| 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 | 1381 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 80.00% | AI-ism character names | Target: 0 AI-default names (17 tracked, −20% each) | | codexExemptions | (empty) | | found | | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 45.69% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1381 | | totalAiIsms | 15 | | found | | 0 | | | 1 | | word | "down her spine" | | count | 1 |
| | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | |
| | highlights | | 0 | "weight" | | 1 | "down her spine" | | 2 | "pulse" | | 3 | "comforting" | | 4 | "perfect" | | 5 | "scanned" | | 6 | "silence" | | 7 | "flicker" | | 8 | "shimmered" | | 9 | "gloom" |
| |
| 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 | 141 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 141 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 179 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 28 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1383 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 2 | | unquotedAttributions | 0 | | matches | (empty) | |
| 50.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 46 | | wordCount | 1112 | | uniqueNames | 8 | | maxNameDensity | 1.98 | | worstName | "Rory" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Rory" | | discoveredNames | | Park | 1 | | Nyx | 10 | | December | 1 | | Rory | 22 | | Heartstone | 1 | | Isolde | 5 | | Violet | 3 | | Petals | 3 |
| | persons | | 0 | "Nyx" | | 1 | "Rory" | | 2 | "Isolde" | | 3 | "Petals" |
| | places | | | globalScore | 0.511 | | windowScore | 0.5 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 87 | | 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 | 1383 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 179 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 80 | | mean | 17.29 | | std | 16.05 | | cv | 0.928 | | sampleLengths | | 0 | 12 | | 1 | 48 | | 2 | 27 | | 3 | 33 | | 4 | 7 | | 5 | 13 | | 6 | 4 | | 7 | 20 | | 8 | 2 | | 9 | 5 | | 10 | 33 | | 11 | 8 | | 12 | 5 | | 13 | 6 | | 14 | 15 | | 15 | 37 | | 16 | 61 | | 17 | 3 | | 18 | 13 | | 19 | 7 | | 20 | 62 | | 21 | 1 | | 22 | 10 | | 23 | 5 | | 24 | 22 | | 25 | 6 | | 26 | 17 | | 27 | 3 | | 28 | 9 | | 29 | 55 | | 30 | 18 | | 31 | 11 | | 32 | 9 | | 33 | 1 | | 34 | 3 | | 35 | 60 | | 36 | 8 | | 37 | 51 | | 38 | 24 | | 39 | 3 | | 40 | 12 | | 41 | 11 | | 42 | 4 | | 43 | 9 | | 44 | 7 | | 45 | 1 | | 46 | 10 | | 47 | 4 | | 48 | 5 | | 49 | 8 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 141 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 197 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 2 | | semicolonCount | 0 | | flaggedSentences | 2 | | totalSentences | 179 | | ratio | 0.011 | | matches | | 0 | "Scent rose thick enough to chew — green sap and honey and crushed petals." | | 1 | "The scent changed with each stride — honey to pepper to iron to rain." |
| |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1112 | | adjectiveStacks | 1 | | stackExamples | | | adverbCount | 32 | | adverbRatio | 0.02877697841726619 | | lyAdverbCount | 2 | | lyAdverbRatio | 0.0017985611510791368 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 179 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 179 | | mean | 7.73 | | std | 4.88 | | cv | 0.632 | | sampleLengths | | 0 | 12 | | 1 | 17 | | 2 | 10 | | 3 | 17 | | 4 | 4 | | 5 | 5 | | 6 | 16 | | 7 | 6 | | 8 | 9 | | 9 | 18 | | 10 | 6 | | 11 | 7 | | 12 | 9 | | 13 | 4 | | 14 | 4 | | 15 | 12 | | 16 | 2 | | 17 | 6 | | 18 | 2 | | 19 | 5 | | 20 | 3 | | 21 | 8 | | 22 | 7 | | 23 | 10 | | 24 | 3 | | 25 | 1 | | 26 | 1 | | 27 | 8 | | 28 | 5 | | 29 | 6 | | 30 | 15 | | 31 | 21 | | 32 | 3 | | 33 | 2 | | 34 | 2 | | 35 | 3 | | 36 | 6 | | 37 | 3 | | 38 | 9 | | 39 | 7 | | 40 | 11 | | 41 | 15 | | 42 | 2 | | 43 | 6 | | 44 | 8 | | 45 | 3 | | 46 | 13 | | 47 | 4 | | 48 | 3 | | 49 | 4 |
| |
| 70.39% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 9 | | diversityRatio | 0.45251396648044695 | | totalSentences | 179 | | uniqueOpeners | 81 | |
| 51.28% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 130 | | matches | | 0 | "Then the stream chuckled again," | | 1 | "Only Isolde walked ahead without" |
| | ratio | 0.015 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 22 | | totalSentences | 130 | | matches | | 0 | "It carried Nyx's voice." | | 1 | "She leaned her weight into" | | 2 | "Her bright blue eyes searched" | | 3 | "Her boots sank into soft" | | 4 | "She looked back." | | 5 | "Their violet gaze tracked it" | | 6 | "Her mouth opened." | | 7 | "Their feet left no dent" | | 8 | "She tapped the glass." | | 9 | "They moved deeper." | | 10 | "She wore a dress of" | | 11 | "She left no print." | | 12 | "Her boots left deep crescents" | | 13 | "She stopped an arm's length" | | 14 | "She drew the blade." | | 15 | "Their form thinned at the" | | 16 | "Her pulse thudded in her" | | 17 | "She brushed a poppy head." | | 18 | "Their voice brushed her ear," | | 19 | "Her face stared back, hair" |
| | ratio | 0.169 | |
| 33.08% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 111 | | totalSentences | 130 | | matches | | 0 | "Rory ducked under the low" | | 1 | "Richmond Park stretched grey and" | | 2 | "Mist curled between them." | | 3 | "Nyx stood at her shoulder." | | 4 | "Violet light burned where eyes" | | 5 | "Rory pulled the silver chain" | | 6 | "The stone at the end," | | 7 | "A spark lived in the" | | 8 | "The wind moved though no" | | 9 | "It carried Nyx's voice." | | 10 | "Rory rubbed the crescent mark" | | 11 | "The scar paled against cold" | | 12 | "Rory stepped closer." | | 13 | "Bark split under her palm," | | 14 | "She leaned her weight into" | | 15 | "Her bright blue eyes searched" | | 16 | "Air hung there." | | 17 | "Rory pushed her straight black" | | 18 | "Sound dropped out." | | 19 | "Her boots sank into soft" |
| | ratio | 0.854 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 130 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 43 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 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 | |