| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 15 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 35 | | tagDensity | 0.429 | | leniency | 0.857 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 91.48% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1174 | | totalAiIsmAdverbs | 2 | | found | | | highlights | | |
| 80.00% | AI-ism character names | Target: 0 AI-default names (17 tracked, −20% each) | | codexExemptions | (empty) | | found | | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 78.71% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1174 | | totalAiIsms | 5 | | found | | | highlights | | 0 | "tracing" | | 1 | "glinting" | | 2 | "standard" | | 3 | "footsteps" | | 4 | "echo" |
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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 | 115 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 0 | | narrationSentences | 115 | | filterMatches | | | hedgeMatches | (empty) | |
| 98.34% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 135 | | gibberishSentences | 1 | | adjustedGibberishSentences | 1 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 42 | | ratio | 0.007 | | matches | | 0 | "Harlow Quinn tucks it into her coat, fingers brushing the leather of her watch—纹路 worn thin from 18 years of tracing the second hand." |
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| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 15 | | markdownWords | 18 | | totalWords | 1165 | | ratio | 0.015 | | matches | | 0 | "have" | | 1 | "here" | | 2 | "cratered" | | 3 | "love" | | 4 | "earn" | | 5 | "removal" | | 6 | "unexplainable" | | 7 | "fake" | | 8 | "Elixir of the Unseen" | | 9 | "real" | | 10 | "waiting" | | 11 | "back" | | 12 | "explodes" | | 13 | "hunger" | | 14 | "Now" |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 15 | | unquotedAttributions | 1 | | matches | | |
| 51.84% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 49 | | wordCount | 815 | | uniqueNames | 14 | | maxNameDensity | 1.96 | | worstName | "Quinn" | | maxWindowNameDensity | 3 | | worstWindowName | "Quinn" | | discoveredNames | | Compass | 6 | | Quinn | 16 | | Tube | 1 | | Market | 2 | | Veil | 2 | | Camden | 1 | | Occult | 1 | | Emporium | 1 | | Highbury | 1 | | Carter | 12 | | Latin | 1 | | Marcus | 1 | | Hale | 2 | | Morris | 2 |
| | persons | | 0 | "Compass" | | 1 | "Quinn" | | 2 | "Market" | | 3 | "Emporium" | | 4 | "Carter" | | 5 | "Marcus" | | 6 | "Hale" | | 7 | "Morris" |
| | places | | 0 | "Camden" | | 1 | "Highbury" | | 2 | "Latin" |
| | globalScore | 0.518 | | windowScore | 0.667 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 60 | | 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 | 1165 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 2 | | totalSentences | 135 | | matches | | 0 | "joke that he’d" | | 1 | "knows that smile" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 47 | | mean | 24.79 | | std | 23.83 | | cv | 0.961 | | sampleLengths | | 0 | 84 | | 1 | 2 | | 2 | 56 | | 3 | 12 | | 4 | 63 | | 5 | 70 | | 6 | 19 | | 7 | 35 | | 8 | 17 | | 9 | 49 | | 10 | 19 | | 11 | 37 | | 12 | 42 | | 13 | 40 | | 14 | 12 | | 15 | 39 | | 16 | 75 | | 17 | 4 | | 18 | 90 | | 19 | 9 | | 20 | 52 | | 21 | 9 | | 22 | 32 | | 23 | 1 | | 24 | 18 | | 25 | 5 | | 26 | 42 | | 27 | 5 | | 28 | 43 | | 29 | 25 | | 30 | 18 | | 31 | 7 | | 32 | 32 | | 33 | 6 | | 34 | 9 | | 35 | 6 | | 36 | 5 | | 37 | 4 | | 38 | 36 | | 39 | 8 | | 40 | 4 | | 41 | 3 | | 42 | 6 | | 43 | 6 | | 44 | 3 | | 45 | 5 | | 46 | 1 |
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| 93.06% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 4 | | totalSentences | 115 | | matches | | 0 | "been burned" | | 1 | "was snapped" | | 2 | "was torn" | | 3 | "are pressed" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 161 | | matches | (empty) | |
| 79.37% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 3 | | semicolonCount | 0 | | flaggedSentences | 3 | | totalSentences | 135 | | ratio | 0.022 | | matches | | 0 | "Harlow Quinn tucks it into her coat, fingers brushing the leather of her watch—纹路 worn thin from 18 years of tracing the second hand." | | 1 | "The token is a wolf bone, yes—but the break at the base is clean, like it was snapped off with pliers." | | 2 | "Quinn’s been there before—staked out a warehouse where the clique moved stolen artifacts." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 823 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 20 | | adverbRatio | 0.024301336573511544 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.006075334143377886 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 135 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 135 | | mean | 8.63 | | std | 7.28 | | cv | 0.843 | | sampleLengths | | 0 | 14 | | 1 | 24 | | 2 | 17 | | 3 | 12 | | 4 | 2 | | 5 | 5 | | 6 | 10 | | 7 | 2 | | 8 | 14 | | 9 | 9 | | 10 | 11 | | 11 | 3 | | 12 | 17 | | 13 | 2 | | 14 | 7 | | 15 | 5 | | 16 | 4 | | 17 | 15 | | 18 | 12 | | 19 | 4 | | 20 | 3 | | 21 | 12 | | 22 | 13 | | 23 | 15 | | 24 | 13 | | 25 | 9 | | 26 | 25 | | 27 | 8 | | 28 | 3 | | 29 | 5 | | 30 | 11 | | 31 | 12 | | 32 | 12 | | 33 | 11 | | 34 | 4 | | 35 | 13 | | 36 | 14 | | 37 | 21 | | 38 | 4 | | 39 | 2 | | 40 | 8 | | 41 | 2 | | 42 | 17 | | 43 | 3 | | 44 | 13 | | 45 | 9 | | 46 | 7 | | 47 | 3 | | 48 | 2 | | 49 | 14 |
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| 53.58% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 11 | | diversityRatio | 0.37037037037037035 | | totalSentences | 135 | | uniqueOpeners | 50 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 98 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 29 | | totalSentences | 98 | | matches | | 0 | "She steps over a rusted" | | 1 | "It has what the living" | | 2 | "It glows, faintly blue, like" | | 3 | "Her jaw tightens." | | 4 | "She kneels, gloved hand hovering" | | 5 | "It’s not a knife." | | 6 | "It’s *cratered*, as if a" | | 7 | "He’s 10 years her junior," | | 8 | "he says, like that explains" | | 9 | "He pulls out his phone," | | 10 | "She taps the wound with" | | 11 | "She’s looking at the platform’s" | | 12 | "It’s a receipt from Camden’s" | | 13 | "she says, more to herself" | | 14 | "Her height is like she" | | 15 | "She steps toward the hole" | | 16 | "She pries it open with" | | 17 | "She stands, her watch ticking" | | 18 | "She pulls her gun, fingers" | | 19 | "He shows her the screen." |
| | ratio | 0.296 | |
| 21.22% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 86 | | totalSentences | 98 | | matches | | 0 | "The Compass vibrates in her" | | 1 | "Harlow Quinn tucks it into" | | 2 | "The air in the abandoned" | | 3 | "She steps over a rusted" | | 4 | "Veil Market doesn’t *have* gravel." | | 5 | "It has what the living" | | 6 | "The body is on the" | | 7 | "The tiles are cracked, but" | | 8 | "It glows, faintly blue, like" | | 9 | "Her jaw tightens." | | 10 | "She kneels, gloved hand hovering" | | 11 | "a voice calls from the" | | 12 | "Quinn doesn’t look up." | | 13 | "The body’s coat is unzipped," | | 14 | "It’s not a knife." | | 15 | "It’s *cratered*, as if a" | | 16 | "Carter rounds the platform, his" | | 17 | "He’s 10 years her junior," | | 18 | "he says, like that explains" | | 19 | "He pulls out his phone," |
| | ratio | 0.878 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 98 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 28 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 25.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 15 | | uselessAdditionCount | 3 | | matches | | 0 | "she says, more to herself" | | 1 | "Carter leans in, voice dropping" | | 2 | "she says, voice tight" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 7 | | fancyCount | 1 | | fancyTags | | 0 | "a voice calls (a voice call)" |
| | dialogueSentences | 35 | | tagDensity | 0.2 | | leniency | 0.4 | | rawRatio | 0.143 | | effectiveRatio | 0.057 | |