| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 12 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 47 | | tagDensity | 0.255 | | leniency | 0.511 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 93.99% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1664 | | totalAiIsmAdverbs | 2 | | 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) | |
| 60.94% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1664 | | totalAiIsms | 13 | | found | | | highlights | | 0 | "throb" | | 1 | "pulse" | | 2 | "chilled" | | 3 | "stomach" | | 4 | "warmth" | | 5 | "familiar" | | 6 | "footsteps" | | 7 | "streaming" | | 8 | "marble" | | 9 | "depths" |
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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 | 173 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 2 | | narrationSentences | 173 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 208 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 30 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1664 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 12 | | unquotedAttributions | 0 | | matches | (empty) | |
| 50.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 73 | | wordCount | 1455 | | uniqueNames | 18 | | maxNameDensity | 1.92 | | worstName | "Aurora" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Aurora" | | discoveredNames | | Heartstone | 4 | | Aurora | 28 | | Park | 1 | | Fae-forged | 1 | | Isolde | 10 | | London | 1 | | Silas | 1 | | Golden | 2 | | Empress | 1 | | Yu-Fei | 1 | | Richmond | 2 | | Cardiff | 1 | | Evan | 1 | | Fae | 2 | | Dymas | 2 | | Nyx | 9 | | Vines | 3 | | Hungry | 3 |
| | persons | | 0 | "Heartstone" | | 1 | "Aurora" | | 2 | "Isolde" | | 3 | "Silas" | | 4 | "Evan" | | 5 | "Nyx" | | 6 | "Vines" |
| | places | | 0 | "Park" | | 1 | "London" | | 2 | "Richmond" | | 3 | "Cardiff" | | 4 | "Dymas" |
| | globalScore | 0.538 | | windowScore | 0.5 | |
| 83.04% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 112 | | glossingSentenceCount | 3 | | matches | | 0 | "looked like someone had cut a doorway fro" | | 1 | "appeared beside her without crossing the ground between" | | 2 | "appeared in front of them" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.601 | | wordCount | 1664 | | matches | | 0 | "not seeds but tiny black beetles" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 208 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 120 | | mean | 13.87 | | std | 14.34 | | cv | 1.034 | | sampleLengths | | 0 | 16 | | 1 | 45 | | 2 | 29 | | 3 | 5 | | 4 | 28 | | 5 | 9 | | 6 | 48 | | 7 | 22 | | 8 | 48 | | 9 | 19 | | 10 | 3 | | 11 | 6 | | 12 | 9 | | 13 | 5 | | 14 | 1 | | 15 | 19 | | 16 | 14 | | 17 | 5 | | 18 | 2 | | 19 | 57 | | 20 | 7 | | 21 | 7 | | 22 | 3 | | 23 | 28 | | 24 | 2 | | 25 | 42 | | 26 | 24 | | 27 | 11 | | 28 | 6 | | 29 | 8 | | 30 | 13 | | 31 | 6 | | 32 | 28 | | 33 | 5 | | 34 | 39 | | 35 | 6 | | 36 | 7 | | 37 | 5 | | 38 | 5 | | 39 | 16 | | 40 | 7 | | 41 | 14 | | 42 | 20 | | 43 | 4 | | 44 | 59 | | 45 | 1 | | 46 | 1 | | 47 | 1 | | 48 | 2 | | 49 | 5 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 173 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 240 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 2 | | flaggedSentences | 1 | | totalSentences | 208 | | ratio | 0.005 | | matches | | 0 | "The clusters overhead changed as they passed: green grapes that glowed from within; fruit shaped like small hearts; pale berries with thin human fingers growing from their stems." |
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| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1460 | | adjectiveStacks | 1 | | stackExamples | | 0 | "tiny pearl-coloured tooth." |
| | adverbCount | 36 | | adverbRatio | 0.024657534246575342 | | lyAdverbCount | 3 | | lyAdverbRatio | 0.002054794520547945 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 208 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 208 | | mean | 8 | | std | 5.59 | | cv | 0.699 | | sampleLengths | | 0 | 16 | | 1 | 16 | | 2 | 24 | | 3 | 5 | | 4 | 5 | | 5 | 16 | | 6 | 8 | | 7 | 5 | | 8 | 12 | | 9 | 16 | | 10 | 5 | | 11 | 4 | | 12 | 8 | | 13 | 10 | | 14 | 30 | | 15 | 5 | | 16 | 17 | | 17 | 10 | | 18 | 7 | | 19 | 6 | | 20 | 17 | | 21 | 8 | | 22 | 19 | | 23 | 3 | | 24 | 4 | | 25 | 2 | | 26 | 9 | | 27 | 5 | | 28 | 1 | | 29 | 8 | | 30 | 11 | | 31 | 10 | | 32 | 4 | | 33 | 5 | | 34 | 2 | | 35 | 5 | | 36 | 15 | | 37 | 9 | | 38 | 28 | | 39 | 7 | | 40 | 7 | | 41 | 3 | | 42 | 7 | | 43 | 8 | | 44 | 13 | | 45 | 2 | | 46 | 13 | | 47 | 8 | | 48 | 12 | | 49 | 9 |
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| 60.26% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 8 | | diversityRatio | 0.38461538461538464 | | totalSentences | 208 | | uniqueOpeners | 80 | |
| 89.49% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 4 | | totalSentences | 149 | | matches | | 0 | "Then one straightened." | | 1 | "Then another smell slid beneath" | | 2 | "Slowly, he turned." | | 3 | "Then it widened with a" |
| | ratio | 0.027 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 34 | | totalSentences | 149 | | matches | | 0 | "Their tall outline drank the" | | 1 | "She had brought it because" | | 2 | "It looked like someone had" | | 3 | "Her flat above Silas’s bar" | | 4 | "She stepped through." | | 5 | "Her boots struck pale gravel," | | 6 | "Their body lost its solidity" | | 7 | "Her feet touched down without" | | 8 | "His face had no eyes." | | 9 | "He lifted a hand in" | | 10 | "Its skin split." | | 11 | "She stepped around it." | | 12 | "Their trunks twisted like braided" | | 13 | "She wore a dress of" | | 14 | "Her voice carried no child’s" | | 15 | "It scraped like a knife" | | 16 | "Her lips peeled back from" | | 17 | "She saw herself at nineteen" | | 18 | "She drew the Fae blade." | | 19 | "Her petal dress browned at" |
| | ratio | 0.228 | |
| 47.25% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 123 | | totalSentences | 149 | | matches | | 0 | "The Heartstone began to throb" | | 1 | "Each pulse pushed heat through" | | 2 | "Richmond Park lay behind them" | | 3 | "Amber light poured through it." | | 4 | "Nyx stopped at Aurora’s shoulder." | | 5 | "Their tall outline drank the" | | 6 | "Violet eyes hovered in a" | | 7 | "Isolde’s silver hair hung straight" | | 8 | "Wildflowers crowded around her bare" | | 9 | "Aurora gripped the Fae-forged blade" | | 10 | "The moonsilver dagger chilled her" | | 11 | "She had brought it because" | | 12 | "The portal made no noise." | | 13 | "It looked like someone had" | | 14 | "Vines climbed white arches taller" | | 15 | "Smoke drifted above them in" | | 16 | "The air carried roasted spice," | | 17 | "Aurora looked at her." | | 18 | "Nyx moved one long hand" | | 19 | "Shadow curled from their fingers" |
| | ratio | 0.826 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 149 | | matches | (empty) | | ratio | 0 | |
| 83.33% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 60 | | technicalSentenceCount | 5 | | matches | | 0 | "So did the Golden Empress, Yu-Fei shouting at delivery drivers who crushed the cartons, the greasy warmth of the kitchen, the familiar shriek of buses on wet ro…" | | 1 | "Smooth skin stretched from brow to cheekbones, unbroken except for a mouth that opened too wide as he smiled at them." | | 2 | "The clusters overhead changed as they passed: green grapes that glowed from within; fruit shaped like small hearts; pale berries with thin human fingers growing…" | | 3 | "Trees rose from black soil in rows that disappeared into amber haze." | | 4 | "Carved into the first step sat the same symbol that marked the Heartstone: a circle split by a jagged red line." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 12 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 1.06% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 11 | | fancyCount | 7 | | fancyTags | | 0 | "Isolde murmured (murmur)" | | 1 | "they whispered (whisper)" | | 2 | "Aurora muttered (mutter)" | | 3 | "Nyx whispered (whisper)" | | 4 | "the girl sang (sing)" | | 5 | "Nyx breathed (breathe)" | | 6 | "they whispered (whisper)" |
| | dialogueSentences | 47 | | tagDensity | 0.234 | | leniency | 0.468 | | rawRatio | 0.636 | | effectiveRatio | 0.298 | |