| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 29 | | adverbTagCount | 1 | | adverbTags | | 0 | "Eva edged backward [backward]" |
| | dialogueSentences | 63 | | tagDensity | 0.46 | | leniency | 0.921 | | rawRatio | 0.034 | | effectiveRatio | 0.032 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1487 | | 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) | |
| 56.29% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1487 | | totalAiIsms | 13 | | found | | | highlights | | 0 | "shattered" | | 1 | "velvet" | | 2 | "standard" | | 3 | "measured" | | 4 | "fascinating" | | 5 | "looming" | | 6 | "rhythmic" | | 7 | "etched" | | 8 | "vibrated" | | 9 | "echoed" | | 10 | "fractured" | | 11 | "trembled" |
| |
| 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 | 114 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 114 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 148 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 28 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1478 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 8 | | unquotedAttributions | 0 | | matches | (empty) | |
| 20.32% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 61 | | wordCount | 1041 | | uniqueNames | 12 | | maxNameDensity | 2.59 | | worstName | "Quinn" | | maxWindowNameDensity | 4 | | worstWindowName | "Quinn" | | discoveredNames | | Detective | 1 | | Harlow | 1 | | Quinn | 27 | | Camden | 1 | | Tube | 1 | | Sergeant | 1 | | Miller | 13 | | Veil | 1 | | Market | 1 | | Two | 1 | | Eva | 12 | | Morris | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Sergeant" | | 3 | "Miller" | | 4 | "Market" | | 5 | "Eva" | | 6 | "Morris" |
| | places | | | globalScore | 0.203 | | windowScore | 0.333 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 91 | | glossingSentenceCount | 1 | | matches | | 0 | "felt like touching a glacier" |
| |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1478 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 148 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 60 | | mean | 24.63 | | std | 16.54 | | cv | 0.672 | | sampleLengths | | 0 | 15 | | 1 | 40 | | 2 | 32 | | 3 | 31 | | 4 | 29 | | 5 | 13 | | 6 | 39 | | 7 | 8 | | 8 | 29 | | 9 | 4 | | 10 | 35 | | 11 | 17 | | 12 | 9 | | 13 | 61 | | 14 | 14 | | 15 | 40 | | 16 | 86 | | 17 | 23 | | 18 | 2 | | 19 | 43 | | 20 | 35 | | 21 | 1 | | 22 | 2 | | 23 | 32 | | 24 | 48 | | 25 | 22 | | 26 | 18 | | 27 | 27 | | 28 | 18 | | 29 | 13 | | 30 | 43 | | 31 | 47 | | 32 | 17 | | 33 | 31 | | 34 | 5 | | 35 | 22 | | 36 | 20 | | 37 | 22 | | 38 | 4 | | 39 | 12 | | 40 | 43 | | 41 | 41 | | 42 | 57 | | 43 | 3 | | 44 | 6 | | 45 | 23 | | 46 | 17 | | 47 | 30 | | 48 | 40 | | 49 | 9 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 114 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 173 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 148 | | ratio | 0 | | matches | (empty) | |
| 82.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1048 | | adjectiveStacks | 3 | | stackExamples | | 0 | "lay open beside it." | | 1 | "beautiful small old round" | | 2 | "massive, shadow-slicked claw" |
| | adverbCount | 19 | | adverbRatio | 0.01812977099236641 | | lyAdverbCount | 7 | | lyAdverbRatio | 0.006679389312977099 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 148 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 148 | | mean | 9.99 | | std | 5.43 | | cv | 0.544 | | sampleLengths | | 0 | 15 | | 1 | 12 | | 2 | 28 | | 3 | 17 | | 4 | 15 | | 5 | 7 | | 6 | 13 | | 7 | 4 | | 8 | 7 | | 9 | 17 | | 10 | 12 | | 11 | 11 | | 12 | 2 | | 13 | 21 | | 14 | 18 | | 15 | 8 | | 16 | 16 | | 17 | 13 | | 18 | 4 | | 19 | 3 | | 20 | 7 | | 21 | 18 | | 22 | 7 | | 23 | 9 | | 24 | 8 | | 25 | 9 | | 26 | 6 | | 27 | 11 | | 28 | 6 | | 29 | 9 | | 30 | 15 | | 31 | 7 | | 32 | 7 | | 33 | 8 | | 34 | 6 | | 35 | 13 | | 36 | 8 | | 37 | 5 | | 38 | 14 | | 39 | 11 | | 40 | 8 | | 41 | 1 | | 42 | 1 | | 43 | 8 | | 44 | 21 | | 45 | 3 | | 46 | 7 | | 47 | 9 | | 48 | 5 | | 49 | 12 |
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| 76.35% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 7 | | diversityRatio | 0.4864864864864865 | | totalSentences | 148 | | uniqueOpeners | 72 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 106 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 16 | | totalSentences | 106 | | matches | | 0 | "She tapped the glass of" | | 1 | "She stepped around a shattered" | | 2 | "She knelt by a dark" | | 3 | "It lacked the sharp metallic" | | 4 | "She used her pen to" | | 5 | "She knew the informant whispers" | | 6 | "They had set up shop" | | 7 | "She pushed round wire-rimmed glasses" | | 8 | "Her green eyes lingered on" | | 9 | "She stepped into Eva's personal" | | 10 | "She reached inside the bag" | | 11 | "She bypassed him, pressing her" | | 12 | "It felt like touching a" | | 13 | "Her voice sounded thin and" | | 14 | "Her satchel swung and hit" | | 15 | "His torch trembled as the" |
| | ratio | 0.151 | |
| 16.60% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 94 | | totalSentences | 106 | | matches | | 0 | "Glass crunched beneath Detective Harlow" | | 1 | "The abandoned Camden Tube station" | | 2 | "Uniforms swarmed the narrow subterranean" | | 3 | "Miller pointed his heavy black" | | 4 | "Quinn stepped over a splintered" | | 5 | "She tapped the glass of" | | 6 | "Quinn pointed her steel torch" | | 7 | "Quinn knelt and measured the" | | 8 | "Quinn stood and walked toward" | | 9 | "A rookie constable reached out" | | 10 | "The rookie froze." | | 11 | "Quinn pointed her pen at" | | 12 | "The silver droplets defied gravity," | | 13 | "The rookie swallowed hard and" | | 14 | "Miller stated, standing a safe" | | 15 | "Quinn walked further down the" | | 16 | "She stepped around a shattered" | | 17 | "The glass crunched under her" | | 18 | "A strange mish-mash of banned" | | 19 | "Miller yelled to a rookie" |
| | ratio | 0.887 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 106 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 40 | | technicalSentenceCount | 1 | | matches | | 0 | "Dried nightshade, powdered silver, and chunks of heavy grey stone that resembled crushed gargoyle horn." |
| |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 29 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 23.02% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 8 | | fancyCount | 8 | | fancyTags | | 0 | "Miller grumbled (grumble)" | | 1 | "Quinn barked (bark)" | | 2 | "Miller stated (state)" | | 3 | "Miller yelled (yell)" | | 4 | "Miller announced (announce)" | | 5 | "Miller laughed (laugh)" | | 6 | "Miller interrupted (interrupt)" | | 7 | "Quinn ordered (order)" |
| | dialogueSentences | 63 | | tagDensity | 0.127 | | leniency | 0.254 | | rawRatio | 1 | | effectiveRatio | 0.254 | |