| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 11 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 151 | | tagDensity | 0.073 | | leniency | 0.146 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1672 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 100.00% | AI-ism character names | Target: 0 AI-default names (16 tracked, −20% each) | | codexExemptions | | | found | (empty) | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 91.03% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1672 | | totalAiIsms | 3 | | found | | | highlights | | 0 | "lilt" | | 1 | "traced" | | 2 | "footsteps" |
| |
| 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 | 98 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 98 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 238 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 31 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1671 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 28 | | unquotedAttributions | 0 | | matches | (empty) | |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 78 | | wordCount | 855 | | uniqueNames | 6 | | maxNameDensity | 3.86 | | worstName | "Rory" | | maxWindowNameDensity | 6 | | worstWindowName | "Eva" | | discoveredNames | | Raven | 1 | | Nest | 1 | | Rory | 33 | | Silas | 8 | | Cardiff | 2 | | Eva | 33 |
| | persons | | 0 | "Raven" | | 1 | "Nest" | | 2 | "Rory" | | 3 | "Silas" | | 4 | "Eva" |
| | places | | | globalScore | 0 | | windowScore | 0 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 62 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.598 | | wordCount | 1671 | | matches | | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 238 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 167 | | mean | 10.01 | | std | 10.63 | | cv | 1.062 | | sampleLengths | | 0 | 34 | | 1 | 7 | | 2 | 61 | | 3 | 1 | | 4 | 14 | | 5 | 6 | | 6 | 33 | | 7 | 4 | | 8 | 1 | | 9 | 17 | | 10 | 8 | | 11 | 2 | | 12 | 3 | | 13 | 28 | | 14 | 2 | | 15 | 1 | | 16 | 6 | | 17 | 3 | | 18 | 14 | | 19 | 3 | | 20 | 31 | | 21 | 25 | | 22 | 3 | | 23 | 25 | | 24 | 7 | | 25 | 15 | | 26 | 2 | | 27 | 1 | | 28 | 4 | | 29 | 6 | | 30 | 37 | | 31 | 11 | | 32 | 6 | | 33 | 2 | | 34 | 2 | | 35 | 1 | | 36 | 4 | | 37 | 13 | | 38 | 19 | | 39 | 17 | | 40 | 17 | | 41 | 2 | | 42 | 4 | | 43 | 2 | | 44 | 5 | | 45 | 2 | | 46 | 6 | | 47 | 36 | | 48 | 4 | | 49 | 2 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 98 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 147 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 1 | | semicolonCount | 0 | | flaggedSentences | 1 | | totalSentences | 238 | | ratio | 0.004 | | matches | | 0 | "The old habit returned—the quiet scrutiny she’d used on Rory at school, when she could spot a lie before Rory had finished building it." |
| |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 858 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 20 | | adverbRatio | 0.023310023310023312 | | lyAdverbCount | 0 | | lyAdverbRatio | 0 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 238 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 238 | | mean | 7.02 | | std | 5.57 | | cv | 0.794 | | sampleLengths | | 0 | 19 | | 1 | 15 | | 2 | 7 | | 3 | 3 | | 4 | 19 | | 5 | 15 | | 6 | 8 | | 7 | 16 | | 8 | 1 | | 9 | 6 | | 10 | 8 | | 11 | 6 | | 12 | 7 | | 13 | 5 | | 14 | 21 | | 15 | 4 | | 16 | 1 | | 17 | 17 | | 18 | 5 | | 19 | 3 | | 20 | 2 | | 21 | 3 | | 22 | 5 | | 23 | 23 | | 24 | 2 | | 25 | 1 | | 26 | 6 | | 27 | 3 | | 28 | 10 | | 29 | 4 | | 30 | 3 | | 31 | 8 | | 32 | 14 | | 33 | 9 | | 34 | 13 | | 35 | 12 | | 36 | 3 | | 37 | 10 | | 38 | 10 | | 39 | 5 | | 40 | 7 | | 41 | 14 | | 42 | 1 | | 43 | 2 | | 44 | 1 | | 45 | 4 | | 46 | 6 | | 47 | 5 | | 48 | 15 | | 49 | 17 |
| |
| 46.64% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 8 | | diversityRatio | 0.22268907563025211 | | totalSentences | 238 | | uniqueOpeners | 53 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 91 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 15 | | totalSentences | 91 | | matches | | 0 | "She stood beneath it, counting" | | 1 | "She looked up." | | 2 | "Her hair, once a dark" | | 3 | "She turned to answer Silas," | | 4 | "She glanced at the coins" | | 5 | "His limp showed as he" | | 6 | "He disappeared through the doorway" | | 7 | "She lowered it again." | | 8 | "Her left wrist showed where" | | 9 | "She traced one point with" | | 10 | "She drew a breath through" | | 11 | "She looked as if life" | | 12 | "She picked up the whisky" | | 13 | "She looked back at Eva." | | 14 | "She glanced at the door," |
| | ratio | 0.165 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 84 | | totalSentences | 91 | | matches | | 0 | "The green neon above the" | | 1 | "She stood beneath it, counting" | | 2 | "The sound caught her by" | | 3 | "She looked up." | | 4 | "Her hair, once a dark" | | 5 | "A pale streak ran above" | | 6 | "She turned to answer Silas," | | 7 | "Rory’s fingers closed over the" | | 8 | "The woman at the bar" | | 9 | "Rain tapped against the window." | | 10 | "Silas set down a glass" | | 11 | "Eva opened the door." | | 12 | "The name came out with" | | 13 | "Rory bent for the coin." | | 14 | "Eva’s mouth lifted, then settled." | | 15 | "She glanced at the coins" | | 16 | "Eva’s gaze held hers, full" | | 17 | "Rory stepped aside." | | 18 | "Silas reached for the towel" | | 19 | "His limp showed as he" |
| | ratio | 0.923 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 91 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 33 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 11 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 4 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 151 | | tagDensity | 0.026 | | leniency | 0.053 | | rawRatio | 0.25 | | effectiveRatio | 0.013 | |