual hum of enchanted" | | 4 | "Officer Ruiz’s voice came from" | | 5 | "He stood by a stall" | | 6 | "The stall held a collection" | | 7 | "He was looking at the" | | 8 | "The victim lay half-propped against" | | 9 | "A single, clean wound marred" | | 10 | "The edges of the fabric" | | 11 | "Ruiz said, flipping open his" | | 12 | "Quinn crouched, her knees protesting" | | 13 | "She didn’t touch the body." | | 14 | "Her gaze swept from the" | | 15 | "His right hand was clenched" | | 16 | "she asked, her voice low" | | 17 | "Quinn’s eyes narrowed" | | 18 | "She pointed with a penlight" | | 19 | "She shifted her attention to" |
| | ratio | 0.867 | |
| 66.67% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 75 | | matches | | | ratio | 0.013 | |
| 83.33% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 36 | | technicalSentenceCount | 3 | | matches | | 0 | "The victim lay half-propped against the stall’s support beam, a man in his late thirties, impeccably dressed in a tailored three-piece suit that had no business…" | | 1 | "The pieces were rearranging themselves in her mind, forming a new, sharper picture." | | 2 | "The compass hadn’t been pointing to a rift; it had been tracking the supernatural energy signature of the feather itself, the very thing that killed him." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 9 | | uselessAdditionCount | 3 | | matches | | 0 | "she asked, her voice low" | | 1 | "Ruiz said, dismissive" | | 2 | "Quinn said, her voice flat" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 6 | | fancyCount | 1 | | fancyTags | | 0 | "Quinn murmured (murmur)" |
| | dialogueSentences | 25 | | tagDensity | 0.24 | | leniency | 0.48 | | rawRatio | 0.167 | | effectiveRatio | 0.08 | |