| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | |
| 84.08% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 628 | | 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) | |
| 12.42% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 628 | | totalAiIsms | 11 | | found | | | highlights | | 0 | "rhythmic" | | 1 | "shattered" | | 2 | "porcelain" | | 3 | "gloom" | | 4 | "pulse" | | 5 | "standard" | | 6 | "traced" | | 7 | "pristine" | | 8 | "weight" | | 9 | "scanned" | | 10 | "perfect" |
| |
| 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 | 50 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 50 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 50 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 23 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 627 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 0 | | unquotedAttributions | 0 | | matches | (empty) | |
| 94.18% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 19 | | wordCount | 627 | | uniqueNames | 7 | | maxNameDensity | 1.12 | | worstName | "Quinn" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Quinn" | | discoveredNames | | Camden | 1 | | Harlow | 2 | | Quinn | 7 | | Vance | 5 | | Northern | 1 | | Line | 1 | | Morris | 2 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Vance" | | 3 | "Morris" |
| | places | (empty) | | globalScore | 0.942 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 46 | | 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 | 627 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 50 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 27 | | mean | 23.22 | | std | 12.01 | | cv | 0.517 | | sampleLengths | | 0 | 51 | | 1 | 15 | | 2 | 33 | | 3 | 44 | | 4 | 21 | | 5 | 13 | | 6 | 32 | | 7 | 15 | | 8 | 12 | | 9 | 29 | | 10 | 19 | | 11 | 24 | | 12 | 14 | | 13 | 17 | | 14 | 54 | | 15 | 18 | | 16 | 11 | | 17 | 22 | | 18 | 29 | | 19 | 33 | | 20 | 9 | | 21 | 12 | | 22 | 28 | | 23 | 31 | | 24 | 9 | | 25 | 16 | | 26 | 16 |
| |
| 98.25% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 50 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 98 | | matches | (empty) | |
| 85.71% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 1 | | semicolonCount | 0 | | flaggedSentences | 1 | | totalSentences | 50 | | ratio | 0.02 | | matches | | 0 | "Eighteen years on the force taught her the scent of iron and copper, but this air carried something else—ozone and scorched wool." |
| |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 631 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 15 | | adverbRatio | 0.02377179080824089 | | lyAdverbCount | 7 | | lyAdverbRatio | 0.011093502377179081 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 50 | | echoCount | 0 | | echoWords | (empty) | |
| 87.73% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 50 | | mean | 12.54 | | std | 4.63 | | cv | 0.369 | | sampleLengths | | 0 | 9 | | 1 | 16 | | 2 | 15 | | 3 | 11 | | 4 | 15 | | 5 | 11 | | 6 | 22 | | 7 | 13 | | 8 | 6 | | 9 | 9 | | 10 | 16 | | 11 | 21 | | 12 | 13 | | 13 | 16 | | 14 | 16 | | 15 | 5 | | 16 | 10 | | 17 | 12 | | 18 | 11 | | 19 | 15 | | 20 | 3 | | 21 | 19 | | 22 | 12 | | 23 | 2 | | 24 | 10 | | 25 | 14 | | 26 | 6 | | 27 | 11 | | 28 | 14 | | 29 | 15 | | 30 | 10 | | 31 | 15 | | 32 | 18 | | 33 | 11 | | 34 | 7 | | 35 | 15 | | 36 | 21 | | 37 | 8 | | 38 | 15 | | 39 | 18 | | 40 | 9 | | 41 | 5 | | 42 | 7 | | 43 | 16 | | 44 | 12 | | 45 | 19 | | 46 | 12 | | 47 | 9 | | 48 | 16 | | 49 | 16 |
| |
| 92.67% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 2 | | diversityRatio | 0.58 | | totalSentences | 50 | | uniqueOpeners | 29 | |
| 68.03% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 49 | | matches | | 0 | "Just a charred circle spanning" |
| | ratio | 0.02 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 8 | | totalSentences | 49 | | matches | | 0 | "Her boots crunched over shattered" | | 1 | "It radiates outward from a" | | 2 | "She crouched again, unhooking her" | | 3 | "She scraped a tiny sliver" | | 4 | "We found no prints, no" | | 5 | "She pocketed the knife and" | | 6 | "They use these old lines" | | 7 | "You chase phantoms on every" |
| | ratio | 0.163 | |
| 51.84% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 40 | | totalSentences | 49 | | matches | | 0 | "Condensation dripped from rusted iron" | | 1 | "Detective Harlow Quinn stepped past" | | 2 | "Her boots crunched over shattered" | | 3 | "A flashlight beam cut through" | | 4 | "The brass watch on her" | | 5 | "Forensics officers crouched around a" | | 6 | "A junior constable named Vance" | | 7 | "The ground is completely fused," | | 8 | "Quinn knelt beside the scorch" | | 9 | "The grain curled upward instead" | | 10 | "It radiates outward from a" | | 11 | "Vance checked his notebook, flipping" | | 12 | "Power surge traveled up the" | | 13 | "Quinn traced the edge of" | | 14 | "Transformers blow outward, scorching surrounding" | | 15 | "The roof tiles are pristine," | | 16 | "Vance shoved his hands deep" | | 17 | "Drafts probably carried the plume" | | 18 | "Quinn stood, her sharp jaw" | | 19 | "A faint green luminescence caught" |
| | ratio | 0.816 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 49 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 37 | | 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 | |