| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 5 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 17 | | tagDensity | 0.294 | | leniency | 0.588 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 779 | | 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) | |
| 87.16% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 779 | | 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 | 47 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 47 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 59 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 43 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 779 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 6 | | unquotedAttributions | 0 | | matches | (empty) | |
| 81.03% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 25 | | wordCount | 580 | | uniqueNames | 13 | | maxNameDensity | 1.38 | | worstName | "Quinn" | | maxWindowNameDensity | 2 | | worstWindowName | "Quinn" | | discoveredNames | | Regent | 1 | | Canal | 1 | | Quinn | 8 | | Tomás | 1 | | Herrera | 5 | | Camden | 1 | | High | 1 | | Street | 1 | | Hackney | 1 | | Underground | 1 | | Saint | 1 | | Christopher | 1 | | Morris | 2 |
| | persons | | 0 | "Regent" | | 1 | "Canal" | | 2 | "Quinn" | | 3 | "Tomás" | | 4 | "Herrera" | | 5 | "Saint" | | 6 | "Christopher" | | 7 | "Morris" |
| | places | | 0 | "Camden" | | 1 | "High" | | 2 | "Street" | | 3 | "Hackney" |
| | globalScore | 0.81 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 36 | | 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 | 779 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 59 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 23 | | mean | 33.87 | | std | 20.92 | | cv | 0.618 | | sampleLengths | | 0 | 53 | | 1 | 9 | | 2 | 37 | | 3 | 47 | | 4 | 54 | | 5 | 48 | | 6 | 14 | | 7 | 17 | | 8 | 35 | | 9 | 6 | | 10 | 83 | | 11 | 46 | | 12 | 20 | | 13 | 56 | | 14 | 10 | | 15 | 32 | | 16 | 14 | | 17 | 10 | | 18 | 10 | | 19 | 67 | | 20 | 48 | | 21 | 41 | | 22 | 22 |
| |
| 97.80% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 47 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 87 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 59 | | ratio | 0 | | matches | (empty) | |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 582 | | adjectiveStacks | 1 | | stackExamples | | 0 | "Far below, faint lights" |
| | adverbCount | 13 | | adverbRatio | 0.022336769759450172 | | lyAdverbCount | 1 | | lyAdverbRatio | 0.001718213058419244 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 59 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 59 | | mean | 13.2 | | std | 8.25 | | cv | 0.625 | | sampleLengths | | 0 | 20 | | 1 | 16 | | 2 | 17 | | 3 | 9 | | 4 | 2 | | 5 | 18 | | 6 | 17 | | 7 | 7 | | 8 | 15 | | 9 | 7 | | 10 | 18 | | 11 | 5 | | 12 | 3 | | 13 | 11 | | 14 | 4 | | 15 | 31 | | 16 | 16 | | 17 | 8 | | 18 | 9 | | 19 | 15 | | 20 | 11 | | 21 | 3 | | 22 | 3 | | 23 | 10 | | 24 | 4 | | 25 | 35 | | 26 | 6 | | 27 | 27 | | 28 | 15 | | 29 | 20 | | 30 | 21 | | 31 | 8 | | 32 | 10 | | 33 | 13 | | 34 | 15 | | 35 | 9 | | 36 | 11 | | 37 | 10 | | 38 | 11 | | 39 | 20 | | 40 | 15 | | 41 | 4 | | 42 | 6 | | 43 | 18 | | 44 | 14 | | 45 | 6 | | 46 | 8 | | 47 | 10 | | 48 | 10 | | 49 | 20 |
| |
| 81.36% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 2 | | diversityRatio | 0.5084745762711864 | | totalSentences | 59 | | uniqueOpeners | 30 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 44 | | matches | (empty) | | ratio | 0 | |
| 92.73% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 14 | | totalSentences | 44 | | matches | | 0 | "Her knee complained on every" | | 1 | "She pulled her radio from" | | 2 | "She glanced at the worn" | | 3 | "He burst out at the" | | 4 | "He pulled something from his" | | 5 | "It was a small carved" | | 6 | "He turned it between his" | | 7 | "Her fingers closed around a" | | 8 | "She drew it out." | | 9 | "He moved two steps closer" | | 10 | "He studied her face in" | | 11 | "His scarred forearm flexed." | | 12 | "She could call it in" | | 13 | "She could wait at the" |
| | ratio | 0.318 | |
| 62.27% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 35 | | totalSentences | 44 | | matches | | 0 | "The rain came sideways off" | | 1 | "The denim jacket he wore" | | 2 | "The sound carried over the" | | 3 | "Quinn's shoes slapped the wet" | | 4 | "Her knee complained on every" | | 5 | "She pulled her radio from" | | 6 | "The radio crackled and died." | | 7 | "Static, then nothing." | | 8 | "She glanced at the worn" | | 9 | "The hands had stopped working" | | 10 | "Herrera swerved left into a" | | 11 | "Quinn followed, her breath sawing" | | 12 | "The alley narrowed to the" | | 13 | "Herrera called over his shoulder" | | 14 | "Quinn kept running." | | 15 | "The name landed like a" | | 16 | "He burst out at the" | | 17 | "Someone had nailed a bone-white" | | 18 | "Herrera stopped at the top" | | 19 | "He pulled something from his" |
| | ratio | 0.795 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 44 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 27 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 5 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 4 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 17 | | tagDensity | 0.235 | | leniency | 0.471 | | rawRatio | 0 | | effectiveRatio | 0 | |