| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 8 | | adverbTagCount | 1 | | adverbTags | | 0 | "she lied smoothly [smoothly]" |
| | dialogueSentences | 21 | | tagDensity | 0.381 | | leniency | 0.762 | | rawRatio | 0.125 | | effectiveRatio | 0.095 | |
| 87.53% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 802 | | totalAiIsmAdverbs | 2 | | 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) | |
| 18.95% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 802 | | totalAiIsms | 13 | | found | | | highlights | | 0 | "scanning" | | 1 | "chill" | | 2 | "gloom" | | 3 | "almost alive" | | 4 | "chaotic" | | 5 | "symphony" | | 6 | "scanned" | | 7 | "weight" | | 8 | "pulse" | | 9 | "pounding" | | 10 | "resolve" | | 11 | "racing" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 72 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 72 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 85 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 24 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 793 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 6 | | unquotedAttributions | 0 | | matches | (empty) | |
| 80.26% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 24 | | wordCount | 717 | | uniqueNames | 11 | | maxNameDensity | 1.39 | | worstName | "Quinn" | | maxWindowNameDensity | 2 | | worstWindowName | "Quinn" | | discoveredNames | | Quinn | 10 | | Broad | 1 | | Court | 1 | | Soho | 1 | | Tube | 1 | | Underground | 1 | | Veil | 1 | | Market | 5 | | Saint | 1 | | Christopher | 1 | | Morris | 1 |
| | persons | | 0 | "Quinn" | | 1 | "Market" | | 2 | "Saint" | | 3 | "Christopher" | | 4 | "Morris" |
| | places | | | globalScore | 0.803 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 59 | | glossingSentenceCount | 1 | | matches | | 0 | "looked like a miniature thunderstorm" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 793 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 85 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 26 | | mean | 30.5 | | std | 17.36 | | cv | 0.569 | | sampleLengths | | 0 | 57 | | 1 | 58 | | 2 | 62 | | 3 | 38 | | 4 | 50 | | 5 | 32 | | 6 | 24 | | 7 | 56 | | 8 | 37 | | 9 | 49 | | 10 | 12 | | 11 | 14 | | 12 | 11 | | 13 | 11 | | 14 | 11 | | 15 | 18 | | 16 | 48 | | 17 | 29 | | 18 | 17 | | 19 | 14 | | 20 | 31 | | 21 | 29 | | 22 | 43 | | 23 | 15 | | 24 | 24 | | 25 | 3 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 72 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 142 | | matches | (empty) | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 5 | | semicolonCount | 0 | | flaggedSentences | 5 | | totalSentences | 85 | | ratio | 0.059 | | matches | | 0 | "That’s when she noticed the faded graffiti—an inverted triangle drawn in ash, barely visible beneath the grime." | | 1 | "She knew the protocol—backup, containment, procedure." | | 2 | "Quinn’s flashlight beam caught fragments of history—faded Tube station signs, broken tiles, and rusting iron girders." | | 3 | "Vendors hawked their wares from makeshift stalls—enchanted relics, shimmering vials of liquid, and creatures that defied logic." | | 4 | "She felt the weight of unfamiliar eyes on her—some curious, others hostile." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 726 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 15 | | adverbRatio | 0.02066115702479339 | | lyAdverbCount | 10 | | lyAdverbRatio | 0.013774104683195593 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 85 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 85 | | mean | 9.33 | | std | 4.81 | | cv | 0.515 | | sampleLengths | | 0 | 12 | | 1 | 19 | | 2 | 12 | | 3 | 2 | | 4 | 12 | | 5 | 10 | | 6 | 22 | | 7 | 13 | | 8 | 13 | | 9 | 12 | | 10 | 9 | | 11 | 11 | | 12 | 17 | | 13 | 6 | | 14 | 7 | | 15 | 8 | | 16 | 8 | | 17 | 6 | | 18 | 4 | | 19 | 5 | | 20 | 7 | | 21 | 14 | | 22 | 13 | | 23 | 16 | | 24 | 4 | | 25 | 3 | | 26 | 18 | | 27 | 9 | | 28 | 5 | | 29 | 4 | | 30 | 9 | | 31 | 11 | | 32 | 12 | | 33 | 17 | | 34 | 18 | | 35 | 9 | | 36 | 9 | | 37 | 16 | | 38 | 12 | | 39 | 9 | | 40 | 16 | | 41 | 16 | | 42 | 8 | | 43 | 4 | | 44 | 8 | | 45 | 7 | | 46 | 7 | | 47 | 5 | | 48 | 6 | | 49 | 7 |
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| 65.10% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 3 | | diversityRatio | 0.4117647058823529 | | totalSentences | 85 | | uniqueOpeners | 35 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 71 | | matches | (empty) | | ratio | 0 | |
| 62.25% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 28 | | totalSentences | 71 | | matches | | 0 | "Her badge gleamed in the" | | 1 | "Her boots splashed through oily" | | 2 | "Her wristwatch dripped with rainwater," | | 3 | "She approached the brick wall" | | 4 | "Her breath came in controlled" | | 5 | "She pressed her palm against" | | 6 | "She knew the protocol—backup, containment," | | 7 | "She flipped on her flashlight" | | 8 | "He turned, tossing it to" | | 9 | "She caught it reflexively." | | 10 | "She declined with a curt" | | 11 | "Her sharp jaw tightened as" | | 12 | "She felt the weight of" | | 13 | "His curly dark hair framed" | | 14 | "He chuckled, gesturing to the" | | 15 | "She flashed the bone token." | | 16 | "He tilted his head, studying" | | 17 | "she lied smoothly, tucking the" | | 18 | "He smirked but didn’t press" | | 19 | "She nodded her thanks and" |
| | ratio | 0.394 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 66 | | totalSentences | 71 | | matches | | 0 | "Harlow Quinn's shout cut through" | | 1 | "Her badge gleamed in the" | | 2 | "The suspect ducked into an" | | 3 | "Every corner led to another" | | 4 | "Her boots splashed through oily" | | 5 | "The rain plastered her salt-and-pepper" | | 6 | "Her wristwatch dripped with rainwater," | | 7 | "The suspect disappeared around yet" | | 8 | "The alley narrowed to a" | | 9 | "She approached the brick wall" | | 10 | "Her breath came in controlled" | | 11 | "That’s when she noticed the" | | 12 | "She pressed her palm against" | | 13 | "The wall yielded with a" | | 14 | "Quinn hesitated, her hand hovering" | | 15 | "She knew the protocol—backup, containment," | | 16 | "This was something else entirely." | | 17 | "She flipped on her flashlight" | | 18 | "The air grew denser, colder," | | 19 | "The steps ended in a" |
| | ratio | 0.93 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 71 | | matches | | 0 | "Before she could react, the" | | 1 | "Before she could react, the" |
| | ratio | 0.028 | |
| 50.69% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 31 | | technicalSentenceCount | 4 | | matches | | 0 | "Her badge gleamed in the flickering streetlamp as she drew her sidearm, tracking the figure darting down Broad Court." | | 1 | "The steps ended in a cavernous space that stretched endlessly into the gloom." | | 2 | "Vendors hawked their wares from makeshift stalls—enchanted relics, shimmering vials of liquid, and creatures that defied logic." | | 3 | "A man wearing a bloodstained apron leaned against his stall, polishing a set of surgical tools." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 8 | | uselessAdditionCount | 2 | | matches | | 0 | "She stepped, her flashlight casting long, jagged shadows" | | 1 | "she said, her voice steady despite the storm brewing around her" |
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| 54.76% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 3 | | fancyCount | 2 | | fancyTags | | 0 | "He chuckled (chuckle)" | | 1 | "she lied smoothly (lie)" |
| | dialogueSentences | 21 | | tagDensity | 0.143 | | leniency | 0.286 | | rawRatio | 0.667 | | effectiveRatio | 0.19 | |