| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 20 | | adverbTagCount | 1 | | adverbTags | | 0 | "Eva smiled weakly [weakly]" |
| | dialogueSentences | 42 | | tagDensity | 0.476 | | leniency | 0.952 | | rawRatio | 0.05 | | effectiveRatio | 0.048 | |
| 86.71% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1129 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | 0 | "really" | | 1 | "quickly" | | 2 | "cautiously" |
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| 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) | |
| 38.00% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1129 | | totalAiIsms | 14 | | found | | | highlights | | 0 | "tension" | | 1 | "glint" | | 2 | "echoes" | | 3 | "quickened" | | 4 | "intricate" | | 5 | "etched" | | 6 | "raced" | | 7 | "chill" | | 8 | "oppressive" | | 9 | "flickered" | | 10 | "tracing" | | 11 | "tinged" | | 12 | "weight" |
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| 66.67% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 2 | | maxInWindow | 2 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 1 |
| | 1 | | label | "hung in the air" | | count | 1 |
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| | highlights | | 0 | "eyes narrowed" | | 1 | "hung in the air" |
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| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 1 | | narrationSentences | 76 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 76 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 98 | | 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 | 1130 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 12 | | unquotedAttributions | 0 | | matches | (empty) | |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 57 | | wordCount | 845 | | uniqueNames | 9 | | maxNameDensity | 3.2 | | worstName | "Quinn" | | maxWindowNameDensity | 5 | | worstWindowName | "Quinn" | | discoveredNames | | Harlow | 1 | | Quinn | 27 | | Tube | 1 | | Morgan | 8 | | Veil | 2 | | Market | 2 | | Eva | 14 | | Kowalski | 1 | | London | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Morgan" | | 3 | "Market" | | 4 | "Eva" | | 5 | "Kowalski" |
| | places | | | globalScore | 0 | | windowScore | 0 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 62 | | glossingSentenceCount | 1 | | matches | | 0 | "officers grew visibly tense, their conver" |
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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 | 1130 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 98 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 42 | | mean | 26.9 | | std | 16.39 | | cv | 0.609 | | sampleLengths | | 0 | 68 | | 1 | 32 | | 2 | 66 | | 3 | 26 | | 4 | 16 | | 5 | 15 | | 6 | 45 | | 7 | 8 | | 8 | 50 | | 9 | 8 | | 10 | 23 | | 11 | 9 | | 12 | 26 | | 13 | 35 | | 14 | 49 | | 15 | 10 | | 16 | 16 | | 17 | 11 | | 18 | 30 | | 19 | 15 | | 20 | 40 | | 21 | 10 | | 22 | 12 | | 23 | 36 | | 24 | 22 | | 25 | 12 | | 26 | 16 | | 27 | 39 | | 28 | 21 | | 29 | 38 | | 30 | 12 | | 31 | 13 | | 32 | 7 | | 33 | 49 | | 34 | 13 | | 35 | 25 | | 36 | 48 | | 37 | 34 | | 38 | 8 | | 39 | 26 | | 40 | 42 | | 41 | 49 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 76 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 158 | | matches | (empty) | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 5 | | semicolonCount | 0 | | flaggedSentences | 5 | | totalSentences | 98 | | ratio | 0.051 | | matches | | 0 | "Her heart quickened as she recognized its significance — the entry toll to the Veil Market." | | 1 | "Quinn noticed something odd about the placement of the bodies — they formed a rough circle, almost ritualistic in nature." | | 2 | "Her eyes narrowed as she spotted another clue — a small brass compass cradled in another victim's hand." | | 3 | "After several minutes, Quinn spotted something — a hidden chamber beneath the platform." | | 4 | "At its center stood an altar cluttered with objects both mundane and mystical — candles, bones, and talismans." |
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| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 845 | | adjectiveStacks | 1 | | stackExamples | | 0 | "stout, clean-shaven man" |
| | adverbCount | 19 | | adverbRatio | 0.022485207100591716 | | lyAdverbCount | 13 | | lyAdverbRatio | 0.015384615384615385 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 98 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 98 | | mean | 11.53 | | std | 5.16 | | cv | 0.448 | | sampleLengths | | 0 | 18 | | 1 | 17 | | 2 | 15 | | 3 | 18 | | 4 | 17 | | 5 | 10 | | 6 | 5 | | 7 | 6 | | 8 | 15 | | 9 | 13 | | 10 | 13 | | 11 | 19 | | 12 | 11 | | 13 | 15 | | 14 | 6 | | 15 | 10 | | 16 | 4 | | 17 | 11 | | 18 | 15 | | 19 | 8 | | 20 | 22 | | 21 | 8 | | 22 | 10 | | 23 | 9 | | 24 | 16 | | 25 | 15 | | 26 | 8 | | 27 | 8 | | 28 | 15 | | 29 | 6 | | 30 | 3 | | 31 | 9 | | 32 | 17 | | 33 | 6 | | 34 | 14 | | 35 | 15 | | 36 | 10 | | 37 | 18 | | 38 | 21 | | 39 | 10 | | 40 | 9 | | 41 | 7 | | 42 | 2 | | 43 | 9 | | 44 | 21 | | 45 | 9 | | 46 | 15 | | 47 | 7 | | 48 | 13 | | 49 | 20 |
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| 73.13% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 5 | | diversityRatio | 0.46938775510204084 | | totalSentences | 98 | | uniqueOpeners | 46 | |
| 48.31% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 69 | | matches | | 0 | "Instead, he gestured towards a" |
| | ratio | 0.014 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 16 | | totalSentences | 69 | | matches | | 0 | "Her salt-and-pepper hair, closely cropped" | | 1 | "He stood near the base" | | 2 | "She stepped closer to the" | | 3 | "She knelt and delicately pried" | | 4 | "His tongue was black and" | | 5 | "Her heart quickened as she" | | 6 | "She leaned in to examine" | | 7 | "She stood and fixed him" | | 8 | "She hadn't seen Eva in" | | 9 | "They worked silently, examining the" | | 10 | "Her eyes narrowed as she" | | 11 | "They pored over it, tracing" | | 12 | "she said, tapping the spot" | | 13 | "They moved quickly, calling for" | | 14 | "She led the way, her" | | 15 | "She approached it cautiously." |
| | ratio | 0.232 | |
| 25.22% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 60 | | totalSentences | 69 | | matches | | 0 | "Detective Harlow Quinn ducked under" | | 1 | "The steady hum of police" | | 2 | "Quinn's polished shoes clicked against" | | 3 | "Her salt-and-pepper hair, closely cropped" | | 4 | "The voice belonged to DCI" | | 5 | "He stood near the base" | | 6 | "Quinn joined Morgan at the" | | 7 | "The underground station still held" | | 8 | "Bodies lay sprawled across the" | | 9 | "The smell of decay hung" | | 10 | "Morgan began, pointing to each" | | 11 | "Quinn frowned, her sharp jawline" | | 12 | "Morgan shook his head." | | 13 | "She stepped closer to the" | | 14 | "She knelt and delicately pried" | | 15 | "His tongue was black and" | | 16 | "Morgan ventured, but his tone" | | 17 | "Quinn glanced around, her brown" | | 18 | "A bone token lay clutched" | | 19 | "Her heart quickened as she" |
| | ratio | 0.87 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 69 | | matches | | 0 | "Now, it served as the" | | 1 | "Before Quinn could respond, a" |
| | ratio | 0.029 | |
| 73.17% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 41 | | technicalSentenceCount | 4 | | matches | | 0 | "His tongue was black and swollen, his eyes wide open and bloodshot, as if he'd seen something that froze him in terror." | | 1 | "Eva's curly red hair framed her worried features, and she clutched her worn leather satchel as if it were a lifeline." | | 2 | "The atmosphere was heavy with an arcane energy that made the hairs on Quinn's neck stand on end." | | 3 | "The Veil Market's tendrils had extended deep into London, and this abandoned station was merely one of many dark corners that harbored its secrets." |
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| 50.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 20 | | uselessAdditionCount | 3 | | matches | | 0 | "Morgan ventured, but his tone lacked conviction" | | 1 | "Quinn replied, her voice steady" | | 2 | "Eva whispered, horrified" |
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| 7.14% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 14 | | fancyCount | 6 | | fancyTags | | 0 | "Eva surmised (surmise)" | | 1 | "Eva whispered (whisper)" | | 2 | "Eva agreed (agree)" | | 3 | "Quinn ordered (order)" | | 4 | "Quinn suggested (suggest)" | | 5 | "Eva whispered (whisper)" |
| | dialogueSentences | 42 | | tagDensity | 0.333 | | leniency | 0.667 | | rawRatio | 0.429 | | effectiveRatio | 0.286 | |