| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1309 | | 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) | |
| 61.80% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1309 | | totalAiIsms | 10 | | found | | | highlights | | 0 | "wavering" | | 1 | "reminder" | | 2 | "stomach" | | 3 | "perfect" | | 4 | "whisper" | | 5 | "familiar" | | 6 | "weight" | | 7 | "marble" | | 8 | "pulsed" |
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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 | 69 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 0 | | narrationSentences | 69 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 69 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 61 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1309 | | ratio | 0 | | matches | (empty) | |
| 75.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 5 | | unquotedAttributions | 1 | | matches | | 0 | "The fruits watch what is consumed, Isolde said, her voice clear over the rustle of leaves." |
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| 83.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 56 | | wordCount | 1309 | | uniqueNames | 25 | | maxNameDensity | 1.07 | | worstName | "Rory" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Rory" | | discoveredNames | | Carter | 1 | | Heartstone | 2 | | Pendant | 1 | | London | 3 | | Veil | 3 | | Rory | 14 | | Isolde | 9 | | Richmond | 1 | | Park | 1 | | December | 1 | | Welsh | 1 | | Yu-Fei | 1 | | Golden | 1 | | Empress | 1 | | Silas | 1 | | Eva | 1 | | Barry | 1 | | Island | 1 | | Earth | 1 | | Dymas | 3 | | Fae-forged | 2 | | Evan | 1 | | Cardiff | 1 | | Prince | 1 | | Nyx | 3 |
| | persons | | 0 | "Carter" | | 1 | "Veil" | | 2 | "Rory" | | 3 | "Isolde" | | 4 | "Yu-Fei" | | 5 | "Silas" | | 6 | "Eva" | | 7 | "Dymas" | | 8 | "Evan" | | 9 | "Prince" | | 10 | "Nyx" |
| | places | | 0 | "London" | | 1 | "Richmond" | | 2 | "Park" | | 3 | "Golden" | | 4 | "Barry" | | 5 | "Island" | | 6 | "Earth" | | 7 | "Cardiff" |
| | globalScore | 0.965 | | windowScore | 0.833 | |
| 63.79% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 58 | | glossingSentenceCount | 2 | | matches | | 0 | "tasted like cinnamon and burnt sugar, thi" | | 1 | "looked like pomegranates at first glance" |
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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 | 1309 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 69 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 15 | | mean | 87.27 | | std | 55.37 | | cv | 0.635 | | sampleLengths | | 0 | 92 | | 1 | 145 | | 2 | 88 | | 3 | 86 | | 4 | 208 | | 5 | 110 | | 6 | 3 | | 7 | 63 | | 8 | 141 | | 9 | 32 | | 10 | 161 | | 11 | 58 | | 12 | 15 | | 13 | 46 | | 14 | 61 |
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| 95.09% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 69 | | matches | | 0 | "is consumed" | | 1 | "is given" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 205 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 1 | | flaggedSentences | 1 | | totalSentences | 69 | | ratio | 0.014 | | matches | | 0 | "Isolde had told her only those with supernatural sight could see the Veil’s distortion clearly; Rory, human, had to squint to trace its wavering edges." |
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| 88.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1318 | | adjectiveStacks | 2 | | stackExamples | | 0 | "left deep, clear prints" | | 1 | "stained deep purple, thick wine" |
| | adverbCount | 37 | | adverbRatio | 0.028072837632776935 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.0037936267071320183 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 69 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 69 | | mean | 18.97 | | std | 11.33 | | cv | 0.597 | | sampleLengths | | 0 | 27 | | 1 | 27 | | 2 | 28 | | 3 | 10 | | 4 | 17 | | 5 | 20 | | 6 | 6 | | 7 | 30 | | 8 | 25 | | 9 | 32 | | 10 | 15 | | 11 | 14 | | 12 | 23 | | 13 | 10 | | 14 | 9 | | 15 | 5 | | 16 | 27 | | 17 | 14 | | 18 | 31 | | 19 | 41 | | 20 | 15 | | 21 | 38 | | 22 | 27 | | 23 | 22 | | 24 | 13 | | 25 | 60 | | 26 | 14 | | 27 | 19 | | 28 | 19 | | 29 | 22 | | 30 | 25 | | 31 | 31 | | 32 | 13 | | 33 | 3 | | 34 | 23 | | 35 | 2 | | 36 | 3 | | 37 | 18 | | 38 | 3 | | 39 | 14 | | 40 | 15 | | 41 | 22 | | 42 | 24 | | 43 | 17 | | 44 | 19 | | 45 | 30 | | 46 | 14 | | 47 | 16 | | 48 | 5 | | 49 | 11 |
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| 74.40% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 2 | | diversityRatio | 0.463768115942029 | | totalSentences | 69 | | uniqueOpeners | 32 | |
| 49.75% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 67 | | matches | | 0 | "So many grapes fell from" |
| | ratio | 0.015 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 17 | | totalSentences | 67 | | matches | | 0 | "She choked on air that" | | 1 | "It was amber, warm and" | | 2 | "She glanced back over her" | | 3 | "Their violet eyes glowed, cutting" | | 4 | "She was barefoot, and when" | | 5 | "They had left Isolde’s grove" | | 6 | "She bit into it without" | | 7 | "It was her mother’s Welsh" | | 8 | "It was every good thing" | | 9 | "She swallowed hard to keep" | | 10 | "His hands were raw, crisscrossed" | | 11 | "He never looked up, not" | | 12 | "She wrapped her fingers around" | | 13 | "They crested a hill an" | | 14 | "She turned to Isolde, her" | | 15 | "He has waited for the" | | 16 | "Your wait ends here." |
| | ratio | 0.254 | |
| 79.40% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 51 | | totalSentences | 67 | | matches | | 0 | "Aurora Carter stumbled over the" | | 1 | "The Heartstone Pendant around her" | | 2 | "She choked on air that" | | 3 | "It was amber, warm and" | | 4 | "She glanced back over her" | | 5 | "The rift hung behind them," | | 6 | "Isolde had told her only" | | 7 | "Nyx stepped through right behind" | | 8 | "Their violet eyes glowed, cutting" | | 9 | "Isolde crossed next, her waist-length" | | 10 | "She was barefoot, and when" | | 11 | "Rory’s boots left deep, clear" | | 12 | "Isolde’s feet never disturbed a" | | 13 | "Rory rubbed the crescent-shaped scar" | | 14 | "They had left Isolde’s grove" | | 15 | "The grove’s time had always" | | 16 | "The three of them moved" | | 17 | "Rory bent to pick up" | | 18 | "She bit into it without" | | 19 | "It was her mother’s Welsh" |
| | ratio | 0.761 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 67 | | matches | (empty) | | ratio | 0 | |
| 25.97% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 55 | | technicalSentenceCount | 9 | | matches | | 0 | "Aurora Carter stumbled over the threshold of the rift, her scuffed black delivery boots sinking six inches into loam that reeked of turned earth and overripe fi…" | | 1 | "Nyx stepped through right behind her, and shifted from wispy shadow to solid form, their six-foot-two frame casting a stretch of inky darkness across the loam t…" | | 2 | "First came the vineyards, rows and rows of gnarled vines that stretched as far as the eye could see, heavy with clusters of grapes that glowed pale indigo, thei…" | | 3 | "Rory bent to pick up a whole grape that had rolled to her boot, its skin firm and warm under her fingers." | | 4 | "His hands were raw, crisscrossed with blisters that oozed clear fluid, and his shirt hung in tatters off his shoulders, stained with wine and gravy." | | 5 | "Next came the orchard, trees with trunks as wide as London buses, their canopies heavy with fruit that looked like pomegranates at first glance." | | 6 | "Long wooden tables stretched for miles, packed with figures that shifted from human to monstrous, their forks clinking, their shouts carrying up the hill to whe…" | | 7 | "Grand tents strung with glowing lanterns dotted the landscape, and in the exact center of the realm, a black marble palace rose, its spires piercing the amber s…" | | 8 | "This was where they’d come to find the benefactor who had left the pendant on her doorstep three months prior, the stranger who had promised answers about the s…" |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 0 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |