| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 16 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 40 | | tagDensity | 0.4 | | leniency | 0.8 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 94.73% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 948 | | 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) | |
| 5.06% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 948 | | totalAiIsms | 18 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | word | "skipped a beat" | | count | 1 |
| | 10 | |
| | highlights | | 0 | "etched" | | 1 | "scanned" | | 2 | "raced" | | 3 | "racing" | | 4 | "determined" | | 5 | "glint" | | 6 | "intricate" | | 7 | "could feel" | | 8 | "familiar" | | 9 | "skipped a beat" | | 10 | "anticipation" |
| |
| 0.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 4 | | maxInWindow | 4 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 3 |
| | 1 | | label | "air was thick with" | | count | 1 |
|
| | highlights | | 0 | "eyes widened" | | 1 | "eyes narrowed" | | 2 | "The air was thick with" |
| |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 2 | | narrationSentences | 82 | | matches | | 0 | "looked shocked" | | 1 | "d with anticipation" |
| |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 82 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 107 | | 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 | 0 | | markdownWords | 0 | | totalWords | 945 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 17 | | unquotedAttributions | 0 | | matches | (empty) | |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 58 | | wordCount | 730 | | uniqueNames | 13 | | maxNameDensity | 3.15 | | worstName | "Harlow" | | maxWindowNameDensity | 4 | | worstWindowName | "Harlow" | | discoveredNames | | Detective | 1 | | Harlow | 23 | | Quinn | 1 | | Tube | 1 | | Camden | 2 | | Veil | 6 | | Market | 5 | | Davies | 13 | | Multiple | 1 | | Compass | 1 | | British | 1 | | Museum | 1 | | Morris | 2 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Market" | | 3 | "Davies" | | 4 | "Multiple" | | 5 | "Compass" | | 6 | "Museum" | | 7 | "Morris" |
| | places | | | globalScore | 0 | | windowScore | 0.333 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 57 | | 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 | 945 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 107 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 40 | | mean | 23.63 | | std | 14.12 | | cv | 0.598 | | sampleLengths | | 0 | 17 | | 1 | 53 | | 2 | 32 | | 3 | 17 | | 4 | 31 | | 5 | 24 | | 6 | 24 | | 7 | 60 | | 8 | 8 | | 9 | 18 | | 10 | 12 | | 11 | 36 | | 12 | 3 | | 13 | 37 | | 14 | 17 | | 15 | 4 | | 16 | 19 | | 17 | 19 | | 18 | 25 | | 19 | 23 | | 20 | 32 | | 21 | 26 | | 22 | 23 | | 23 | 26 | | 24 | 15 | | 25 | 59 | | 26 | 42 | | 27 | 32 | | 28 | 28 | | 29 | 7 | | 30 | 14 | | 31 | 6 | | 32 | 5 | | 33 | 10 | | 34 | 37 | | 35 | 14 | | 36 | 9 | | 37 | 13 | | 38 | 40 | | 39 | 28 |
| |
| 92.43% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 82 | | matches | | 0 | "was determined" | | 1 | "was determined" | | 2 | "was determined" |
| |
| 98.99% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 132 | | matches | | 0 | "was getting" | | 1 | "were falling" |
| |
| 62.75% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 3 | | semicolonCount | 0 | | flaggedSentences | 3 | | totalSentences | 107 | | ratio | 0.028 | | matches | | 0 | "The air was thick with the scent of copper and something else—something ancient and unsettling." | | 1 | "One book caught her eye—a tome on ancient history, marked with a British Museum's restricted archives stamp." | | 2 | "The symbols, the compass, the satchel full of books—it all pointed to something bigger." |
| |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 309 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 4 | | adverbRatio | 0.012944983818770227 | | lyAdverbCount | 3 | | lyAdverbRatio | 0.009708737864077669 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 107 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 107 | | mean | 8.83 | | std | 4.89 | | cv | 0.554 | | sampleLengths | | 0 | 13 | | 1 | 4 | | 2 | 15 | | 3 | 23 | | 4 | 15 | | 5 | 17 | | 6 | 13 | | 7 | 2 | | 8 | 11 | | 9 | 6 | | 10 | 12 | | 11 | 19 | | 12 | 6 | | 13 | 13 | | 14 | 2 | | 15 | 3 | | 16 | 16 | | 17 | 3 | | 18 | 5 | | 19 | 12 | | 20 | 12 | | 21 | 12 | | 22 | 13 | | 23 | 11 | | 24 | 8 | | 25 | 8 | | 26 | 10 | | 27 | 3 | | 28 | 9 | | 29 | 7 | | 30 | 14 | | 31 | 15 | | 32 | 2 | | 33 | 1 | | 34 | 8 | | 35 | 12 | | 36 | 17 | | 37 | 14 | | 38 | 3 | | 39 | 3 | | 40 | 1 | | 41 | 10 | | 42 | 9 | | 43 | 15 | | 44 | 4 | | 45 | 7 | | 46 | 14 | | 47 | 2 | | 48 | 2 | | 49 | 9 |
| |
| 66.98% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 5 | | diversityRatio | 0.42990654205607476 | | totalSentences | 107 | | uniqueOpeners | 46 | |
| 43.86% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 76 | | matches | | | ratio | 0.013 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 15 | | totalSentences | 76 | | matches | | 0 | "It was from an occult" | | 1 | "He pointed to the heavy" | | 2 | "Her eyes were wide open," | | 3 | "Its needle pointed unwaveringly to" | | 4 | "She glanced around the abandoned" | | 5 | "She turned to see a" | | 6 | "Her heart raced." | | 7 | "she ordered, handing the box" | | 8 | "She glanced at her worn" | | 9 | "He had died during a" | | 10 | "She wouldn't let that happen" | | 11 | "She crouched down and pulled" | | 12 | "It was old, with intricate" | | 13 | "She could feel it." | | 14 | "It all pointed to something" |
| | ratio | 0.197 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 71 | | totalSentences | 76 | | matches | | 0 | "Davies muttered, snapping photos of" | | 1 | "Detective Harlow Quinn crouched beside" | | 2 | "The victim lay sprawled in" | | 3 | "The air was thick with" | | 4 | "Harlow said, picking up a" | | 5 | "It was from an occult" | | 6 | "Davies glanced at her, his" | | 7 | "Harlow pointed to the nearest" | | 8 | "Davies frowned, his freckled complexion" | | 9 | "He pointed to the heavy" | | 10 | "Harlow asked, her eyes narrowing" | | 11 | "Something was off." | | 12 | "The evidence didn't add up." | | 13 | "The victim, a young woman" | | 14 | "Her eyes were wide open," | | 15 | "Harlow's gaze shifted to the" | | 16 | "The small brass compass, etched" | | 17 | "Its needle pointed unwaveringly to" | | 18 | "Davies asked, peering over her" | | 19 | "Harlow replied, her voice tight" |
| | ratio | 0.934 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 76 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 33 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 16 | | uselessAdditionCount | 5 | | matches | | 0 | "Harlow asked, her eyes narrowing as she scanned the scene" | | 1 | "Harlow replied, her voice tight" | | 2 | "Davies said, his voice tense" | | 3 | "Harlow finished, her voice cold" | | 4 | "Harlow said, her voice steely" |
| |
| 25.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 13 | | fancyCount | 5 | | fancyTags | | 0 | "Davies muttered (mutter)" | | 1 | "Harlow murmured (murmur)" | | 2 | "a voice called out (call out)" | | 3 | "she ordered (order)" | | 4 | "Davies called out (call out)" |
| | dialogueSentences | 40 | | tagDensity | 0.325 | | leniency | 0.65 | | rawRatio | 0.385 | | effectiveRatio | 0.25 | |