| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 5 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 13 | | tagDensity | 0.385 | | leniency | 0.769 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 89.73% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 487 | | 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) | |
| 79.47% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 487 | | totalAiIsms | 2 | | found | | | highlights | | |
| 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 | 49 | | matches | (empty) | |
| 55.39% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 2 | | narrationSentences | 49 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 58 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 25 | | ratio | 0 | | matches | (empty) | |
| 0.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 15 | | markdownWords | 61 | | totalWords | 481 | | ratio | 0.127 | | matches | | 0 | "\"You’re late.\"" | | 1 | "\"Whoever did this,\"" | | 2 | "\"didn’t just kill them. They left a mark.\"" | | 3 | "\"That’s not a tourist’s compass,\"" | | 4 | "\"That’s a Veil Compass.\"" | | 5 | "\"You’re not the first to find one here.\"" | | 6 | "\"Then why’s it pointing at me?\"" | | 7 | "\"They didn’t kill them here,\"" | | 8 | "\"They brought them in.\"" | | 9 | "\"Or they brought *you" | | 10 | "click" | | 11 | "\"Shit.\"" | | 12 | "\"You’re not leaving here.\"" | | 13 | "\"They’re still here,\"" | | 14 | "\"And they’re watching.\"" |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 3 | | unquotedAttributions | 0 | | matches | (empty) | |
| 6.12% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 21 | | wordCount | 417 | | uniqueNames | 5 | | maxNameDensity | 2.88 | | worstName | "Quinn" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Quinn" | | discoveredNames | | Veil | 2 | | Market | 2 | | Camden | 1 | | Quinn | 12 | | Davies | 4 |
| | persons | | 0 | "Market" | | 1 | "Camden" | | 2 | "Quinn" | | 3 | "Davies" |
| | places | | | globalScore | 0.061 | | windowScore | 0.5 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 24 | | 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 | 481 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 58 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 18 | | mean | 26.72 | | std | 21.04 | | cv | 0.787 | | sampleLengths | | 0 | 64 | | 1 | 33 | | 2 | 2 | | 3 | 35 | | 4 | 74 | | 5 | 13 | | 6 | 47 | | 7 | 11 | | 8 | 11 | | 9 | 6 | | 10 | 58 | | 11 | 13 | | 12 | 8 | | 13 | 29 | | 14 | 27 | | 15 | 12 | | 16 | 30 | | 17 | 8 |
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| 83.78% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 49 | | matches | | 0 | "been dragged" | | 1 | "were curled" | | 2 | "was patched" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 63 | | matches | (empty) | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 7 | | semicolonCount | 0 | | flaggedSentences | 6 | | totalSentences | 58 | | ratio | 0.103 | | matches | | 0 | "The air here wasn’t just damp—it was thick, like the breath of a patient who’d been holding it too long." | | 1 | "Then—" | | 2 | "The throat had been slit, but not cleanly—there were jagged tears, like something had been dragged through the flesh before the blade came down." | | 3 | "The sigils on the face were worn, but legible—protective runes, if Quinn remembered correctly." | | 4 | "Just a single, shallow bite mark on the wrist—fresh, like it had happened minutes ago." | | 5 | "Quinn’s watch—her worn leather one—stopped." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 333 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 13 | | adverbRatio | 0.03903903903903904 | | lyAdverbCount | 2 | | lyAdverbRatio | 0.006006006006006006 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 58 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 58 | | mean | 8.29 | | std | 6.34 | | cv | 0.764 | | sampleLengths | | 0 | 24 | | 1 | 20 | | 2 | 20 | | 3 | 8 | | 4 | 3 | | 5 | 21 | | 6 | 1 | | 7 | 2 | | 8 | 5 | | 9 | 23 | | 10 | 5 | | 11 | 2 | | 12 | 19 | | 13 | 24 | | 14 | 13 | | 15 | 13 | | 16 | 5 | | 17 | 13 | | 18 | 5 | | 19 | 10 | | 20 | 10 | | 21 | 14 | | 22 | 3 | | 23 | 1 | | 24 | 2 | | 25 | 2 | | 26 | 7 | | 27 | 4 | | 28 | 3 | | 29 | 8 | | 30 | 6 | | 31 | 14 | | 32 | 14 | | 33 | 9 | | 34 | 2 | | 35 | 4 | | 36 | 15 | | 37 | 9 | | 38 | 4 | | 39 | 3 | | 40 | 5 | | 41 | 8 | | 42 | 5 | | 43 | 4 | | 44 | 8 | | 45 | 2 | | 46 | 2 | | 47 | 15 | | 48 | 3 | | 49 | 9 |
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| 52.87% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 6 | | diversityRatio | 0.3793103448275862 | | totalSentences | 58 | | uniqueOpeners | 22 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 38 | | matches | | 0 | "Just a single, shallow bite" | | 1 | "Then, with a sickening *click*," | | 2 | "Slowly, the fingers curled around" |
| | ratio | 0.079 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 3 | | totalSentences | 38 | | matches | | 0 | "She knew the sound before" | | 1 | "She didn’t look at Quinn." | | 2 | "She reached for her radio," |
| | ratio | 0.079 | |
| 52.11% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 31 | | totalSentences | 38 | | matches | | 0 | "The Veil Market’s entrance yawned" | | 1 | "Detective Quinn adjusted her gloves," | | 2 | "The air here wasn’t just" | | 3 | "A shadow moved behind the" | | 4 | "Quinn didn’t turn." | | 5 | "She knew the sound before" | | 6 | "The voice was sharp, clinical." | | 7 | "DS Davies stood at the" | | 8 | "She didn’t look at Quinn." | | 9 | "A body lay sprawled across" | | 10 | "The throat had been slit," | | 11 | "Quinn’s fingers twitched toward her" | | 12 | "The victim’s eyes were open," | | 13 | "Quinn exhaled through her nose." | | 14 | "The victim’s fingers were curled" | | 15 | "The casing was patched, the" | | 16 | "The sigils on the face" | | 17 | "Davies didn’t flinch." | | 18 | "The station was empty now," | | 19 | "Quinn crouched beside the corpse," |
| | ratio | 0.816 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 38 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 16 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 5 | | uselessAdditionCount | 2 | | matches | | 0 | "Quinn said, voice low" | | 1 | "She reached, but her fingers brushed something cold against her palm" |
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| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 4 | | fancyCount | 2 | | fancyTags | | 0 | "she muttered (mutter)" | | 1 | "Quinn whispered (whisper)" |
| | dialogueSentences | 13 | | tagDensity | 0.308 | | leniency | 0.615 | | rawRatio | 0.5 | | effectiveRatio | 0.308 | |