| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 12 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 49 | | tagDensity | 0.245 | | leniency | 0.49 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 95.17% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1036 | | totalAiIsmAdverbs | 1 | | 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) | |
| 32.43% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1036 | | totalAiIsms | 14 | | found | | | highlights | | 0 | "weight" | | 1 | "unsettled" | | 2 | "effortless" | | 3 | "predator" | | 4 | "chaotic" | | 5 | "sanctuary" | | 6 | "throbbed" | | 7 | "sense of" | | 8 | "vibrated" | | 9 | "pulse" | | 10 | "trembled" | | 11 | "tracing" | | 12 | "glistening" |
| |
| 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 | 43 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 43 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 80 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 32 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1036 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 6 | | unquotedAttributions | 0 | | matches | (empty) | |
| 50.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 26 | | wordCount | 618 | | uniqueNames | 8 | | maxNameDensity | 1.78 | | worstName | "Lucien" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Rory" | | discoveredNames | | Rory | 9 | | Marseille | 1 | | Brick | 1 | | Lane | 1 | | East | 1 | | End | 1 | | Lucien | 11 | | Halloween | 1 |
| | persons | | | places | | 0 | "Marseille" | | 1 | "Brick" | | 2 | "Lane" | | 3 | "East" | | 4 | "End" |
| | globalScore | 0.61 | | windowScore | 0.5 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 40 | | 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 | 1036 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 80 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 52 | | mean | 19.92 | | std | 15.16 | | cv | 0.761 | | sampleLengths | | 0 | 18 | | 1 | 20 | | 2 | 24 | | 3 | 15 | | 4 | 4 | | 5 | 43 | | 6 | 57 | | 7 | 58 | | 8 | 24 | | 9 | 18 | | 10 | 21 | | 11 | 23 | | 12 | 6 | | 13 | 4 | | 14 | 6 | | 15 | 19 | | 16 | 21 | | 17 | 30 | | 18 | 3 | | 19 | 7 | | 20 | 39 | | 21 | 30 | | 22 | 4 | | 23 | 17 | | 24 | 5 | | 25 | 26 | | 26 | 4 | | 27 | 15 | | 28 | 38 | | 29 | 56 | | 30 | 7 | | 31 | 15 | | 32 | 8 | | 33 | 36 | | 34 | 4 | | 35 | 3 | | 36 | 9 | | 37 | 43 | | 38 | 34 | | 39 | 31 | | 40 | 8 | | 41 | 4 | | 42 | 27 | | 43 | 22 | | 44 | 9 | | 45 | 16 | | 46 | 20 | | 47 | 9 | | 48 | 2 | | 49 | 3 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 43 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 100 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 80 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 624 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 6 | | adverbRatio | 0.009615384615384616 | | lyAdverbCount | 1 | | lyAdverbRatio | 0.0016025641025641025 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 80 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 80 | | mean | 12.95 | | std | 7.22 | | cv | 0.558 | | sampleLengths | | 0 | 18 | | 1 | 20 | | 2 | 18 | | 3 | 6 | | 4 | 15 | | 5 | 4 | | 6 | 18 | | 7 | 25 | | 8 | 15 | | 9 | 30 | | 10 | 12 | | 11 | 12 | | 12 | 17 | | 13 | 29 | | 14 | 24 | | 15 | 9 | | 16 | 9 | | 17 | 16 | | 18 | 5 | | 19 | 15 | | 20 | 8 | | 21 | 6 | | 22 | 4 | | 23 | 6 | | 24 | 19 | | 25 | 8 | | 26 | 13 | | 27 | 15 | | 28 | 15 | | 29 | 3 | | 30 | 7 | | 31 | 10 | | 32 | 13 | | 33 | 16 | | 34 | 11 | | 35 | 19 | | 36 | 4 | | 37 | 17 | | 38 | 5 | | 39 | 10 | | 40 | 16 | | 41 | 4 | | 42 | 15 | | 43 | 9 | | 44 | 14 | | 45 | 15 | | 46 | 15 | | 47 | 18 | | 48 | 23 | | 49 | 7 |
| |
| 62.92% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 8 | | diversityRatio | 0.4375 | | totalSentences | 80 | | uniqueOpeners | 35 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 41 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 11 | | totalSentences | 41 | | matches | | 0 | "She slammed her weight against" | | 1 | "He stepped inside, closed the" | | 2 | "He stood in the cramped" | | 3 | "He wore a crisp, tailored" | | 4 | "His heterochromatic eyes, one bright" | | 5 | "He raised his hand, the" | | 6 | "He did not move an" | | 7 | "he hissed, his amber eye" | | 8 | "He leaned down, his face" | | 9 | "He pulled her closer, his" | | 10 | "She parted her lips to" |
| | ratio | 0.268 | |
| 8.78% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 37 | | totalSentences | 41 | | matches | | 0 | "The bottom lock clicked, but" | | 1 | "She slammed her weight against" | | 2 | "Lucien said, his throat-rasping Marseille" | | 3 | "Rory pushed against the wood," | | 4 | "He stepped inside, closed the" | | 5 | "He stood in the cramped" | | 6 | "He wore a crisp, tailored" | | 7 | "His heterochromatic eyes, one bright" | | 8 | "Eva’s flat on Brick Lane" | | 9 | "A pungent aroma of scorched" | | 10 | "Ptolemy, the fat ginger tabby" | | 11 | "Lucien ignored the cat, his" | | 12 | "Rory crossed her arms, hiding" | | 13 | "Lucien leaned on his cane," | | 14 | "Rory stepped into his space," | | 15 | "Lucien’s gaze dropped to her" | | 16 | "Lucien stepped closer, his physical" | | 17 | "He raised his hand, the" | | 18 | "Rory did not flinch, even" | | 19 | "Lucien chuckled, a low rumble" |
| | ratio | 0.902 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 41 | | matches | (empty) | | ratio | 0 | |
| 85.71% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 25 | | technicalSentenceCount | 2 | | matches | | 0 | "He wore a crisp, tailored charcoal woollen suit that hugged his broad shoulders, and his slicked-back platinum hair caught the amber glow of the single lightbul…" | | 1 | "Standing in the threshold was a massive, eyeless beast, its glistening jaws dripping with glowing green acid that hissed as it touched the floor." |
| |
| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 12 | | uselessAdditionCount | 5 | | matches | | 0 | "Rory pushed, her sneakers sliding on the damp linoleum" | | 1 | "Lucien’s gaze dropped, his expression softening into something dark and hungry" | | 2 | "he hissed, his amber eye flaring with sudden, terrifying heat" | | 3 | "Lucien’s hand slid, his thumb tracing the soft skin of her inner elbow" | | 4 | "Lucien whispered, his black eye widening" |
| |
| 68.37% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 5 | | fancyCount | 4 | | fancyTags | | 0 | "he murmured (murmur)" | | 1 | "he hissed (hiss)" | | 2 | "Lucien snapped (snap)" | | 3 | "Lucien whispered (whisper)" |
| | dialogueSentences | 49 | | tagDensity | 0.102 | | leniency | 0.204 | | rawRatio | 0.8 | | effectiveRatio | 0.163 | |