| 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 | 1090 | | 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) | |
| 72.48% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1090 | | totalAiIsms | 6 | | found | | | highlights | | 0 | "silk" | | 1 | "warmth" | | 2 | "churned" | | 3 | "shattered" | | 4 | "rhythmic" | | 5 | "churn" |
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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 | 61 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 61 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 78 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 32 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1089 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 2 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 23 | | wordCount | 930 | | uniqueNames | 9 | | maxNameDensity | 0.86 | | worstName | "Aurora" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Aurora" | | discoveredNames | | Aurora | 8 | | Heartstone | 2 | | Veil | 1 | | London | 1 | | Shade | 1 | | Nyx | 5 | | Cardiff | 1 | | Fae | 1 | | Isolde | 3 |
| | persons | | 0 | "Aurora" | | 1 | "Veil" | | 2 | "Shade" | | 3 | "Nyx" | | 4 | "Isolde" |
| | places | | | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 58 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1089 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 78 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 40 | | mean | 27.23 | | std | 22.59 | | cv | 0.83 | | sampleLengths | | 0 | 8 | | 1 | 52 | | 2 | 60 | | 3 | 6 | | 4 | 33 | | 5 | 9 | | 6 | 52 | | 7 | 33 | | 8 | 9 | | 9 | 35 | | 10 | 13 | | 11 | 20 | | 12 | 55 | | 13 | 15 | | 14 | 3 | | 15 | 1 | | 16 | 71 | | 17 | 10 | | 18 | 15 | | 19 | 6 | | 20 | 73 | | 21 | 70 | | 22 | 4 | | 23 | 51 | | 24 | 4 | | 25 | 20 | | 26 | 32 | | 27 | 7 | | 28 | 15 | | 29 | 27 | | 30 | 72 | | 31 | 15 | | 32 | 5 | | 33 | 36 | | 34 | 12 | | 35 | 51 | | 36 | 6 | | 37 | 17 | | 38 | 12 | | 39 | 54 |
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| 88.01% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 61 | | matches | | 0 | "been smoothed" | | 1 | "were cleaned" | | 2 | "been chiseled" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 142 | | matches | | |
| 69.60% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 1 | | semicolonCount | 1 | | flaggedSentences | 2 | | totalSentences | 78 | | ratio | 0.026 | | matches | | 0 | "The black stone had not been chiseled; it had melted into place, frozen mid-boil, with delicate iron hooks driven into the joints to hold silver chains." | | 1 | "A set of three distinct gouges grooved the metal—claw marks wide enough to span her ribcage." |
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| 88.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 937 | | adjectiveStacks | 2 | | stackExamples | | 0 | "translucent, pomegranate-sized globes" | | 1 | "grey, salt-crusted rind" |
| | adverbCount | 16 | | adverbRatio | 0.017075773745997867 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.005336179295624333 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 78 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 78 | | mean | 13.96 | | std | 6.5 | | cv | 0.465 | | sampleLengths | | 0 | 8 | | 1 | 14 | | 2 | 19 | | 3 | 19 | | 4 | 11 | | 5 | 24 | | 6 | 25 | | 7 | 6 | | 8 | 20 | | 9 | 13 | | 10 | 9 | | 11 | 5 | | 12 | 11 | | 13 | 19 | | 14 | 17 | | 15 | 20 | | 16 | 13 | | 17 | 9 | | 18 | 19 | | 19 | 16 | | 20 | 13 | | 21 | 5 | | 22 | 15 | | 23 | 15 | | 24 | 25 | | 25 | 15 | | 26 | 6 | | 27 | 9 | | 28 | 3 | | 29 | 1 | | 30 | 19 | | 31 | 12 | | 32 | 17 | | 33 | 17 | | 34 | 6 | | 35 | 10 | | 36 | 15 | | 37 | 6 | | 38 | 9 | | 39 | 6 | | 40 | 20 | | 41 | 22 | | 42 | 16 | | 43 | 14 | | 44 | 16 | | 45 | 24 | | 46 | 16 | | 47 | 4 | | 48 | 10 | | 49 | 26 |
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| 79.06% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 5 | | diversityRatio | 0.5128205128205128 | | totalSentences | 78 | | uniqueOpeners | 40 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 61 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 11 | | totalSentences | 61 | | matches | | 0 | "She gripped the hilt of" | | 1 | "Her boot heels clicked on" | | 2 | "She touched her left wrist," | | 3 | "She did not look back." | | 4 | "She paused, crouching beside the" | | 5 | "Her gaze lifted to the" | | 6 | "It was magnificent and choked" | | 7 | "They descended a flight of" | | 8 | "Her pale lavender eyes fixed" | | 9 | "They reached the floor of" | | 10 | "She drew the Fae blade" |
| | ratio | 0.18 | |
| 74.75% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 47 | | totalSentences | 61 | | matches | | 0 | "The boundary parted like oil" | | 1 | "Heat hit Aurora first, dense" | | 2 | "She gripped the hilt of" | | 3 | "Nyx poured across the glassy" | | 4 | "Aurora stepped past the threshold." | | 5 | "Her boot heels clicked on" | | 6 | "She touched her left wrist," | | 7 | "The steam off the current" | | 8 | "Isolde drifted past, the hem" | | 9 | "Waist-length silver hair drifted over" | | 10 | "She did not look back." | | 11 | "Aurora tracked the canal's curve" | | 12 | "Clusters of translucent, pomegranate-sized globes" | | 13 | "A low, continuous drone rose" | | 14 | "She paused, crouching beside the" | | 15 | "The moonsilver blade gleamed cold" | | 16 | "Nyx stretched an arm, the" | | 17 | "The moment the Shade’s silhouette" | | 18 | "The globe contracted with a" | | 19 | "The glass sizzled, spitting white" |
| | ratio | 0.77 | |
| 81.97% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 61 | | matches | | | ratio | 0.016 | |
| 42.86% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 50 | | technicalSentenceCount | 7 | | matches | | 0 | "Nyx poured across the glassy flagstones, their form flattening into a two-dimensional ribbon before rising six feet of liquid silhouette." | | 1 | "To the right, a canal cut through the terrace, carrying a dark, viscous fluid that churned with thick red bubbles." | | 2 | "Waist-length silver hair drifted over her shoulder, caught in a breeze that carried no cooling relief." | | 3 | "Vast aqueducts bridged the gaps between cliffs, bleeding rivers of deep purple into hanging orchards that dwarfed the city squares of Cardiff." | | 4 | "Here, the heat pooled into stagnant pockets that smelled of fermenting plums and woodsmoke." | | 5 | "The droning grew louder, swelling from a distant vibration into a rhythmic, grinding churn that shuddered through the soles of Aurora's boots." | | 6 | "Far down the terraced valley, the purple canopies rippled against the heavy wind, shaking loose a shower of crimson chaff that drifted upward into the sky like …" |
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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 | |