| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 2 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 9 | | tagDensity | 0.222 | | leniency | 0.444 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 94.97% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 994 | | 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) | |
| 69.82% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 994 | | totalAiIsms | 6 | | found | | | highlights | | 0 | "scanned" | | 1 | "glinting" | | 2 | "pulse" | | 3 | "stomach" | | 4 | "unreadable" | | 5 | "flickered" |
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| 66.67% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 2 | | maxInWindow | 2 | | found | | 0 | | label | "blood ran cold" | | count | 1 |
| | 1 | | label | "hung in the air" | | count | 1 |
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| | highlights | | 0 | "blood ran cold" | | 1 | "hung heavy in the air" |
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| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 2 | | narrationSentences | 86 | | matches | | 0 | "t in determination" | | 1 | "t with anger" |
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| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 86 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 93 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 28 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 2 | | markdownWords | 4 | | totalWords | 985 | | ratio | 0.004 | | matches | | 0 | "The Raven’s Nest" | | 1 | "click" |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 5 | | unquotedAttributions | 0 | | matches | (empty) | |
| 74.41% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 39 | | wordCount | 926 | | uniqueNames | 12 | | maxNameDensity | 1.51 | | worstName | "Quinn" | | maxWindowNameDensity | 2 | | worstWindowName | "Quinn" | | discoveredNames | | London | 1 | | Harlow | 1 | | Quinn | 14 | | Soho | 1 | | Raven | 1 | | Tomás | 1 | | Herrera | 13 | | Saint | 1 | | Christopher | 1 | | Tube | 1 | | Veil | 2 | | Market | 2 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Tomás" | | 3 | "Herrera" | | 4 | "Saint" | | 5 | "Christopher" |
| | places | | | globalScore | 0.744 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 62 | | glossingSentenceCount | 1 | | matches | | 0 | "looked like a floating, disembodied eye" |
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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 | 985 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 93 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 34 | | mean | 28.97 | | std | 23.21 | | cv | 0.801 | | sampleLengths | | 0 | 80 | | 1 | 34 | | 2 | 78 | | 3 | 11 | | 4 | 45 | | 5 | 55 | | 6 | 11 | | 7 | 38 | | 8 | 48 | | 9 | 17 | | 10 | 7 | | 11 | 63 | | 12 | 88 | | 13 | 19 | | 14 | 46 | | 15 | 20 | | 16 | 34 | | 17 | 12 | | 18 | 10 | | 19 | 15 | | 20 | 32 | | 21 | 34 | | 22 | 10 | | 23 | 56 | | 24 | 30 | | 25 | 12 | | 26 | 23 | | 27 | 4 | | 28 | 3 | | 29 | 15 | | 30 | 10 | | 31 | 15 | | 32 | 3 | | 33 | 7 |
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| 88.94% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 4 | | totalSentences | 86 | | matches | | 0 | "were plastered" | | 1 | "was swallowed" | | 2 | "were bought" | | 3 | "were lined" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 160 | | matches | | 0 | "was winning" | | 1 | "was heading" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 8 | | semicolonCount | 0 | | flaggedSentences | 6 | | totalSentences | 93 | | ratio | 0.065 | | matches | | 0 | "She’d been tailing the suspect for blocks—ever since he’d bolted from *The Raven’s Nest* like a man with something to hide." | | 1 | "The suspect—Tomás Herrera, if her sources were right—was fast, but she was faster." | | 2 | "Herrera hesitated for half a second—just long enough for Quinn to close the distance." | | 3 | "The scent of incense and something metallic—blood?—hung heavy in the air." | | 4 | "A man in a long coat displayed rows of teeth—human, animal, something in between." | | 5 | "The vendor, a gaunt man with hollow cheeks, handed him something small and white—a bone token." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 935 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 27 | | adverbRatio | 0.028877005347593583 | | lyAdverbCount | 1 | | lyAdverbRatio | 0.0010695187165775401 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 93 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 93 | | mean | 10.59 | | std | 6.53 | | cv | 0.616 | | sampleLengths | | 0 | 15 | | 1 | 23 | | 2 | 18 | | 3 | 24 | | 4 | 21 | | 5 | 13 | | 6 | 13 | | 7 | 10 | | 8 | 6 | | 9 | 20 | | 10 | 14 | | 11 | 15 | | 12 | 4 | | 13 | 3 | | 14 | 4 | | 15 | 13 | | 16 | 10 | | 17 | 14 | | 18 | 8 | | 19 | 18 | | 20 | 14 | | 21 | 23 | | 22 | 11 | | 23 | 3 | | 24 | 22 | | 25 | 3 | | 26 | 5 | | 27 | 5 | | 28 | 4 | | 29 | 23 | | 30 | 7 | | 31 | 14 | | 32 | 5 | | 33 | 5 | | 34 | 1 | | 35 | 1 | | 36 | 5 | | 37 | 7 | | 38 | 11 | | 39 | 28 | | 40 | 13 | | 41 | 11 | | 42 | 16 | | 43 | 13 | | 44 | 16 | | 45 | 11 | | 46 | 14 | | 47 | 18 | | 48 | 3 | | 49 | 13 |
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| 40.32% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 9 | | diversityRatio | 0.2903225806451613 | | totalSentences | 93 | | uniqueOpeners | 27 | |
| 79.37% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 84 | | matches | | 0 | "Then, with a sigh, he" | | 1 | "Then Herrera spoke, his voice" |
| | ratio | 0.024 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 25 | | totalSentences | 84 | | matches | | 0 | "Her breath came in controlled" | | 1 | "She’d been tailing the suspect" | | 2 | "He had youth on his" | | 3 | "She could see the Saint" | | 4 | "His dark curls were plastered" | | 5 | "He glanced back, his warm" | | 6 | "She just ran harder." | | 7 | "She could hear his ragged" | | 8 | "He wasn’t used to being" | | 9 | "She lunged, her fingers brushing" | | 10 | "she barked, but the word" | | 11 | "He bolted again, this time" | | 12 | "She knew the rumors." | | 13 | "She’d seen a lot in" | | 14 | "She spotted Herrera again, weaving" | | 15 | "He turned and slipped behind" | | 16 | "She didn’t have a token." | | 17 | "She shouldered her way through" | | 18 | "he said, his voice like" | | 19 | "She just held out her" |
| | ratio | 0.298 | |
| 49.29% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 69 | | totalSentences | 84 | | matches | | 0 | "The rain came down in" | | 1 | "Detective Harlow Quinn moved with" | | 2 | "The neon glow of Soho’s" | | 3 | "Her breath came in controlled" | | 4 | "She’d been tailing the suspect" | | 5 | "The suspect—Tomás Herrera, if her" | | 6 | "He had youth on his" | | 7 | "She could see the Saint" | | 8 | "His dark curls were plastered" | | 9 | "He glanced back, his warm" | | 10 | "Quinn didn’t call out." | | 11 | "She just ran harder." | | 12 | "Herrera cut down a side" | | 13 | "Quinn followed, her own steps" | | 14 | "She could hear his ragged" | | 15 | "He wasn’t used to being" | | 16 | "The alley opened into a" | | 17 | "Herrera hesitated for half a" | | 18 | "She lunged, her fingers brushing" | | 19 | "she barked, but the word" |
| | ratio | 0.821 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 84 | | matches | (empty) | | ratio | 0 | |
| 47.62% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 45 | | technicalSentenceCount | 6 | | matches | | 0 | "Detective Harlow Quinn moved with the precision of a soldier, her boots splashing through puddles that pooled in the cracks of the pavement." | | 1 | "She lunged, her fingers brushing the fabric of his jacket before he twisted away, his scarred forearm flashing as he shoved her back." | | 2 | "Knew the stories about the underground black market that moved with the full moon, where things were bought and sold that shouldn’t exist." | | 3 | "The sound of the rain faded behind her, replaced by the low hum of voices, the clink of glass, the occasional laugh that sounded too sharp, too knowing." | | 4 | "The market was a labyrinth of stalls, each one selling things that made her skin prickle." | | 5 | "The man smirked, revealing teeth that were just a little too sharp." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 2 | | uselessAdditionCount | 1 | | matches | | 0 | "she barked, but the word was swallowed by the storm" |
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| 38.89% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 2 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 9 | | tagDensity | 0.222 | | leniency | 0.444 | | rawRatio | 0.5 | | effectiveRatio | 0.222 | |