| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 2 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 2 | | tagDensity | 1 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 287 | | 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) | |
| 65.16% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 287 | | totalAiIsms | 2 | | found | | | highlights | | |
| 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 | 27 | | matches | (empty) | |
| 0.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 1 | | narrationSentences | 27 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 27 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 45 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 296 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 2 | | unquotedAttributions | 0 | | matches | (empty) | |
| 62.59% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 43 | | wordCount | 286 | | uniqueNames | 22 | | maxNameDensity | 1.75 | | worstName | "Nyx" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Nyx" | | discoveredNames | | Aurora | 3 | | Rory | 4 | | Nyx | 5 | | Isolde | 5 | | Fae | 4 | | Grove | 2 | | Richmond | 2 | | Park | 2 | | Heartstone | 2 | | Pendant | 1 | | Fae-Forged | 1 | | Blade | 1 | | Veil | 2 | | Dymas | 1 | | Opening | 1 | | Entering | 1 | | Exploration | 1 | | Discoveries | 1 | | Unease | 1 | | Fae-touched | 1 | | Wonder | 1 | | End | 1 |
| | persons | | 0 | "Aurora" | | 1 | "Rory" | | 2 | "Nyx" | | 3 | "Isolde" | | 4 | "Discoveries" | | 5 | "Unease" |
| | places | | 0 | "Fae" | | 1 | "Grove" | | 2 | "Richmond" | | 3 | "Park" | | 4 | "Fae-touched" |
| | globalScore | 0.626 | | windowScore | 0.833 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 19 | | 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 | 296 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 27 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 9 | | mean | 32.89 | | std | 26.39 | | cv | 0.802 | | sampleLengths | | |
| 92.27% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 27 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 53 | | matches | (empty) | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 2 | | semicolonCount | 0 | | flaggedSentences | 2 | | totalSentences | 27 | | ratio | 0.074 | | matches | | 0 | "The environment should be alien and wondrous, described through exploration — what they see, hear, feel." | | 1 | "Nyx provides contrast — being a shade, they might sense things differently." |
| |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 281 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 5 | | adverbRatio | 0.017793594306049824 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.017793594306049824 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 27 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 27 | | mean | 10.93 | | std | 8.81 | | cv | 0.806 | | sampleLengths | | 0 | 3 | | 1 | 21 | | 2 | 16 | | 3 | 4 | | 4 | 6 | | 5 | 10 | | 6 | 7 | | 7 | 5 | | 8 | 3 | | 9 | 9 | | 10 | 19 | | 11 | 5 | | 12 | 27 | | 13 | 3 | | 14 | 12 | | 15 | 5 | | 16 | 9 | | 17 | 11 | | 18 | 9 | | 19 | 15 | | 20 | 8 | | 21 | 10 | | 22 | 6 | | 23 | 12 | | 24 | 10 | | 25 | 45 | | 26 | 5 |
| |
| 96.30% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 1 | | diversityRatio | 0.7777777777777778 | | totalSentences | 27 | | uniqueOpeners | 21 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 27 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 4 | | totalSentences | 27 | | matches | | 0 | "I need to decide who" | | 1 | "They find the grove entrance." | | 2 | "I'll use Rory as POV" | | 3 | "I'll write the scene now." |
| | ratio | 0.148 | |
| 100.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 12 | | totalSentences | 27 | | matches | | 0 | "Analysis of requirements:" | | 1 | "The instructions want a 1000+" | | 2 | "The environment should be alien" | | 3 | "World-building through character experience, not" | | 4 | "Codex entries to reference: characters" | | 5 | "I need to decide who" | | 6 | "The instructions don't specify, but" | | 7 | "They find the grove entrance." | | 8 | "I'll use Rory as POV" | | 9 | "Nyx provides contrast — being" | | 10 | "The grove should feel alive," | | 11 | "I'll write the scene now." |
| | ratio | 0.444 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 27 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 10 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 2 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |