| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 1 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 1 | | tagDensity | 1 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 610 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 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) | |
| 1.64% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 610 | | totalAiIsms | 12 | | found | | | highlights | | 0 | "weight" | | 1 | "familiar" | | 2 | "flicker" | | 3 | "echo" | | 4 | "footsteps" | | 5 | "rhythmic" | | 6 | "pulse" | | 7 | "velvet" | | 8 | "shimmered" | | 9 | "glistening" | | 10 | "tracing" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "air was thick with" | | count | 1 |
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| | highlights | | 0 | "the air was thick with" |
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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 | 0 | | hedgeCount | 0 | | narrationSentences | 81 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 81 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 34 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 4 | | markdownWords | 6 | | totalWords | 600 | | ratio | 0.01 | | matches | | 0 | "The Raven’s Nest." | | 1 | "thump" | | 2 | "market" | | 3 | "memories" |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 2 | | unquotedAttributions | 0 | | matches | (empty) | |
| 82.66% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 11 | | wordCount | 594 | | uniqueNames | 3 | | maxNameDensity | 1.35 | | worstName | "Quinn" | | maxWindowNameDensity | 2 | | worstWindowName | "Quinn" | | discoveredNames | | | persons | | | places | | | globalScore | 0.827 | | windowScore | 1 | |
| 0.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 42 | | glossingSentenceCount | 3 | | matches | | 0 | "looked like it had been recently cut" | | 1 | "appeared behind him, his face pale in the dim light" | | 2 | "looked like he’d seen a ghost" |
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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 | 600 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 81 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 24 | | mean | 25 | | std | 22.36 | | cv | 0.894 | | sampleLengths | | 0 | 88 | | 1 | 21 | | 2 | 74 | | 3 | 28 | | 4 | 39 | | 5 | 16 | | 6 | 2 | | 7 | 43 | | 8 | 21 | | 9 | 5 | | 10 | 17 | | 11 | 63 | | 12 | 40 | | 13 | 21 | | 14 | 5 | | 15 | 31 | | 16 | 10 | | 17 | 19 | | 18 | 7 | | 19 | 19 | | 20 | 12 | | 21 | 11 | | 22 | 4 | | 23 | 4 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 81 | | matches | (empty) | |
| 0.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 5 | | totalVerbs | 96 | | matches | | 0 | "was watching" | | 1 | "was walking" | | 2 | "wasn’t leaving" | | 3 | "wasn’t selling" | | 4 | "was selling" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 7 | | semicolonCount | 0 | | flaggedSentences | 6 | | totalSentences | 81 | | ratio | 0.074 | | matches | | 0 | "The suspect—some low-level dealer with a habit of slipping through the cracks—had bolted into the shadows near the old Tube station entrance, his coat flapping like a flag in the wind." | | 1 | "The air grew thick with the scent of damp stone and something older—something metallic, like old blood left to rust." | | 2 | "Or worse—he’d found a way out she didn’t know about." | | 3 | "Then she saw it—a door, half-hidden behind a tangle of wires." | | 4 | "Inside, the air was thick with the scent of herbs and something sharper—alcohol, maybe, or something stronger." | | 5 | "But he was watching something—a table laden with bones." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 604 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 17 | | adverbRatio | 0.028145695364238412 | | lyAdverbCount | 3 | | lyAdverbRatio | 0.004966887417218543 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 81 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 81 | | mean | 7.41 | | std | 5.72 | | cv | 0.772 | | sampleLengths | | 0 | 21 | | 1 | 3 | | 2 | 2 | | 3 | 31 | | 4 | 14 | | 5 | 7 | | 6 | 10 | | 7 | 4 | | 8 | 12 | | 9 | 3 | | 10 | 2 | | 11 | 20 | | 12 | 9 | | 13 | 16 | | 14 | 6 | | 15 | 12 | | 16 | 11 | | 17 | 5 | | 18 | 5 | | 19 | 8 | | 20 | 10 | | 21 | 8 | | 22 | 12 | | 23 | 9 | | 24 | 10 | | 25 | 2 | | 26 | 2 | | 27 | 2 | | 28 | 4 | | 29 | 3 | | 30 | 3 | | 31 | 2 | | 32 | 11 | | 33 | 11 | | 34 | 11 | | 35 | 10 | | 36 | 3 | | 37 | 7 | | 38 | 4 | | 39 | 2 | | 40 | 5 | | 41 | 4 | | 42 | 1 | | 43 | 9 | | 44 | 8 | | 45 | 17 | | 46 | 2 | | 47 | 3 | | 48 | 2 | | 49 | 23 |
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| 51.03% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 7 | | diversityRatio | 0.35802469135802467 | | totalSentences | 81 | | uniqueOpeners | 29 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 5 | | totalSentences | 66 | | matches | | 0 | "Just the echo of his" | | 1 | "Somewhere beyond the next bend," | | 2 | "Then she saw it—a door," | | 3 | "Just her and the dark." | | 4 | "Just kept his eyes on" |
| | ratio | 0.076 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 15 | | totalSentences | 66 | | matches | | 0 | "She didn’t slow." | | 1 | "She’d carried it through enough" | | 2 | "Her boots splashed through puddles" | | 3 | "She reached for her radio," | | 4 | "She stepped forward, her boot" | | 5 | "He wasn’t the suspect." | | 6 | "She didn’t know what she" | | 7 | "She wasn’t leaving without answers." | | 8 | "He didn’t sound scared." | | 9 | "She didn’t answer." | | 10 | "She didn’t have to." | | 11 | "He looked like he’d seen" | | 12 | "His eyes locked onto Quinn’s." | | 13 | "He wasn’t selling bones." | | 14 | "He was selling *memories*." |
| | ratio | 0.227 | |
| 96.36% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 48 | | totalSentences | 66 | | matches | | 0 | "The rain hammered against the" | | 1 | "She didn’t slow." | | 2 | "The suspect—some low-level dealer with" | | 3 | "Quinn’s breath came sharp, her" | | 4 | "The gun was cold, the" | | 5 | "She’d carried it through enough" | | 6 | "A flicker of movement." | | 7 | "A flash of dark fabric" | | 8 | "Quinn didn’t think." | | 9 | "The air grew thick with" | | 10 | "The tunnel sloped downward, the" | | 11 | "Her boots splashed through puddles" | | 12 | "*The Raven’s Nest.* She recognised" | | 13 | "A dive bar, but not" | | 14 | "The kind that served things" | | 15 | "The suspect was already gone." | | 16 | "Quinn pressed her back against" | | 17 | "The tunnel stretched ahead, a" | | 18 | "A low, rhythmic *thump*." | | 19 | "This one was old, its" |
| | ratio | 0.727 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 66 | | matches | (empty) | | ratio | 0 | |
| 85.71% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 25 | | technicalSentenceCount | 2 | | matches | | 0 | "The suspect—some low-level dealer with a habit of slipping through the cracks—had bolted into the shadows near the old Tube station entrance, his coat flapping …" | | 1 | "Her boots splashed through puddles that glowed faintly under the flickering neon of a distant sign." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 1 | | uselessAdditionCount | 1 | | matches | | 0 | "the man said, his voice low, smooth" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 1 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 1 | | tagDensity | 1 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |