| 18.18% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 14 | | adverbTagCount | 3 | | adverbTags | | 0 | "she replied curtly [curtly]" | | 1 | "he sighed heavily [heavily]" | | 2 | "Harlow replied coldly [coldly]" |
| | dialogueSentences | 33 | | tagDensity | 0.424 | | leniency | 0.848 | | rawRatio | 0.214 | | effectiveRatio | 0.182 | |
| 79.05% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1432 | | totalAiIsmAdverbs | 6 | | found | | | highlights | | 0 | "quickly" | | 1 | "cautiously" | | 2 | "coldly" | | 3 | "sadly" |
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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) | |
| 26.68% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1432 | | totalAiIsms | 21 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | | | 13 | | | 14 | | | 15 | | | 16 | | | 17 | | | 18 | |
| | highlights | | 0 | "rhythmic" | | 1 | "echoed" | | 2 | "steeled" | | 3 | "flickered" | | 4 | "scanned" | | 5 | "eyebrow" | | 6 | "whisper" | | 7 | "racing" | | 8 | "echoing" | | 9 | "macabre" | | 10 | "sense of" | | 11 | "footsteps" | | 12 | "cacophony" | | 13 | "velvet" | | 14 | "determined" | | 15 | "delve" | | 16 | "facade" | | 17 | "depths" | | 18 | "amiss" |
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| 0.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 5 | | maxInWindow | 4 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 1 |
| | 1 | | label | "sense of foreboding" | | count | 1 |
| | 2 | | label | "air was thick with" | | count | 2 |
| | 3 | | label | "couldn't help but" | | count | 1 |
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| | highlights | | 0 | "eyes narrowed" | | 1 | "A sense of dread" | | 2 | "the air was thick with" | | 3 | "The air was thick with" | | 4 | "couldn't help but feel" |
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| 84.02% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 3 | | narrationSentences | 61 | | matches | | 0 | "A sense of dread" | | 1 | "d with determination" | | 2 | "g with anger" |
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| 49.18% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 4 | | narrationSentences | 61 | | filterMatches | (empty) | | hedgeMatches | | 0 | "try to" | | 1 | "seemed to" | | 2 | "began to" |
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| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 81 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 40 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1432 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 15 | | unquotedAttributions | 0 | | matches | (empty) | |
| 50.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 44 | | wordCount | 1083 | | uniqueNames | 10 | | maxNameDensity | 1.66 | | worstName | "Harlow" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Harlow" | | discoveredNames | | Quinn | 1 | | Tomás | 10 | | Herrera | 1 | | Harlow | 18 | | Raven | 2 | | Nest | 3 | | London | 1 | | Silas | 6 | | Veil | 1 | | Market | 1 |
| | persons | | 0 | "Quinn" | | 1 | "Tomás" | | 2 | "Herrera" | | 3 | "Harlow" | | 4 | "Raven" | | 5 | "Silas" |
| | places | | | globalScore | 0.669 | | windowScore | 0.5 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 55 | | glossingSentenceCount | 1 | | matches | | 0 | "eyes that seemed to see right through her" |
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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 | 1432 | | matches | (empty) | |
| 43.21% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 3 | | totalSentences | 81 | | matches | | 0 | "realizing that Tomás" | | 1 | "noticed that Tomás" | | 2 | "knowing that she" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 40 | | mean | 35.8 | | std | 21.83 | | cv | 0.61 | | sampleLengths | | 0 | 80 | | 1 | 73 | | 2 | 42 | | 3 | 51 | | 4 | 56 | | 5 | 15 | | 6 | 43 | | 7 | 12 | | 8 | 26 | | 9 | 37 | | 10 | 30 | | 11 | 5 | | 12 | 15 | | 13 | 10 | | 14 | 24 | | 15 | 5 | | 16 | 35 | | 17 | 14 | | 18 | 24 | | 19 | 43 | | 20 | 16 | | 21 | 26 | | 22 | 33 | | 23 | 35 | | 24 | 59 | | 25 | 63 | | 26 | 59 | | 27 | 58 | | 28 | 59 | | 29 | 52 | | 30 | 18 | | 31 | 31 | | 32 | 39 | | 33 | 21 | | 34 | 28 | | 35 | 39 | | 36 | 13 | | 37 | 41 | | 38 | 100 | | 39 | 2 |
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| 93.76% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 61 | | matches | | 0 | "being peddled" | | 1 | "was replaced" |
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| 61.11% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 4 | | totalVerbs | 192 | | matches | | 0 | "were starting" | | 1 | "was speaking" | | 2 | "was happening – was making" |
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| 72.31% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 2 | | semicolonCount | 0 | | flaggedSentences | 2 | | totalSentences | 81 | | ratio | 0.025 | | matches | | 0 | "Instead, she found herself standing at the entrance of the Raven's Nest – an old, downtrodden bar that served as the meeting place for many of London's supernatural underground." | | 1 | "A sudden surge of adrenaline coursed through her veins as she realized what was happening – Tomás was making a deal for whatever dangerous artifact he had stolen from the clique." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 592 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 15 | | adverbRatio | 0.02533783783783784 | | lyAdverbCount | 7 | | lyAdverbRatio | 0.011824324324324325 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 81 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 81 | | mean | 17.68 | | std | 8.73 | | cv | 0.494 | | sampleLengths | | 0 | 16 | | 1 | 17 | | 2 | 20 | | 3 | 27 | | 4 | 17 | | 5 | 27 | | 6 | 29 | | 7 | 19 | | 8 | 23 | | 9 | 13 | | 10 | 20 | | 11 | 18 | | 12 | 12 | | 13 | 28 | | 14 | 16 | | 15 | 12 | | 16 | 3 | | 17 | 20 | | 18 | 23 | | 19 | 12 | | 20 | 15 | | 21 | 11 | | 22 | 16 | | 23 | 21 | | 24 | 14 | | 25 | 16 | | 26 | 5 | | 27 | 15 | | 28 | 3 | | 29 | 7 | | 30 | 6 | | 31 | 18 | | 32 | 5 | | 33 | 7 | | 34 | 28 | | 35 | 14 | | 36 | 24 | | 37 | 11 | | 38 | 32 | | 39 | 14 | | 40 | 2 | | 41 | 20 | | 42 | 6 | | 43 | 15 | | 44 | 18 | | 45 | 17 | | 46 | 18 | | 47 | 16 | | 48 | 16 | | 49 | 27 |
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| 80.25% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 0 | | diversityRatio | 0.48148148148148145 | | totalSentences | 81 | | uniqueOpeners | 39 | |
| 55.56% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 60 | | matches | | 0 | "Instead, she found herself standing" |
| | ratio | 0.017 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 17 | | totalSentences | 60 | | matches | | 0 | "She had been chasing Tomás" | | 1 | "She skidded around the same" | | 2 | "Their eyes followed Harlow as" | | 3 | "She noticed a door at" | | 4 | "It made sense that he" | | 5 | "He was a tall, slender" | | 6 | "she replied curtly, turning back" | | 7 | "She knew that chasing Tomás" | | 8 | "she hissed, reaching into her" | | 9 | "He handed it to her" | | 10 | "She slipped it into her" | | 11 | "She scanned the crowd for" | | 12 | "It wasn't long before she" | | 13 | "She didn't know how much" | | 14 | "He quickly slipped whatever he" | | 15 | "she panted, her voice hard" | | 16 | "She smirked, sliding her hand" |
| | ratio | 0.283 | |
| 93.33% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 44 | | totalSentences | 60 | | matches | | 0 | "The rain pounded against the" | | 1 | "Harlow Quinn sprinted through the" | | 2 | "She had been chasing Tomás" | | 3 | "The rhythmic slapping of their" | | 4 | "Tomás darted around a corner," | | 5 | "She skidded around the same" | | 6 | "Harlow whispered under her breath," | | 7 | "Their eyes followed Harlow as" | | 8 | "She noticed a door at" | | 9 | "It made sense that he" | | 10 | "Harlow spun around to see" | | 11 | "He was a tall, slender" | | 12 | "she replied curtly, turning back" | | 13 | "Silas retorted, moving towards her" | | 14 | "Harlow shot back, reaching for" | | 15 | "Silas smirked, wagging a finger" | | 16 | "Harlow's eyes narrowed." | | 17 | "Silas cocked an eyebrow" | | 18 | "The old man laughed, shaking" | | 19 | "Harlow growled through gritted teeth" |
| | ratio | 0.733 | |
| 83.33% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 60 | | matches | | 0 | "Yet, even as she walked" |
| | ratio | 0.017 | |
| 23.81% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 42 | | technicalSentenceCount | 7 | | matches | | 0 | "Instead, she found herself standing at the entrance of the Raven's Nest – an old, downtrodden bar that served as the meeting place for many of London's supernat…" | | 1 | "Dim lights flickered overhead, casting long shadows on the worn faces of the patrons who sat hunched over their drinks." | | 2 | "He was a tall, slender man with a shock of white hair and piercing blue eyes that seemed to see right through her." | | 3 | "Harlow could hear the faint sound of voices echoing from somewhere up ahead, and she followed them cautiously, her hand resting on the handle of her gun." | | 4 | "As she drew closer, she noticed that Tomás was speaking with a tall, hooded man who seemed to be selling him something from a black velvet pouch." | | 5 | "Tomás looked up at the sound of her approach, his eyes widening in shock as he saw her closing in on him." | | 6 | "As she led him back through the winding corridors of the Veil Market, she couldn't help but feel a sense of satisfaction wash over her, knowing that she had fin…" |
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| 53.57% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 14 | | uselessAdditionCount | 2 | | matches | | 0 | "she panted, her voice hard with determination" | | 1 | "Harlow retorted, her grip tightening on his wrist" |
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| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 10 | | fancyCount | 8 | | fancyTags | | 0 | "Harlow whispered (whisper)" | | 1 | "Silas retorted (retort)" | | 2 | "Harlow growled (growl)" | | 3 | "Silas drawled (drawl)" | | 4 | "she hissed (hiss)" | | 5 | "she panted (pant)" | | 6 | "Harlow retorted (retort)" | | 7 | "he sighed heavily (sigh)" |
| | dialogueSentences | 33 | | tagDensity | 0.303 | | leniency | 0.606 | | rawRatio | 0.8 | | effectiveRatio | 0.485 | |