| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 10 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 32 | | tagDensity | 0.313 | | leniency | 0.625 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 78.42% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1390 | | totalAiIsmAdverbs | 6 | | found | | | highlights | | 0 | "very" | | 1 | "gently" | | 2 | "softly" | | 3 | "slowly" |
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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) | |
| 31.65% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1390 | | totalAiIsms | 19 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | word | "practiced ease" | | count | 1 |
| | 5 | | | 6 | | | 7 | | | 8 | | word | "down her spine" | | count | 1 |
| | 9 | | | 10 | | | 11 | | | 12 | | | 13 | | word | "the last thing" | | count | 1 |
| | 14 | | | 15 | |
| | highlights | | 0 | "glint" | | 1 | "echoing" | | 2 | "footsteps" | | 3 | "scanned" | | 4 | "practiced ease" | | 5 | "could feel" | | 6 | "weight" | | 7 | "chill" | | 8 | "down her spine" | | 9 | "silk" | | 10 | "charged" | | 11 | "silence" | | 12 | "resonance" | | 13 | "the last thing" | | 14 | "racing" | | 15 | "gleaming" |
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| 0.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 5 | | maxInWindow | 5 | | found | | 0 | | label | "heart pounded in chest" | | count | 1 |
| | 1 | | label | "eyes widened/narrowed" | | count | 2 |
| | 2 | | label | "air was thick with" | | count | 1 |
| | 3 | | label | "sent a shiver through" | | count | 1 |
|
| | highlights | | 0 | "heart pounded in her chest" | | 1 | "eyes narrowed" | | 2 | "eyes widened" | | 3 | "The air was thick with" | | 4 | "sent a chill down" |
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| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 99 | | matches | (empty) | |
| 56.28% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 3 | | hedgeCount | 3 | | narrationSentences | 99 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 121 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 31 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1384 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 13 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 19 | | wordCount | 1208 | | uniqueNames | 4 | | maxNameDensity | 0.75 | | worstName | "Quinn" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Quinn" | | discoveredNames | | Harlow | 1 | | Quinn | 9 | | Tomás | 8 | | Herrera | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Tomás" | | 3 | "Herrera" |
| | places | (empty) | | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 85 | | glossingSentenceCount | 1 | | matches | | 0 | "items that seemed to shift under her gaze—glass bottles filled with glowing liquid, strange artifacts wrapped in cloth, and weapons that hummed with unseen power" |
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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 | 1384 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 121 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 46 | | mean | 30.09 | | std | 18.96 | | cv | 0.63 | | sampleLengths | | 0 | 100 | | 1 | 15 | | 2 | 57 | | 3 | 61 | | 4 | 62 | | 5 | 43 | | 6 | 49 | | 7 | 9 | | 8 | 38 | | 9 | 18 | | 10 | 40 | | 11 | 28 | | 12 | 16 | | 13 | 21 | | 14 | 15 | | 15 | 13 | | 16 | 19 | | 17 | 24 | | 18 | 10 | | 19 | 26 | | 20 | 40 | | 21 | 54 | | 22 | 57 | | 23 | 3 | | 24 | 40 | | 25 | 14 | | 26 | 26 | | 27 | 3 | | 28 | 43 | | 29 | 49 | | 30 | 19 | | 31 | 13 | | 32 | 34 | | 33 | 21 | | 34 | 37 | | 35 | 20 | | 36 | 14 | | 37 | 27 | | 38 | 13 | | 39 | 14 | | 40 | 49 | | 41 | 34 | | 42 | 30 | | 43 | 16 | | 44 | 35 | | 45 | 15 |
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| 94.63% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 99 | | matches | | 0 | "were filled" | | 1 | "was obscured" | | 2 | "were gone" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 240 | | matches | (empty) | |
| 72.02% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 3 | | semicolonCount | 0 | | flaggedSentences | 3 | | totalSentences | 121 | | ratio | 0.025 | | matches | | 0 | "She didn’t need to see their face to know who they were—Tomás Herrera, the paramedic turned underground medic for the very clique she’d been tailing for months." | | 1 | "There—Tomás, weaving through the throng with practiced ease." | | 2 | "The stalls were filled with items that seemed to shift under her gaze—glass bottles filled with glowing liquid, strange artifacts wrapped in cloth, and weapons that hummed with unseen power." |
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| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1213 | | adjectiveStacks | 1 | | stackExamples | | 0 | "paramedic turned underground medic" |
| | adverbCount | 24 | | adverbRatio | 0.01978565539983512 | | lyAdverbCount | 8 | | lyAdverbRatio | 0.006595218466611707 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 121 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 121 | | mean | 11.44 | | std | 5.98 | | cv | 0.523 | | sampleLengths | | 0 | 18 | | 1 | 14 | | 2 | 16 | | 3 | 27 | | 4 | 25 | | 5 | 9 | | 6 | 2 | | 7 | 4 | | 8 | 9 | | 9 | 17 | | 10 | 16 | | 11 | 4 | | 12 | 2 | | 13 | 9 | | 14 | 11 | | 15 | 11 | | 16 | 10 | | 17 | 16 | | 18 | 13 | | 19 | 11 | | 20 | 19 | | 21 | 17 | | 22 | 15 | | 23 | 8 | | 24 | 12 | | 25 | 13 | | 26 | 10 | | 27 | 17 | | 28 | 18 | | 29 | 14 | | 30 | 5 | | 31 | 4 | | 32 | 11 | | 33 | 8 | | 34 | 19 | | 35 | 18 | | 36 | 10 | | 37 | 11 | | 38 | 19 | | 39 | 16 | | 40 | 12 | | 41 | 7 | | 42 | 9 | | 43 | 19 | | 44 | 2 | | 45 | 4 | | 46 | 11 | | 47 | 3 | | 48 | 8 | | 49 | 2 |
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| 40.91% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 11 | | diversityRatio | 0.2644628099173554 | | totalSentences | 121 | | uniqueOpeners | 32 | |
| 34.36% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 97 | | matches | | | ratio | 0.01 | |
| 38.56% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 44 | | totalSentences | 97 | | matches | | 0 | "She didn’t need to see" | | 1 | "His black jacket flapped behind" | | 2 | "she shouted, her voice cutting" | | 3 | "She pushed harder, her lungs" | | 4 | "Her sharp jaw tightened, and" | | 5 | "Her watch, the worn leather" | | 6 | "She couldn’t lose him." | | 7 | "She pulled her flashlight from" | | 8 | "She descended, each step echoing" | | 9 | "She pushed it open, her" | | 10 | "She rounded a corner and" | | 11 | "She cursed under her breath" | | 12 | "She turned slowly, her flashlight" | | 13 | "He was tall, broad-shouldered, with" | | 14 | "His fingers dug into her" | | 15 | "she said, her voice steady" | | 16 | "His lips curled into a" | | 17 | "She glanced over his shoulder," | | 18 | "She reached for her cuffs," | | 19 | "He laughed, a deep, rumbling" |
| | ratio | 0.454 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 91 | | totalSentences | 97 | | matches | | 0 | "The rain hammered down on" | | 1 | "Detective Harlow Quinn sprinted down" | | 2 | "The suspect was fast, a" | | 3 | "She didn’t need to see" | | 4 | "His black jacket flapped behind" | | 5 | "she shouted, her voice cutting" | | 6 | "She pushed harder, her lungs" | | 7 | "Her sharp jaw tightened, and" | | 8 | "Her watch, the worn leather" | | 9 | "She couldn’t lose him." | | 10 | "Tomás vanished down a set" | | 11 | "Quinn hesitated at the top," | | 12 | "The stairwell was unlit, the" | | 13 | "She pulled her flashlight from" | | 14 | "The air smelled damp, metallic," | | 15 | "She descended, each step echoing" | | 16 | "The walls were slick with" | | 17 | "She pushed it open, her" | | 18 | "The sound of footsteps ahead" | | 19 | "The tunnel twisted and turned," |
| | ratio | 0.938 | |
| 51.55% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 97 | | matches | | 0 | "Before she could react, he" |
| | ratio | 0.01 | |
| 84.31% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 61 | | technicalSentenceCount | 5 | | matches | | 0 | "He was tall, broad-shouldered, with eyes that glinted like polished steel." | | 1 | "He laughed, a deep, rumbling sound that sent a chill down her spine." | | 2 | "His smile faded, and he released her shoulder with a shove that sent her stumbling back a step." | | 3 | "The stalls were filled with items that seemed to shift under her gaze—glass bottles filled with glowing liquid, strange artifacts wrapped in cloth, and weapons …" | | 4 | "She caught snippets of conversation, words in languages she didn’t recognize, and the occasional burst of laughter that sounded too sharp, too unnatural." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 10 | | uselessAdditionCount | 5 | | matches | | 0 | "she shouted, her voice cutting through the storm" | | 1 | "she said, her voice steady despite the adrenaline coursing through her" | | 2 | "Quinn said, her tone leaving no room for debate" | | 3 | "she called, her voice cutting through the silence" | | 4 | "the figure said, their voice echoing in her mind" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 7 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 32 | | tagDensity | 0.219 | | leniency | 0.438 | | rawRatio | 0.143 | | effectiveRatio | 0.063 | |