| 18.18% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 4 | | adverbTagCount | 1 | | adverbTags | | 0 | "She hesitated then [then]" |
| | dialogueSentences | 11 | | tagDensity | 0.364 | | leniency | 0.727 | | rawRatio | 0.25 | | effectiveRatio | 0.182 | |
| 86.15% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 361 | | 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) | |
| 30.75% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 361 | | totalAiIsms | 5 | | found | | | highlights | | 0 | "stomach" | | 1 | "silence" | | 2 | "pulse" | | 3 | "vibrated" | | 4 | "flickered" |
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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 | 36 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 36 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 43 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 23 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 4 | | markdownWords | 12 | | totalWords | 358 | | ratio | 0.034 | | matches | | 0 | "the thing he’d been obsessed with" | | 1 | "absorbed" | | 2 | "moved" | | 3 | "“You shouldn’t have come.”" |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 5 | | unquotedAttributions | 0 | | matches | (empty) | |
| 53.54% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 18 | | wordCount | 311 | | uniqueNames | 8 | | maxNameDensity | 1.93 | | worstName | "Quinn" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Quinn" | | discoveredNames | | Tube | 1 | | Harlow | 1 | | Quinn | 6 | | Morris | 2 | | Veil | 1 | | Compass | 1 | | Kowalski | 1 | | Eva | 5 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Morris" | | 3 | "Kowalski" | | 4 | "Eva" |
| | places | (empty) | | globalScore | 0.535 | | windowScore | 0.833 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 21 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 358 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 43 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 14 | | mean | 25.57 | | std | 18 | | cv | 0.704 | | sampleLengths | | 0 | 61 | | 1 | 52 | | 2 | 52 | | 3 | 29 | | 4 | 9 | | 5 | 41 | | 6 | 13 | | 7 | 18 | | 8 | 25 | | 9 | 22 | | 10 | 10 | | 11 | 11 | | 12 | 11 | | 13 | 4 |
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| 95.52% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 36 | | matches | | |
| 74.21% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 53 | | matches | | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 4 | | semicolonCount | 0 | | flaggedSentences | 3 | | totalSentences | 43 | | ratio | 0.07 | | matches | | 0 | "The Tube station smelled of damp stone and something older—something that clung to the air like a second skin." | | 1 | "The way his fingers curled around the Veil Compass—*the thing he’d been obsessed with*—made her stomach twist." | | 2 | "Then, from the darkness, a voice—soft, but clear as a blade." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 314 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 10 | | adverbRatio | 0.03184713375796178 | | lyAdverbCount | 2 | | lyAdverbRatio | 0.006369426751592357 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 43 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 43 | | mean | 8.33 | | std | 5.95 | | cv | 0.715 | | sampleLengths | | 0 | 19 | | 1 | 19 | | 2 | 23 | | 3 | 13 | | 4 | 2 | | 5 | 5 | | 6 | 2 | | 7 | 17 | | 8 | 7 | | 9 | 6 | | 10 | 22 | | 11 | 11 | | 12 | 19 | | 13 | 7 | | 14 | 17 | | 15 | 5 | | 16 | 3 | | 17 | 6 | | 18 | 3 | | 19 | 15 | | 20 | 15 | | 21 | 5 | | 22 | 3 | | 23 | 7 | | 24 | 6 | | 25 | 3 | | 26 | 12 | | 27 | 3 | | 28 | 11 | | 29 | 7 | | 30 | 3 | | 31 | 4 | | 32 | 3 | | 33 | 8 | | 34 | 4 | | 35 | 7 | | 36 | 6 | | 37 | 4 | | 38 | 3 | | 39 | 4 | | 40 | 4 | | 41 | 11 | | 42 | 4 |
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| 66.67% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 3 | | diversityRatio | 0.4418604651162791 | | totalSentences | 43 | | uniqueOpeners | 19 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 34 | | matches | | 0 | "Then, from the shadows above," | | 1 | "Then, from the darkness, a" |
| | ratio | 0.059 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 7 | | totalSentences | 34 | | matches | | 0 | "She crouched beside the body," | | 1 | "His chest was still warm." | | 2 | "She stood beside her satchel," | | 3 | "She tucked her curly red" | | 4 | "She hesitated, then pressed a" | | 5 | "She knelt, brushing aside a" | | 6 | "She stood, her gaze locked" |
| | ratio | 0.206 | |
| 48.24% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 28 | | totalSentences | 34 | | matches | | 0 | "The Tube station smelled of" | | 1 | "Detective Harlow Quinn stepped through" | | 2 | "The place had been a" | | 3 | "She crouched beside the body," | | 4 | "His chest was still warm." | | 5 | "The way his fingers curled" | | 6 | "Eva Kowalski’s voice cut through" | | 7 | "She stood beside her satchel," | | 8 | "She tucked her curly red" | | 9 | "Quinn said, her voice low," | | 10 | "She hesitated, then pressed a" | | 11 | "Eva exhaled sharply." | | 12 | "Quinn didn’t answer." | | 13 | "She knelt, brushing aside a" | | 14 | "The brass compass lay half-buried" | | 15 | "Eva muttered, her voice tight" | | 16 | "Quinn’s watch ticked." | | 17 | "The leather strap was worn" | | 18 | "A distant hum vibrated through" | | 19 | "The air thickened, pressing against" |
| | ratio | 0.824 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 34 | | matches | (empty) | | ratio | 0 | |
| 83.33% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 12 | | technicalSentenceCount | 1 | | matches | | 0 | "The Tube station smelled of damp stone and something older—something that clung to the air like a second skin." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 4 | | uselessAdditionCount | 2 | | matches | | 0 | "Quinn said, her voice low, precise" | | 1 | "Eva muttered, her voice tight" |
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| 59.09% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 2 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 11 | | tagDensity | 0.182 | | leniency | 0.364 | | rawRatio | 0.5 | | effectiveRatio | 0.182 | |