| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 18 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 42 | | tagDensity | 0.429 | | leniency | 0.857 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 85.18% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1012 | | totalAiIsmAdverbs | 3 | | 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) | |
| 6.13% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1012 | | totalAiIsms | 19 | | found | | | highlights | | 0 | "scanned" | | 1 | "echoes" | | 2 | "footsteps" | | 3 | "silence" | | 4 | "furrowed" | | 5 | "tracing" | | 6 | "grave" | | 7 | "etched" | | 8 | "flicker" | | 9 | "measured" | | 10 | "racing" | | 11 | "echoed" | | 12 | "furrowing" | | 13 | "navigate" |
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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 | 2 |
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| | highlights | | |
| 69.44% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 4 | | narrationSentences | 60 | | matches | | 0 | "t with determination" | | 1 | "e with fear" | | 2 | "a flicker of sympathy" | | 3 | "g with grief" |
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| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 60 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 82 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 37 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1010 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 6 | | unquotedAttributions | 0 | | matches | (empty) | |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 61 | | wordCount | 668 | | uniqueNames | 12 | | maxNameDensity | 3.44 | | worstName | "Harlow" | | maxWindowNameDensity | 5 | | worstWindowName | "Harlow" | | discoveredNames | | Quinn | 1 | | Tube | 1 | | Detective | 1 | | Sergeant | 1 | | Briggs | 10 | | Harlow | 23 | | Eva | 6 | | Aurora | 9 | | Sinclair | 1 | | Veil | 4 | | Market | 3 | | Compass | 1 |
| | persons | | 0 | "Quinn" | | 1 | "Sergeant" | | 2 | "Briggs" | | 3 | "Harlow" | | 4 | "Eva" | | 5 | "Aurora" | | 6 | "Sinclair" | | 7 | "Market" |
| | places | (empty) | | globalScore | 0 | | windowScore | 0 | |
| 96.81% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 47 | | glossingSentenceCount | 1 | | matches | | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1010 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 82 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 39 | | mean | 25.9 | | std | 14.4 | | cv | 0.556 | | sampleLengths | | 0 | 47 | | 1 | 32 | | 2 | 13 | | 3 | 20 | | 4 | 14 | | 5 | 22 | | 6 | 27 | | 7 | 17 | | 8 | 17 | | 9 | 18 | | 10 | 53 | | 11 | 13 | | 12 | 12 | | 13 | 3 | | 14 | 21 | | 15 | 67 | | 16 | 27 | | 17 | 24 | | 18 | 11 | | 19 | 17 | | 20 | 21 | | 21 | 31 | | 22 | 36 | | 23 | 17 | | 24 | 36 | | 25 | 43 | | 26 | 27 | | 27 | 55 | | 28 | 33 | | 29 | 11 | | 30 | 19 | | 31 | 47 | | 32 | 30 | | 33 | 7 | | 34 | 18 | | 35 | 43 | | 36 | 15 | | 37 | 11 | | 38 | 35 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 60 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 112 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 1 | | semicolonCount | 0 | | flaggedSentences | 1 | | totalSentences | 82 | | ratio | 0.012 | | matches | | 0 | "Harlow's breath caught in her throat as she gently pried it open, revealing a faded photograph of two young women — one with red curls, the other with a brilliant smile." |
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| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 561 | | adjectiveStacks | 1 | | stackExamples | | 0 | "notorious supernatural black market," |
| | adverbCount | 17 | | adverbRatio | 0.030303030303030304 | | lyAdverbCount | 6 | | lyAdverbRatio | 0.0106951871657754 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 82 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 82 | | mean | 12.32 | | std | 7.67 | | cv | 0.623 | | sampleLengths | | 0 | 26 | | 1 | 15 | | 2 | 6 | | 3 | 10 | | 4 | 22 | | 5 | 13 | | 6 | 13 | | 7 | 7 | | 8 | 11 | | 9 | 3 | | 10 | 22 | | 11 | 3 | | 12 | 18 | | 13 | 6 | | 14 | 17 | | 15 | 13 | | 16 | 4 | | 17 | 9 | | 18 | 9 | | 19 | 3 | | 20 | 18 | | 21 | 27 | | 22 | 5 | | 23 | 13 | | 24 | 9 | | 25 | 3 | | 26 | 2 | | 27 | 1 | | 28 | 17 | | 29 | 4 | | 30 | 21 | | 31 | 15 | | 32 | 31 | | 33 | 6 | | 34 | 16 | | 35 | 5 | | 36 | 24 | | 37 | 11 | | 38 | 10 | | 39 | 7 | | 40 | 14 | | 41 | 7 | | 42 | 15 | | 43 | 16 | | 44 | 11 | | 45 | 9 | | 46 | 16 | | 47 | 9 | | 48 | 8 | | 49 | 11 |
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| 67.07% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 0 | | diversityRatio | 0.4024390243902439 | | totalSentences | 82 | | uniqueOpeners | 33 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 59 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 11 | | totalSentences | 59 | | matches | | 0 | "Her sharp eyes scanned the" | | 1 | "She ducked under the tape," | | 2 | "She knew of the notorious" | | 3 | "She knelt beside the body," | | 4 | "Her eyes narrowed as she" | | 5 | "Her trembling hands covered her" | | 6 | "She crouched beside Aurora, her" | | 7 | "Her voice trailed off, a" | | 8 | "She rose to her feet," | | 9 | "She had to uncover the" | | 10 | "He gestured toward a shadowy" |
| | ratio | 0.186 | |
| 27.80% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 51 | | totalSentences | 59 | | matches | | 0 | "Harlow Quinn's boots crunched against" | | 1 | "Her sharp eyes scanned the" | | 2 | "This was no ordinary crime" | | 3 | "She ducked under the tape," | | 4 | "The flickering fluorescent lights cast" | | 5 | "Harlow demanded, her gaze sweeping" | | 6 | "Detective Sergeant Briggs approached, his" | | 7 | "Harlow nodded, her eyes narrowing" | | 8 | "Briggs gestured toward the shadowy" | | 9 | "Harlow's expression darkened." | | 10 | "She knew of the notorious" | | 11 | "Briggs asked, his tone laced" | | 12 | "Harlow strode toward the body," | | 13 | "Briggs consulted his notebook" | | 14 | "Harlow's brow furrowed." | | 15 | "She knelt beside the body," | | 16 | "Her eyes narrowed as she" | | 17 | "Briggs offered, his tone grave" | | 18 | "Harlow stood, her gaze sweeping" | | 19 | "Harlow's eyes narrowed" |
| | ratio | 0.864 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 59 | | matches | | 0 | "If Eva wasn't involved with" | | 1 | "If Eva had one, it" |
| | ratio | 0.034 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 24 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 18 | | uselessAdditionCount | 7 | | matches | | 0 | "Harlow demanded, her gaze sweeping over the gathered officers" | | 1 | "Detective Sergeant Briggs approached, his brow furrowed" | | 2 | "She knelt, her fingers gently tracing the deep gash across Eva's throat" | | 3 | "Harlow whispered, her heart sinking" | | 4 | "trembling hands covered, her shoulders shaking with sobs" | | 5 | "Briggs hesitated, his brow furrowing" | | 6 | "Harlow's jaw tightened, her mind racing" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 4 | | fancyCount | 2 | | fancyTags | | 0 | "Harlow demanded (demand)" | | 1 | "Harlow whispered (whisper)" |
| | dialogueSentences | 42 | | tagDensity | 0.095 | | leniency | 0.19 | | rawRatio | 0.5 | | effectiveRatio | 0.095 | |