| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 2 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 11 | | tagDensity | 0.182 | | leniency | 0.364 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 782 | | 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) | |
| 36.06% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 782 | | totalAiIsms | 10 | | found | | | highlights | | 0 | "footsteps" | | 1 | "echoing" | | 2 | "eyebrow" | | 3 | "raced" | | 4 | "perfect" | | 5 | "clandestine" | | 6 | "glint" | | 7 | "etched" | | 8 | "flicker" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 54 | | matches | (empty) | |
| 63.49% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 3 | | narrationSentences | 54 | | filterMatches | (empty) | | hedgeMatches | | 0 | "tried to" | | 1 | "manage to" | | 2 | "began to" |
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| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 63 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 31 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 787 | | ratio | 0 | | matches | (empty) | |
| 75.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 5 | | unquotedAttributions | 1 | | matches | | 0 | "As if reading her thoughts, Perkins spoke up." |
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| 62.42% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 39 | | wordCount | 628 | | uniqueNames | 13 | | maxNameDensity | 1.75 | | worstName | "Quinn" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Quinn" | | discoveredNames | | Harlow | 1 | | Quinn | 11 | | Tube | 1 | | Perkins | 5 | | Eva | 7 | | Kowalski | 2 | | Veil | 2 | | Market | 1 | | Compass | 1 | | Shade | 1 | | Aurora | 5 | | British | 1 | | Museum | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Perkins" | | 3 | "Eva" | | 4 | "Kowalski" | | 5 | "Compass" | | 6 | "Museum" |
| | places | | | globalScore | 0.624 | | windowScore | 0.833 | |
| 93.18% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 44 | | glossingSentenceCount | 1 | | matches | | 0 | "As if reading her thoughts, Perkins spoke up" |
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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 | 787 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 63 | | matches | (empty) | |
| 76.10% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 26 | | mean | 30.27 | | std | 12.6 | | cv | 0.416 | | sampleLengths | | 0 | 63 | | 1 | 34 | | 2 | 20 | | 3 | 37 | | 4 | 49 | | 5 | 7 | | 6 | 40 | | 7 | 30 | | 8 | 44 | | 9 | 33 | | 10 | 30 | | 11 | 18 | | 12 | 25 | | 13 | 47 | | 14 | 36 | | 15 | 34 | | 16 | 23 | | 17 | 7 | | 18 | 33 | | 19 | 32 | | 20 | 25 | | 21 | 11 | | 22 | 19 | | 23 | 37 | | 24 | 27 | | 25 | 26 |
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| 98.77% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 54 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 111 | | matches | | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 4 | | semicolonCount | 1 | | flaggedSentences | 5 | | totalSentences | 63 | | ratio | 0.079 | | matches | | 0 | "She glanced around, taking in the scene with a critical eye - the peeling paint on the walls, the debris scattered across the platform, the eerie stillness that hung thick as fog." | | 1 | "This was no accident; it was murder." | | 2 | "The Veil Market - an underground supernatural black market that moved locations every full moon." | | 3 | "A Veil Compass - crafted by a Shade artisan to point towards the nearest supernatural rift or portal." | | 4 | "It was time to pay a visit to the British Museum's restricted archives - and see if Aurora could shed some light on this mystery." |
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| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 625 | | adjectiveStacks | 1 | | stackExamples | | 0 | "underground supernatural black market" |
| | adverbCount | 17 | | adverbRatio | 0.0272 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.008 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 63 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 63 | | mean | 12.49 | | std | 7.03 | | cv | 0.562 | | sampleLengths | | 0 | 16 | | 1 | 15 | | 2 | 32 | | 3 | 13 | | 4 | 21 | | 5 | 4 | | 6 | 16 | | 7 | 22 | | 8 | 15 | | 9 | 15 | | 10 | 18 | | 11 | 16 | | 12 | 2 | | 13 | 5 | | 14 | 12 | | 15 | 28 | | 16 | 10 | | 17 | 13 | | 18 | 7 | | 19 | 11 | | 20 | 9 | | 21 | 6 | | 22 | 18 | | 23 | 8 | | 24 | 25 | | 25 | 3 | | 26 | 15 | | 27 | 9 | | 28 | 3 | | 29 | 4 | | 30 | 14 | | 31 | 25 | | 32 | 14 | | 33 | 15 | | 34 | 18 | | 35 | 9 | | 36 | 12 | | 37 | 8 | | 38 | 7 | | 39 | 12 | | 40 | 22 | | 41 | 22 | | 42 | 1 | | 43 | 7 | | 44 | 5 | | 45 | 19 | | 46 | 9 | | 47 | 7 | | 48 | 25 | | 49 | 13 |
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| 82.01% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 0 | | diversityRatio | 0.49206349206349204 | | totalSentences | 63 | | uniqueOpeners | 31 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 52 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 12 | | totalSentences | 52 | | matches | | 0 | "She glanced around, taking in" | | 1 | "Her colleague, a young constable" | | 2 | "Her mind raced as she" | | 3 | "It was the perfect place" | | 4 | "She turned to Perkins." | | 5 | "Her heart raced as she" | | 6 | "She'd been hunting for something" | | 7 | "She needed to find out" | | 8 | "She stood up, dusting off" | | 9 | "It was time to pay" | | 10 | "It was Aurora, alive and" | | 11 | "she said, her voice steady" |
| | ratio | 0.231 | |
| 100.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 33 | | totalSentences | 52 | | matches | | 0 | "Detective Harlow Quinn strode into" | | 1 | "The place reeked of mold" | | 2 | "She glanced around, taking in" | | 3 | "Her colleague, a young constable" | | 4 | "Quinn arched an eyebrow." | | 5 | "Perkins led her to the" | | 6 | "Quinn knelt beside the body," | | 7 | "The victim's curly red hair" | | 8 | "A worn leather satchel full" | | 9 | "Perkins said, scratching his head" | | 10 | "Quinn stood, her gaze drifting" | | 11 | "The lip of the platform" | | 12 | "This was no accident; it" | | 13 | "Her mind raced as she" | | 14 | "Quinn's eyes narrowed." | | 15 | "The Veil Market - an" | | 16 | "It was the perfect place" | | 17 | "She turned to Perkins." | | 18 | "A Veil Compass - crafted" | | 19 | "Her heart raced as she" |
| | ratio | 0.635 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 52 | | matches | | 0 | "As if reading her thoughts," | | 1 | "If Aurora was involved in" |
| | ratio | 0.038 | |
| 91.84% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 28 | | technicalSentenceCount | 2 | | matches | | 0 | "She glanced around, taking in the scene with a critical eye - the peeling paint on the walls, the debris scattered across the platform, the eerie stillness that…" | | 1 | "The Veil Market - an underground supernatural black market that moved locations every full moon." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 2 | | uselessAdditionCount | 1 | | matches | | 0 | "she said, her voice steady despite the fear in her eyes" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 2 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 11 | | tagDensity | 0.182 | | leniency | 0.364 | | rawRatio | 0 | | effectiveRatio | 0 | |