| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 2 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 12 | | tagDensity | 0.167 | | leniency | 0.333 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 90.18% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 509 | | 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) | |
| 21.41% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 509 | | totalAiIsms | 8 | | found | | | highlights | | 0 | "footsteps" | | 1 | "echoed" | | 2 | "glinting" | | 3 | "charged" | | 4 | "could feel" | | 5 | "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 | 38 | | matches | (empty) | |
| 30.08% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 2 | | narrationSentences | 38 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 47 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 27 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 507 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 2 | | unquotedAttributions | 0 | | matches | (empty) | |
| 80.39% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 21 | | wordCount | 431 | | uniqueNames | 13 | | maxNameDensity | 1.39 | | worstName | "Quinn" | | maxWindowNameDensity | 2 | | worstWindowName | "Quinn" | | discoveredNames | | Soho | 1 | | Harlow | 1 | | Quinn | 6 | | Raven | 1 | | Nest | 1 | | Tube | 1 | | Veil | 1 | | Market | 1 | | Saint | 1 | | Christopher | 1 | | Herrera | 1 | | Spanish | 1 | | Tomás | 4 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Raven" | | 3 | "Market" | | 4 | "Saint" | | 5 | "Christopher" | | 6 | "Herrera" | | 7 | "Tomás" |
| | places | | | globalScore | 0.804 | | windowScore | 1 | |
| 57.41% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 27 | | glossingSentenceCount | 1 | | matches | | 0 | "something like charred bone" |
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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 | 507 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 47 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 22 | | mean | 23.05 | | std | 18.42 | | cv | 0.799 | | sampleLengths | | 0 | 55 | | 1 | 16 | | 2 | 52 | | 3 | 48 | | 4 | 60 | | 5 | 52 | | 6 | 5 | | 7 | 8 | | 8 | 29 | | 9 | 2 | | 10 | 12 | | 11 | 20 | | 12 | 30 | | 13 | 17 | | 14 | 18 | | 15 | 29 | | 16 | 8 | | 17 | 3 | | 18 | 19 | | 19 | 16 | | 20 | 3 | | 21 | 5 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 38 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 75 | | matches | | |
| 21.28% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 2 | | semicolonCount | 0 | | flaggedSentences | 2 | | totalSentences | 47 | | ratio | 0.043 | | matches | | 0 | "Quinn didn’t hesitate—she grabbed the railing and swung herself over, landing with military precision on the slick steps below." | | 1 | "Beyond it, flickering lanterns cast long shadows across an underground cavern—an abandoned Tube station, its tiled walls cracked and stained." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 433 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 7 | | adverbRatio | 0.016166281755196306 | | lyAdverbCount | 2 | | lyAdverbRatio | 0.004618937644341801 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 47 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 47 | | mean | 10.79 | | std | 6.82 | | cv | 0.632 | | sampleLengths | | 0 | 15 | | 1 | 27 | | 2 | 13 | | 3 | 16 | | 4 | 18 | | 5 | 15 | | 6 | 19 | | 7 | 11 | | 8 | 21 | | 9 | 16 | | 10 | 8 | | 11 | 20 | | 12 | 18 | | 13 | 11 | | 14 | 3 | | 15 | 11 | | 16 | 16 | | 17 | 25 | | 18 | 5 | | 19 | 8 | | 20 | 2 | | 21 | 20 | | 22 | 7 | | 23 | 2 | | 24 | 5 | | 25 | 7 | | 26 | 3 | | 27 | 17 | | 28 | 6 | | 29 | 9 | | 30 | 15 | | 31 | 11 | | 32 | 6 | | 33 | 7 | | 34 | 11 | | 35 | 3 | | 36 | 21 | | 37 | 5 | | 38 | 3 | | 39 | 5 | | 40 | 2 | | 41 | 1 | | 42 | 19 | | 43 | 9 | | 44 | 7 | | 45 | 3 | | 46 | 5 |
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| 73.76% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 2 | | diversityRatio | 0.46808510638297873 | | totalSentences | 47 | | uniqueOpeners | 22 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 35 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 9 | | totalSentences | 35 | | matches | | 0 | "Her voice cut through the" | | 1 | "She pushed harder, her breath" | | 2 | "She’d heard whispers of this" | | 3 | "His warm brown eyes held" | | 4 | "She glanced back at the" | | 5 | "She could feel the weight" | | 6 | "She exhaled sharply." | | 7 | "She didn’t wait for an" | | 8 | "He cursed under his breath" |
| | ratio | 0.257 | |
| 2.86% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 32 | | totalSentences | 35 | | matches | | 0 | "The rain came down in" | | 1 | "Detective Harlow Quinn sprinted after" | | 2 | "The suspect darted around a" | | 3 | "Her voice cut through the" | | 4 | "She pushed harder, her breath" | | 5 | "The suspect vaulted over a" | | 6 | "Quinn didn’t hesitate—she grabbed the" | | 7 | "The stairwell stank of damp" | | 8 | "The suspect’s footsteps echoed ahead," | | 9 | "The air grew thick, heavy" | | 10 | "Stalls lined the platform, their" | | 11 | "The Veil Market." | | 12 | "Quinn slowed, her hand drifting" | | 13 | "She’d heard whispers of this" | | 14 | "The suspect was already weaving" | | 15 | "A hand caught her elbow." | | 16 | "A man stood beside her," | | 17 | "His warm brown eyes held" | | 18 | "Quinn yanked her arm free." | | 19 | "Tomás didn’t flinch." |
| | ratio | 0.914 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 35 | | matches | (empty) | | ratio | 0 | |
| 67.67% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 19 | | technicalSentenceCount | 2 | | matches | | 0 | "Detective Harlow Quinn sprinted after the figure in the dark hoodie, her boots splashing through puddles that reflected the neon glow of the Raven’s Nest sign o…" | | 1 | "The suspect was already weaving through the crowd, his hood slipping just enough to reveal a flash of olive skin, a scar along his forearm." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 2 | | uselessAdditionCount | 1 | | matches | | 0 | "Tomás stepped, his voice low" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |