| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 2 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 11 | | tagDensity | 0.182 | | leniency | 0.364 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1667 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 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) | |
| 19.02% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1667 | | totalAiIsms | 27 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | | | 13 | | | 14 | | | 15 | | | 16 | | | 17 | | | 18 | | | 19 | |
| | highlights | | 0 | "rhythmic" | | 1 | "chill" | | 2 | "sanctuary" | | 3 | "silence" | | 4 | "porcelain" | | 5 | "throb" | | 6 | "weight" | | 7 | "pulse" | | 8 | "echoed" | | 9 | "flicker" | | 10 | "dancing" | | 11 | "pulsed" | | 12 | "shimmered" | | 13 | "flickered" | | 14 | "gloom" | | 15 | "vibrated" | | 16 | "silk" | | 17 | "searing" | | 18 | "cacophony" | | 19 | "oppressive" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 0 | | maxInWindow | 0 | | found | (empty) | | highlights | (empty) | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 126 | | matches | (empty) | |
| 97.51% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 4 | | narrationSentences | 126 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 135 | | 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 | 1654 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 3 | | unquotedAttributions | 0 | | matches | (empty) | |
| 98.52% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 41 | | wordCount | 1554 | | uniqueNames | 11 | | maxNameDensity | 1.03 | | worstName | "Aurora" | | maxWindowNameDensity | 2 | | worstWindowName | "Aurora" | | discoveredNames | | Aurora | 16 | | Heartstone | 6 | | Pendant | 2 | | London | 2 | | Richmond | 2 | | Park | 2 | | Grove | 5 | | Golden | 2 | | Empress | 2 | | North | 1 | | South | 1 |
| | persons | | 0 | "Aurora" | | 1 | "Heartstone" | | 2 | "Pendant" | | 3 | "Grove" | | 4 | "Empress" |
| | places | | 0 | "London" | | 1 | "Richmond" | | 2 | "Park" | | 3 | "Golden" |
| | globalScore | 0.985 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 109 | | glossingSentenceCount | 2 | | matches | | 0 | "felt like an insult to the ancient, loa" | | 1 | "looked like polished obsidian" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.605 | | wordCount | 1654 | | matches | | 0 | "not from the trees, but from the ground directly beneath her feet" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 135 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 51 | | mean | 32.43 | | std | 19.13 | | cv | 0.59 | | sampleLengths | | 0 | 96 | | 1 | 9 | | 2 | 10 | | 3 | 73 | | 4 | 47 | | 5 | 10 | | 6 | 55 | | 7 | 42 | | 8 | 9 | | 9 | 16 | | 10 | 59 | | 11 | 40 | | 12 | 14 | | 13 | 46 | | 14 | 46 | | 15 | 32 | | 16 | 7 | | 17 | 33 | | 18 | 39 | | 19 | 1 | | 20 | 21 | | 21 | 51 | | 22 | 56 | | 23 | 28 | | 24 | 40 | | 25 | 31 | | 26 | 49 | | 27 | 27 | | 28 | 8 | | 29 | 64 | | 30 | 43 | | 31 | 17 | | 32 | 43 | | 33 | 17 | | 34 | 37 | | 35 | 16 | | 36 | 40 | | 37 | 8 | | 38 | 45 | | 39 | 42 | | 40 | 10 | | 41 | 37 | | 42 | 31 | | 43 | 6 | | 44 | 29 | | 45 | 33 | | 46 | 22 | | 47 | 28 | | 48 | 43 | | 49 | 32 |
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| 91.34% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 5 | | totalSentences | 126 | | matches | | 0 | "was supposed" | | 1 | "was gone" | | 2 | "were stitched" | | 3 | "was gone" | | 4 | "was replaced" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 3 | | totalVerbs | 244 | | matches | | 0 | "was dying" | | 1 | "were grinning" | | 2 | "was glowing" |
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| 15.87% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 1 | | semicolonCount | 5 | | flaggedSentences | 6 | | totalSentences | 135 | | ratio | 0.044 | | matches | | 0 | "The Grove didn't just look different; it felt hungry." | | 1 | "The Heartstone Pendant was no longer just warm; it burned." | | 2 | "It didn't pull her down; it simply held her, a tethering anchor." | | 3 | "She didn't slice at the hand; she slammed the butt of the knife into the wrist bones." | | 4 | "They didn't speak; they vibrated." | | 5 | "She threw herself toward the wall of brambles, North, South—she didn't care." |
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| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1566 | | adjectiveStacks | 1 | | stackExamples | | 0 | "long, many-jointed arm." |
| | adverbCount | 37 | | adverbRatio | 0.02362707535121328 | | lyAdverbCount | 13 | | lyAdverbRatio | 0.008301404853128991 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 135 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 135 | | mean | 12.25 | | std | 6.3 | | cv | 0.514 | | sampleLengths | | 0 | 15 | | 1 | 16 | | 2 | 23 | | 3 | 31 | | 4 | 11 | | 5 | 9 | | 6 | 10 | | 7 | 12 | | 8 | 7 | | 9 | 25 | | 10 | 4 | | 11 | 25 | | 12 | 10 | | 13 | 14 | | 14 | 16 | | 15 | 4 | | 16 | 3 | | 17 | 10 | | 18 | 2 | | 19 | 14 | | 20 | 5 | | 21 | 13 | | 22 | 13 | | 23 | 8 | | 24 | 9 | | 25 | 23 | | 26 | 10 | | 27 | 9 | | 28 | 6 | | 29 | 10 | | 30 | 6 | | 31 | 11 | | 32 | 31 | | 33 | 11 | | 34 | 7 | | 35 | 7 | | 36 | 9 | | 37 | 17 | | 38 | 14 | | 39 | 6 | | 40 | 10 | | 41 | 10 | | 42 | 20 | | 43 | 11 | | 44 | 17 | | 45 | 18 | | 46 | 13 | | 47 | 9 | | 48 | 10 | | 49 | 7 |
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| 35.19% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 20 | | diversityRatio | 0.26666666666666666 | | totalSentences | 135 | | uniqueOpeners | 36 | |
| 53.33% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 125 | | matches | | 0 | "Usually, Richmond Park offered a" | | 1 | "Then, a soft, wet slither" |
| | ratio | 0.016 | |
| 82.40% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 43 | | totalSentences | 125 | | matches | | 0 | "She checked the silver chain" | | 1 | "Her own voice sounded thin," | | 2 | "She clutched the thermal delivery" | | 3 | "It cast a bleached, unnatural" | | 4 | "Her boots sank into moss" | | 5 | "It wasn't the snap of" | | 6 | "It was the wet, deliberate" | | 7 | "She swung her flashlight beam" | | 8 | "She picked up her pace," | | 9 | "She spun, the flashlight beam" | | 10 | "It moved with too many" | | 11 | "She forced her legs to" | | 12 | "It was a flat slab" | | 13 | "She set the Golden Empress" | | 14 | "She turned to bolt, but" | | 15 | "It didn't pull her down;" | | 16 | "It sprouted inside her skull," | | 17 | "Her heavy boot connected with" | | 18 | "They weren't people." | | 19 | "They were silhouettes of hunger," |
| | ratio | 0.344 | |
| 28.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 108 | | totalSentences | 125 | | matches | | 0 | "She checked the silver chain" | | 1 | "The Heartstone Pendant rested against" | | 2 | "Silence rushed into her ears," | | 3 | "The Grove didn't just look" | | 4 | "Her own voice sounded thin," | | 5 | "She clutched the thermal delivery" | | 6 | "Steam from the Golden Empress’s" | | 7 | "Yu-Fei had been insistent." | | 8 | "The coordinates led here, to" | | 9 | "The moon hung above the" | | 10 | "It cast a bleached, unnatural" | | 11 | "Bluebells and foxgloves stood tall" | | 12 | "The Heartstone gave a sudden," | | 13 | "Her boots sank into moss" | | 14 | "It wasn't the snap of" | | 15 | "It was the wet, deliberate" | | 16 | "She swung her flashlight beam" | | 17 | "The light hit the gnarled" | | 18 | "The bark seemed to ripple," | | 19 | "Aurora’s pulse hammered against the" |
| | ratio | 0.864 | |
| 40.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 125 | | matches | | 0 | "To her left, something crunched." |
| | ratio | 0.008 | |
| 0.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 76 | | technicalSentenceCount | 16 | | matches | | 0 | "Dew-slicked ferns brushed against Aurora’s shins, drenching her denim jeans in a creeping, rhythmic chill." | | 1 | "The Heartstone Pendant rested against her collarbone, a thumbnail of solid blood that hummed with a heat far exceeding the humid London night." | | 2 | "Steam from the Golden Empress’s ginger beef wafted up, a mundane scent that felt like an insult to the ancient, loamy air of the clearing." | | 3 | "The coordinates led here, to a pocket of land that shouldn't exist on any GPS, for a customer who had paid in heavy, gold sovereigns." | | 4 | "It cast a bleached, unnatural light over the wildflowers that choked the forest floor." | | 5 | "Bluebells and foxgloves stood tall and rigid, frozen in a bloom that felt permanent and porcelain." | | 6 | "The bark seemed to ripple, a slow-motion heave of gray wood that settled back into place the moment the beam centered on it." | | 7 | "They moved in unison, a slow, crawling tide of darkness that crept over the white wildflowers, turning the bluebells to ash where they touched." | | 8 | "A high-pitched keen pierced the air, a sound that set her teeth on edge." | | 9 | "Where there had been a clear line of sight to the park beyond, there was now a wall of brambles that shimmered with a faint, oily light." | | 10 | "They had no eyes, only deep, vertical slits that wept a clear, thick fluid." | | 11 | "The sound was a low-frequency hum that vibrated in Aurora’s marrow, making her vision blur." | | 12 | "It smelled of wet earth and something ancient, something that had never known the sun." | | 13 | "The stillness of the night broke into a cacophony of screeching birds and the roar of a wind that shouldn't be there." | | 14 | "She lay there, gasping for air, her heart trying to kick its way out of her ribs." | | 15 | "Aurora scrambled to her feet, leaving the cup on the grass, and didn't stop running until she saw the lights of a petrol station." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 2 | | uselessAdditionCount | 1 | | matches | | 0 | "she hissed, her voice cracking" |
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| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 2 | | fancyCount | 2 | | fancyTags | | 0 | "the voice whispered (whisper)" | | 1 | "she hissed (hiss)" |
| | dialogueSentences | 11 | | tagDensity | 0.182 | | leniency | 0.364 | | rawRatio | 1 | | effectiveRatio | 0.364 | |