| 57.14% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 14 | | adverbTagCount | 2 | | adverbTags | | 0 | "she said quietly [quietly]" | | 1 | "Isolde said softly [softly]" |
| | dialogueSentences | 27 | | tagDensity | 0.519 | | leniency | 1 | | rawRatio | 0.143 | | effectiveRatio | 0.143 | |
| 85.01% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1334 | | totalAiIsmAdverbs | 4 | | found | | | highlights | | 0 | "slowly" | | 1 | "utterly" | | 2 | "softly" |
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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) | |
| 70.01% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1334 | | totalAiIsms | 8 | | found | | | highlights | | 0 | "silk" | | 1 | "stomach" | | 2 | "pulsed" | | 3 | "shimmered" | | 4 | "perfect" | | 5 | "flickered" | | 6 | "could feel" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "hung in the air" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 86 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 86 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 98 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 40 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 2 | | markdownWords | 2 | | totalWords | 1334 | | ratio | 0.001 | | matches | | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 19 | | unquotedAttributions | 0 | | matches | (empty) | |
| 80.31% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 38 | | wordCount | 1148 | | uniqueNames | 11 | | maxNameDensity | 1.39 | | worstName | "Rory" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Rory" | | discoveredNames | | Veil | 1 | | Thames-side | 1 | | Isolde | 6 | | Half-Fae | 1 | | Rory | 16 | | Heartstone | 2 | | Nyx | 6 | | Yu-Fei | 1 | | Cheung | 1 | | Sunday | 1 | | Fae | 2 |
| | persons | | 0 | "Veil" | | 1 | "Isolde" | | 2 | "Rory" | | 3 | "Heartstone" | | 4 | "Nyx" | | 5 | "Yu-Fei" | | 6 | "Cheung" |
| | places | | | globalScore | 0.803 | | windowScore | 0.833 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 67 | | 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 | 1334 | | matches | (empty) | |
| 64.63% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 3 | | totalSentences | 98 | | matches | | 0 | "total that she" | | 1 | "saw that every" | | 2 | "noticed that they" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 39 | | mean | 34.21 | | std | 29.75 | | cv | 0.87 | | sampleLengths | | 0 | 7 | | 1 | 47 | | 2 | 24 | | 3 | 39 | | 4 | 6 | | 5 | 12 | | 6 | 69 | | 7 | 13 | | 8 | 129 | | 9 | 6 | | 10 | 46 | | 11 | 6 | | 12 | 69 | | 13 | 4 | | 14 | 14 | | 15 | 58 | | 16 | 97 | | 17 | 56 | | 18 | 3 | | 19 | 7 | | 20 | 67 | | 21 | 47 | | 22 | 10 | | 23 | 15 | | 24 | 49 | | 25 | 7 | | 26 | 77 | | 27 | 15 | | 28 | 39 | | 29 | 57 | | 30 | 7 | | 31 | 53 | | 32 | 70 | | 33 | 10 | | 34 | 17 | | 35 | 36 | | 36 | 8 | | 37 | 7 | | 38 | 31 |
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| 93.02% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 86 | | matches | | 0 | "was gone" | | 1 | "was pulled" | | 2 | "been moved" |
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| 90.71% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 3 | | totalVerbs | 183 | | matches | | 0 | "was watering" | | 1 | "was thinking" | | 2 | "were walking" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 98 | | ratio | 0 | | matches | (empty) | |
| 88.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1156 | | adjectiveStacks | 2 | | stackExamples | | 0 | "warm pressed against her" | | 1 | "red, long purple pods" |
| | adverbCount | 35 | | adverbRatio | 0.03027681660899654 | | lyAdverbCount | 14 | | lyAdverbRatio | 0.012110726643598616 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 98 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 98 | | mean | 13.61 | | std | 9.05 | | cv | 0.665 | | sampleLengths | | 0 | 7 | | 1 | 33 | | 2 | 2 | | 3 | 12 | | 4 | 11 | | 5 | 13 | | 6 | 2 | | 7 | 20 | | 8 | 17 | | 9 | 6 | | 10 | 9 | | 11 | 3 | | 12 | 12 | | 13 | 29 | | 14 | 6 | | 15 | 7 | | 16 | 10 | | 17 | 5 | | 18 | 13 | | 19 | 4 | | 20 | 8 | | 21 | 28 | | 22 | 13 | | 23 | 16 | | 24 | 40 | | 25 | 20 | | 26 | 6 | | 27 | 9 | | 28 | 16 | | 29 | 21 | | 30 | 6 | | 31 | 6 | | 32 | 25 | | 33 | 13 | | 34 | 25 | | 35 | 4 | | 36 | 14 | | 37 | 6 | | 38 | 31 | | 39 | 21 | | 40 | 8 | | 41 | 27 | | 42 | 6 | | 43 | 20 | | 44 | 36 | | 45 | 15 | | 46 | 9 | | 47 | 14 | | 48 | 18 | | 49 | 3 |
| |
| 71.77% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 3 | | diversityRatio | 0.4489795918367347 | | totalSentences | 98 | | uniqueOpeners | 44 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 74 | | matches | | 0 | "Then he wiped the spoon" | | 1 | "Somewhere close a smell rose" | | 2 | "Somewhere far behind them a" |
| | ratio | 0.041 | |
| 95.68% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 23 | | totalSentences | 74 | | matches | | 0 | "Her stomach clenched with a" | | 1 | "She looked no more at" | | 2 | "Her own boots had left" | | 3 | "It wasn't sunset or a" | | 4 | "It was the deep, honeyed" | | 5 | "She pressed her palm over" | | 6 | "Their violet eyes drifted across" | | 7 | "They followed the gravel path" | | 8 | "It was a kitchen, or" | | 9 | "She knew the look of" | | 10 | "she said quietly" | | 11 | "They were clear and bright" | | 12 | "She tilted her head, her" | | 13 | "Her mouth was watering, and" | | 14 | "She turned toward it before" | | 15 | "She looked down." | | 16 | "Her hand had drifted to" | | 17 | "She drew it a few" | | 18 | "She let the blade clear" | | 19 | "Her thumb rubbed the little" |
| | ratio | 0.311 | |
| 81.62% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 56 | | totalSentences | 74 | | matches | | 0 | "The Veil gave way like" | | 1 | "Rory felt it first in" | | 2 | "A hand of cold smoke" | | 3 | "Nyx whispered, the voice a" | | 4 | "Woodsmoke, browned butter, split figs," | | 5 | "Her stomach clenched with a" | | 6 | "The Half-Fae woman's silver hair" | | 7 | "She looked no more at" | | 8 | "Rory looked back at the" | | 9 | "Her own boots had left" | | 10 | "Nyx's shadow-feet left a faint" | | 11 | "Isolde's left nothing at all." | | 12 | "Rory straightened and looked up," | | 13 | "The sky was amber." | | 14 | "It wasn't sunset or a" | | 15 | "It was the deep, honeyed" | | 16 | "Vineyards ran in green-black rows," | | 17 | "Orchards came after them, trees" | | 18 | "She pressed her palm over" | | 19 | "The pendant was warm, warmer" |
| | ratio | 0.757 | |
| 67.57% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 74 | | matches | | 0 | "Whoever had pressed it into" |
| | ratio | 0.014 | |
| 79.37% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 45 | | technicalSentenceCount | 4 | | matches | | 0 | "Rory felt it first in her teeth, a low hum that traveled up her jaw, and then the winter dark of the Thames-side alley was gone and something warm pressed again…" | | 1 | "Orchards came after them, trees bent double under fruit Rory had no names for: gold spheres veined in red, long purple pods that dripped something clear, cluste…" | | 2 | "A woman in a stained white coat flipped a pan, and the contents rose in a perfect, glittering arc and came down on a plate that had been moved to meet it withou…" | | 3 | "Somewhere close a smell rose that was exactly her mother's Sunday lamb, rosemary and crackling fat and the steam from potatoes, though she had not smelled it in…" |
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| 89.29% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 14 | | uselessAdditionCount | 1 | | matches | | 0 | "Nyx whispered, the voice a draft through a keyhole" |
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| 1.85% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 12 | | fancyCount | 4 | | fancyTags | | 0 | "Nyx whispered (whisper)" | | 1 | "she murmured (murmur)" | | 2 | "Nyx whispered (whisper)" | | 3 | "Nyx breathed (breathe)" |
| | dialogueSentences | 27 | | tagDensity | 0.444 | | leniency | 0.889 | | rawRatio | 0.333 | | effectiveRatio | 0.296 | |