| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 8 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 71 | | tagDensity | 0.113 | | leniency | 0.225 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 97.69% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 2167 | | totalAiIsmAdverbs | 1 | | found | | | highlights | | |
| 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) | |
| 58.47% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 2167 | | totalAiIsms | 18 | | found | | | highlights | | 0 | "pulsed" | | 1 | "warmth" | | 2 | "whisper" | | 3 | "trembled" | | 4 | "marble" | | 5 | "silence" | | 6 | "footsteps" | | 7 | "mosaic" | | 8 | "comfortable" | | 9 | "echo" | | 10 | "echoes" |
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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 | 195 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 3 | | narrationSentences | 195 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 258 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 29 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 2167 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 9 | | unquotedAttributions | 0 | | matches | (empty) | |
| 33.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 85 | | wordCount | 1771 | | uniqueNames | 17 | | maxNameDensity | 2.09 | | worstName | "Aurora" | | maxWindowNameDensity | 4 | | worstWindowName | "Aurora" | | discoveredNames | | Aurora | 37 | | Richmond | 2 | | Heartstone | 1 | | Isolde | 18 | | Cardiff | 1 | | French | 1 | | Cantonese | 1 | | Italian | 1 | | Golden | 1 | | Empress | 1 | | Yu-Fei | 2 | | East | 1 | | London | 1 | | Dymas | 1 | | Nyx | 13 | | Fae-forged | 1 | | Fae | 2 |
| | persons | | 0 | "Aurora" | | 1 | "Isolde" | | 2 | "Empress" | | 3 | "Yu-Fei" | | 4 | "Dymas" | | 5 | "Nyx" |
| | places | | 0 | "Richmond" | | 1 | "Cardiff" | | 2 | "French" | | 3 | "Golden" | | 4 | "East" | | 5 | "London" |
| | globalScore | 0.455 | | windowScore | 0.333 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 141 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.461 | | wordCount | 2167 | | matches | | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 258 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 146 | | mean | 14.84 | | std | 13.56 | | cv | 0.914 | | sampleLengths | | 0 | 17 | | 1 | 53 | | 2 | 13 | | 3 | 7 | | 4 | 14 | | 5 | 71 | | 6 | 8 | | 7 | 20 | | 8 | 23 | | 9 | 5 | | 10 | 8 | | 11 | 6 | | 12 | 36 | | 13 | 20 | | 14 | 3 | | 15 | 5 | | 16 | 9 | | 17 | 6 | | 18 | 5 | | 19 | 14 | | 20 | 6 | | 21 | 17 | | 22 | 14 | | 23 | 44 | | 24 | 9 | | 25 | 6 | | 26 | 6 | | 27 | 34 | | 28 | 4 | | 29 | 12 | | 30 | 2 | | 31 | 17 | | 32 | 1 | | 33 | 6 | | 34 | 42 | | 35 | 12 | | 36 | 17 | | 37 | 10 | | 38 | 3 | | 39 | 24 | | 40 | 8 | | 41 | 4 | | 42 | 1 | | 43 | 8 | | 44 | 3 | | 45 | 13 | | 46 | 41 | | 47 | 7 | | 48 | 13 | | 49 | 2 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 195 | | matches | | 0 | "been carved" | | 1 | "been chiselled" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 291 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 258 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1776 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 41 | | adverbRatio | 0.023085585585585586 | | lyAdverbCount | 4 | | lyAdverbRatio | 0.0022522522522522522 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 258 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 258 | | mean | 8.4 | | std | 5 | | cv | 0.595 | | sampleLengths | | 0 | 17 | | 1 | 13 | | 2 | 11 | | 3 | 10 | | 4 | 19 | | 5 | 3 | | 6 | 10 | | 7 | 7 | | 8 | 8 | | 9 | 4 | | 10 | 2 | | 11 | 19 | | 12 | 13 | | 13 | 10 | | 14 | 29 | | 15 | 8 | | 16 | 4 | | 17 | 16 | | 18 | 5 | | 19 | 18 | | 20 | 5 | | 21 | 4 | | 22 | 4 | | 23 | 6 | | 24 | 15 | | 25 | 10 | | 26 | 11 | | 27 | 9 | | 28 | 11 | | 29 | 3 | | 30 | 5 | | 31 | 4 | | 32 | 5 | | 33 | 6 | | 34 | 5 | | 35 | 14 | | 36 | 6 | | 37 | 7 | | 38 | 10 | | 39 | 14 | | 40 | 15 | | 41 | 12 | | 42 | 17 | | 43 | 9 | | 44 | 3 | | 45 | 3 | | 46 | 6 | | 47 | 8 | | 48 | 5 | | 49 | 18 |
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| 58.40% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 6 | | diversityRatio | 0.3643410852713178 | | totalSentences | 258 | | uniqueOpeners | 94 | |
| 91.07% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 5 | | totalSentences | 183 | | matches | | 0 | "Then the opening narrowed to" | | 1 | "Then a grape dropped somewhere" | | 2 | "Then a broad cook at" | | 3 | "More ran beneath her collar" | | 4 | "Somewhere beneath the stone, metal" |
| | ratio | 0.027 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 25 | | totalSentences | 183 | | matches | | 0 | "She caught herself on a" | | 1 | "Their violet eyes cast two" | | 2 | "Her silver hair stirred in" | | 3 | "They went on." | | 4 | "She recognised the pattern of" | | 5 | "Her skin had the dry," | | 6 | "His eyes were pale and" | | 7 | "She stepped back before the" | | 8 | "They had drawn themselves narrower," | | 9 | "They left the cheers and" | | 10 | "Their fingers flattened against empty" | | 11 | "It felt solid beneath her" | | 12 | "She released them." | | 13 | "She threw a second handful" | | 14 | "Its slender moonsilver blade had" | | 15 | "She pressed harder." | | 16 | "She drew it down the" | | 17 | "Its columns had been carved" | | 18 | "It climbed without splashing, gathered" | | 19 | "She watched until the effort" |
| | ratio | 0.137 | |
| 69.29% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 143 | | totalSentences | 183 | | matches | | 0 | "The portal took the winter" | | 1 | "She caught herself on a" | | 2 | "The Heartstone pendant pulsed beneath" | | 3 | "Nyx glanced back." | | 4 | "Their violet eyes cast two" | | 5 | "Aurora saw nothing where the" | | 6 | "Rows of them climbed the" | | 7 | "The uppermost vineyards floated above" | | 8 | "Fruit hung among the leaves" | | 9 | "Light came from everywhere, pressing" | | 10 | "Isolde stepped onto the road." | | 11 | "Her silver hair stirred in" | | 12 | "Aurora lowered her gaze." | | 13 | "Nyx unfolded beside them, their" | | 14 | "The amber light thinned the" | | 15 | "Nyx’s whisper moved through the" | | 16 | "Aurora looked at Isolde." | | 17 | "Isolde’s pale lavender eyes settled" | | 18 | "Isolde turned towards the far" | | 19 | "Vines had pushed through the" |
| | ratio | 0.781 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 183 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 82 | | technicalSentenceCount | 4 | | matches | | 0 | "The Heartstone pendant pulsed beneath her shirt, its warmth answering the departed gateway before settling into a faint glow." | | 1 | "Rows of them climbed the hills on either side, their terraces rising higher than physics had any business allowing." | | 2 | "Her silver hair stirred in a breeze that carried cloves, woodsmoke and the green bite of crushed stems." | | 3 | "For a moment she heard tyres hissing over wet tarmac and her mother calling up the stairs, telling her she would miss the train." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 8 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 8 | | fancyCount | 2 | | fancyTags | | 0 | "Nyx whispered (whisper)" | | 1 | "their whisper sighed (sigh)" |
| | dialogueSentences | 71 | | tagDensity | 0.113 | | leniency | 0.225 | | rawRatio | 0.25 | | effectiveRatio | 0.056 | |