| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 3 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 16 | | tagDensity | 0.188 | | leniency | 0.375 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 742 | | 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) | |
| 32.61% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 742 | | totalAiIsms | 10 | | found | | | highlights | | 0 | "loomed" | | 1 | "echo" | | 2 | "silence" | | 3 | "chaotic" | | 4 | "pulsed" | | 5 | "pulse" | | 6 | "warmth" | | 7 | "vibrated" | | 8 | "churned" |
| |
| 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 | 88 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 88 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 101 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 32 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 5 | | markdownWords | 16 | | totalWords | 735 | | ratio | 0.022 | | matches | | 0 | "Pulse. Warmth." | | 1 | "“Avoid the stones, Rory. Nothing good lives in the dirt.”" | | 2 | "thud" | | 3 | "Step back." | | 4 | "was" |
| |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 3 | | unquotedAttributions | 0 | | matches | (empty) | |
| 83.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 20 | | wordCount | 680 | | uniqueNames | 11 | | maxNameDensity | 0.88 | | worstName | "Rory" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Rory" | | discoveredNames | | Park | 1 | | Fae-touched | 1 | | Yu-Fei | 2 | | Golden | 1 | | Empress | 1 | | Fae | 2 | | Heartstone | 1 | | Hel | 1 | | Orion | 1 | | Rory | 6 | | Eva | 3 |
| | persons | | 0 | "Yu-Fei" | | 1 | "Orion" | | 2 | "Rory" | | 3 | "Eva" |
| | places | | | globalScore | 1 | | windowScore | 0.833 | |
| 95.65% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 46 | | glossingSentenceCount | 1 | | matches | | 0 | "as if leaning in to watch" |
| |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 735 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 101 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 41 | | mean | 17.93 | | std | 16.33 | | cv | 0.911 | | sampleLengths | | 0 | 58 | | 1 | 53 | | 2 | 55 | | 3 | 1 | | 4 | 10 | | 5 | 54 | | 6 | 21 | | 7 | 2 | | 8 | 29 | | 9 | 24 | | 10 | 4 | | 11 | 13 | | 12 | 3 | | 13 | 21 | | 14 | 11 | | 15 | 22 | | 16 | 17 | | 17 | 10 | | 18 | 5 | | 19 | 22 | | 20 | 7 | | 21 | 1 | | 22 | 19 | | 23 | 40 | | 24 | 3 | | 25 | 3 | | 26 | 25 | | 27 | 1 | | 28 | 29 | | 29 | 2 | | 30 | 15 | | 31 | 11 | | 32 | 1 | | 33 | 32 | | 34 | 1 | | 35 | 30 | | 36 | 5 | | 37 | 25 | | 38 | 37 | | 39 | 3 | | 40 | 10 |
| |
| 93.30% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 88 | | matches | | 0 | "were arranged" | | 1 | "being pulled" | | 2 | "was gone" |
| |
| 29.06% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 3 | | totalVerbs | 117 | | matches | | 0 | "was burning" | | 1 | "were swaying" | | 2 | "was writhing" |
| |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 1 | | semicolonCount | 0 | | flaggedSentences | 1 | | totalSentences | 101 | | ratio | 0.01 | | matches | | 0 | "The neon sign of Yu-Fei’s Golden Empress restaurant buzzed in her mind—the order was late, the late fee would bite, but the gates of the Fae realm were more immediate." |
| |
| 88.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 687 | | adjectiveStacks | 2 | | stackExamples | | 0 | "deep, unnatural purple moss." | | 1 | "small crescent-shaped scar" |
| | adverbCount | 27 | | adverbRatio | 0.039301310043668124 | | lyAdverbCount | 4 | | lyAdverbRatio | 0.005822416302765648 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 101 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 101 | | mean | 7.28 | | std | 5.9 | | cv | 0.81 | | sampleLengths | | 0 | 17 | | 1 | 18 | | 2 | 23 | | 3 | 10 | | 4 | 30 | | 5 | 13 | | 6 | 4 | | 7 | 10 | | 8 | 17 | | 9 | 24 | | 10 | 1 | | 11 | 2 | | 12 | 8 | | 13 | 4 | | 14 | 7 | | 15 | 2 | | 16 | 11 | | 17 | 4 | | 18 | 26 | | 19 | 15 | | 20 | 3 | | 21 | 3 | | 22 | 1 | | 23 | 1 | | 24 | 7 | | 25 | 6 | | 26 | 6 | | 27 | 10 | | 28 | 2 | | 29 | 7 | | 30 | 5 | | 31 | 2 | | 32 | 8 | | 33 | 4 | | 34 | 4 | | 35 | 9 | | 36 | 2 | | 37 | 1 | | 38 | 11 | | 39 | 10 | | 40 | 4 | | 41 | 7 | | 42 | 13 | | 43 | 9 | | 44 | 6 | | 45 | 7 | | 46 | 4 | | 47 | 8 | | 48 | 2 | | 49 | 5 |
| |
| 54.13% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 12 | | diversityRatio | 0.39603960396039606 | | totalSentences | 101 | | uniqueOpeners | 40 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 75 | | matches | | 0 | "Just keep moving." | | 1 | "Just keep moving." | | 2 | "Then the world tore open." |
| | ratio | 0.04 | |
| 70.67% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 28 | | totalSentences | 75 | | matches | | 0 | "She thrust a hand behind" | | 1 | "She shoved through a curtain" | | 2 | "They marked the boundary between" | | 3 | "She checked her phone." | | 4 | "She checked her wrist." | | 5 | "It was warm." | | 6 | "It meant a Hel portal" | | 7 | "They swayed as if leaning" | | 8 | "It was high, flat, tasting" | | 9 | "She wore her usual suit," | | 10 | "Her head tilted at an" | | 11 | "She pointed a trembling finger" | | 12 | "She simply dissolved." | | 13 | "Her heels hit the moss" | | 14 | "She was gone." | | 15 | "She whirled around, bracing for" | | 16 | "She ripped the chain over" | | 17 | "She took a step back." | | 18 | "She spun toward the stones." | | 19 | "They weren't leaves." |
| | ratio | 0.373 | |
| 33.33% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 64 | | totalSentences | 75 | | matches | | 0 | "Briars tore at the hem" | | 1 | "Rory forced her legs to" | | 2 | "Richmond Park usually smelled of" | | 3 | "She thrust a hand behind" | | 4 | "The neon sign of Yu-Fei’s" | | 5 | "She shoved through a curtain" | | 6 | "They marked the boundary between" | | 7 | "An hour here could be" | | 8 | "The silence swallowed the word," | | 9 | "She checked her phone." | | 10 | "The screen remained a stubborn," | | 11 | "The signal had died before" | | 12 | "She checked her wrist." | | 13 | "The small crescent-shaped scar from" | | 14 | "The Heartstone pendant, a rough" | | 15 | "It was warm." | | 16 | "It meant a Hel portal" | | 17 | "Yu-Fei had warned her about" | | 18 | "The path she’d come down" | | 19 | "The ferns were too dense." |
| | ratio | 0.853 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 75 | | matches | (empty) | | ratio | 0 | |
| 89.95% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 27 | | technicalSentenceCount | 2 | | matches | | 0 | "The crimson stone grew larger in her hand, pulsing a warning rhythm that hurt her teeth." | | 1 | "Something rose from the tear in reality, tall and impossibly thin, composed of shadow and smoke and something that glistened like oil." |
| |
| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 3 | | uselessAdditionCount | 1 | | matches | | 0 | "Rory whispered, her knees trembling" |
| |
| 87.50% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 3 | | fancyCount | 1 | | fancyTags | | 0 | "Rory whispered (whisper)" |
| | dialogueSentences | 16 | | tagDensity | 0.188 | | leniency | 0.375 | | rawRatio | 0.333 | | effectiveRatio | 0.125 | |