| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 15 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 39 | | tagDensity | 0.385 | | leniency | 0.769 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 91.06% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1118 | | 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) | |
| 55.28% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1118 | | totalAiIsms | 10 | | found | | | highlights | | 0 | "sentinels" | | 1 | "chaotic" | | 2 | "scanned" | | 3 | "predator" | | 4 | "etched" | | 5 | "weight" | | 6 | "perfect" | | 7 | "flickered" | | 8 | "dancing" | | 9 | "chill" |
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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 | 3 | | narrationSentences | 100 | | matches | | 0 | "e with anxiety" | | 1 | "felt a chill" | | 2 | "t with fear" |
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| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 100 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 122 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 30 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 1 | | markdownWords | 1 | | totalWords | 1115 | | ratio | 0.001 | | matches | | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 9 | | unquotedAttributions | 0 | | matches | (empty) | |
| 32.42% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 50 | | wordCount | 893 | | uniqueNames | 10 | | maxNameDensity | 2.35 | | worstName | "Quinn" | | maxWindowNameDensity | 4 | | worstWindowName | "Eva" | | discoveredNames | | Quinn | 21 | | Metropolitan | 1 | | Transit | 1 | | Victorian | 1 | | Veil | 1 | | Market | 1 | | Camden | 1 | | Pendelton | 2 | | Eva | 15 | | Arthur | 6 |
| | persons | | 0 | "Quinn" | | 1 | "Market" | | 2 | "Pendelton" | | 3 | "Eva" | | 4 | "Arthur" |
| | places | (empty) | | globalScore | 0.324 | | windowScore | 0.333 | |
| 39.71% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 68 | | glossingSentenceCount | 3 | | matches | | 0 | "looked like it had been branded by a torc" | | 1 | "looked like the wood had been drilled int" | | 2 | "looked like a reflection, distorted by he" |
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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 | 1115 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 122 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 44 | | mean | 25.34 | | std | 16.34 | | cv | 0.645 | | sampleLengths | | 0 | 61 | | 1 | 84 | | 2 | 23 | | 3 | 26 | | 4 | 9 | | 5 | 24 | | 6 | 38 | | 7 | 18 | | 8 | 23 | | 9 | 35 | | 10 | 12 | | 11 | 42 | | 12 | 4 | | 13 | 38 | | 14 | 6 | | 15 | 29 | | 16 | 3 | | 17 | 34 | | 18 | 33 | | 19 | 28 | | 20 | 39 | | 21 | 13 | | 22 | 26 | | 23 | 22 | | 24 | 37 | | 25 | 5 | | 26 | 20 | | 27 | 29 | | 28 | 45 | | 29 | 7 | | 30 | 25 | | 31 | 2 | | 32 | 49 | | 33 | 2 | | 34 | 24 | | 35 | 11 | | 36 | 25 | | 37 | 42 | | 38 | 15 | | 39 | 29 | | 40 | 10 | | 41 | 28 | | 42 | 12 | | 43 | 28 |
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| 91.23% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 4 | | totalSentences | 100 | | matches | | 0 | "was cauterized" | | 1 | "been branded" | | 2 | "was etched" | | 3 | "been drilled" |
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| 0.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 8 | | totalVerbs | 159 | | matches | | 0 | "wasn't pointing" | | 1 | "was vibrating" | | 2 | "weren't following" | | 3 | "were pulsing" | | 4 | "were gripping" | | 5 | "was intensifying" | | 6 | "were vibrating" | | 7 | "was spinning" |
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| 96.02% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 2 | | flaggedSentences | 2 | | totalSentences | 122 | | ratio | 0.016 | | matches | | 0 | "She didn't pull her close; she planted her feet, anchoring the scientist in place." | | 1 | "The needle was no longer moving; it had locked in place, locked on Quinn." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 895 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 30 | | adverbRatio | 0.0335195530726257 | | lyAdverbCount | 10 | | lyAdverbRatio | 0.0111731843575419 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 122 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 122 | | mean | 9.14 | | std | 5.75 | | cv | 0.629 | | sampleLengths | | 0 | 5 | | 1 | 22 | | 2 | 4 | | 3 | 17 | | 4 | 13 | | 5 | 7 | | 6 | 18 | | 7 | 20 | | 8 | 15 | | 9 | 4 | | 10 | 3 | | 11 | 3 | | 12 | 14 | | 13 | 13 | | 14 | 10 | | 15 | 9 | | 16 | 8 | | 17 | 9 | | 18 | 9 | | 19 | 17 | | 20 | 7 | | 21 | 15 | | 22 | 15 | | 23 | 2 | | 24 | 3 | | 25 | 3 | | 26 | 12 | | 27 | 6 | | 28 | 23 | | 29 | 3 | | 30 | 5 | | 31 | 9 | | 32 | 18 | | 33 | 8 | | 34 | 4 | | 35 | 6 | | 36 | 16 | | 37 | 12 | | 38 | 8 | | 39 | 4 | | 40 | 27 | | 41 | 11 | | 42 | 6 | | 43 | 15 | | 44 | 5 | | 45 | 5 | | 46 | 4 | | 47 | 3 | | 48 | 8 | | 49 | 12 |
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| 43.44% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 8 | | diversityRatio | 0.2786885245901639 | | totalSentences | 122 | | uniqueOpeners | 34 | |
| 70.92% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 94 | | matches | | 0 | "Just a crowd of shadowy" | | 1 | "Just Pendelton’s own shoes." |
| | ratio | 0.021 | |
| 83.83% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 32 | | totalSentences | 94 | | matches | | 0 | "It just materialized, a chaotic" | | 1 | "Her jaw was set, the" | | 2 | "She scanned the perimeter." | | 3 | "She walked toward the back" | | 4 | "They parted instantly, sensing the" | | 5 | "He was a fence, a" | | 6 | "It was art." | | 7 | "It glowed, a faint, sickly" | | 8 | "She crouched, inspecting the wound." | | 9 | "It looked like it had" | | 10 | "Her curly red hair framed" | | 11 | "She pushed her round glasses" | | 12 | "It was vibrating, twitching erratically." | | 13 | "They had arrived without weight." | | 14 | "She placed a hand on" | | 15 | "It was cold, unnaturally so." | | 16 | "She tapped the compass against" | | 17 | "It formed a perfect circle" | | 18 | "It wasn't wet." | | 19 | "It looked like the wood" |
| | ratio | 0.34 | |
| 13.19% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 84 | | totalSentences | 94 | | matches | | 0 | "Harlow Quinn checked her watch." | | 1 | "The leather strap was tight" | | 2 | "The Metropolitan Transit service had" | | 3 | "A gate hung open, forcing" | | 4 | "The Veil Market didn't announce" | | 5 | "It just materialized, a chaotic" | | 6 | "Quinn pressed her palms against" | | 7 | "Her jaw was set, the" | | 8 | "She scanned the perimeter." | | 9 | "She walked toward the back" | | 10 | "The floor here was slick" | | 11 | "Quinn pushed through, her boots" | | 12 | "They parted instantly, sensing the" | | 13 | "Quinn commanded, her voice low" | | 14 | "A man with a tattoo" | | 15 | "Quinn stepped up to the" | | 16 | "Arthur Pendelton lay flat on" | | 17 | "He was a fence, a" | | 18 | "this wasn't inventory." | | 19 | "It was art." |
| | ratio | 0.894 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 94 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 32 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 15 | | uselessAdditionCount | 6 | | matches | | 0 | "Quinn commanded, her voice low and gravelly" | | 1 | "Eva said, her voice rising a fraction" | | 2 | "Eva stepped, her hand hovering over the compass" | | 3 | "Eva said, her voice trembling" | | 4 | "Eva grabbed, her fingers digging in hard" | | 5 | "Quinn said, her voice low and commanding" |
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| 98.72% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 7 | | fancyCount | 2 | | fancyTags | | 0 | "Eva whispered (whisper)" | | 1 | "Eva whispered (whisper)" |
| | dialogueSentences | 39 | | tagDensity | 0.179 | | leniency | 0.359 | | rawRatio | 0.286 | | effectiveRatio | 0.103 | |