| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 1 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 14 | | tagDensity | 0.071 | | leniency | 0.143 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 95.30% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1064 | | 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) | |
| 6.02% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1064 | | totalAiIsms | 20 | | found | | | highlights | | 0 | "weight" | | 1 | "rhythmic" | | 2 | "predator" | | 3 | "scanned" | | 4 | "maw" | | 5 | "footsteps" | | 6 | "echoing" | | 7 | "silence" | | 8 | "scanning" | | 9 | "standard" | | 10 | "chaotic" | | 11 | "raced" | | 12 | "echoed" | | 13 | "vibrated" | | 14 | "pulse" | | 15 | "cacophony" | | 16 | "velvet" |
| |
| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 1 |
|
| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 78 | | matches | (empty) | |
| 69.60% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 3 | | narrationSentences | 78 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 91 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 35 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1064 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 4 | | unquotedAttributions | 0 | | matches | (empty) | |
| 66.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 19 | | wordCount | 887 | | uniqueNames | 7 | | maxNameDensity | 1.47 | | worstName | "Quinn" | | maxWindowNameDensity | 3 | | worstWindowName | "Quinn" | | discoveredNames | | Tube | 1 | | Latin | 1 | | London | 1 | | Underground | 1 | | Saint | 1 | | Christopher | 1 | | Quinn | 13 |
| | persons | | 0 | "Saint" | | 1 | "Christopher" | | 2 | "Quinn" |
| | places | | | globalScore | 0.767 | | windowScore | 0.667 | |
| 27.05% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 61 | | glossingSentenceCount | 3 | | matches | | 0 | "looked like a standard station, but the s" | | 1 | "something that seemed to writhe when she looked at it directly" | | 2 | "looked like oversized insects whispered s" |
| |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1064 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 91 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 44 | | mean | 24.18 | | std | 18.16 | | cv | 0.751 | | sampleLengths | | 0 | 2 | | 1 | 10 | | 2 | 61 | | 3 | 27 | | 4 | 48 | | 5 | 3 | | 6 | 28 | | 7 | 60 | | 8 | 2 | | 9 | 58 | | 10 | 48 | | 11 | 49 | | 12 | 7 | | 13 | 21 | | 14 | 18 | | 15 | 18 | | 16 | 38 | | 17 | 7 | | 18 | 5 | | 19 | 3 | | 20 | 12 | | 21 | 13 | | 22 | 15 | | 23 | 19 | | 24 | 26 | | 25 | 15 | | 26 | 4 | | 27 | 60 | | 28 | 3 | | 29 | 18 | | 30 | 24 | | 31 | 35 | | 32 | 16 | | 33 | 16 | | 34 | 21 | | 35 | 6 | | 36 | 53 | | 37 | 18 | | 38 | 37 | | 39 | 53 | | 40 | 21 | | 41 | 10 | | 42 | 40 | | 43 | 16 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 78 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 146 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 91 | | ratio | 0 | | matches | (empty) | |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 890 | | adjectiveStacks | 1 | | stackExamples | | 0 | "genuine, belly-deep sound." |
| | adverbCount | 15 | | adverbRatio | 0.016853932584269662 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.0056179775280898875 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 91 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 91 | | mean | 11.69 | | std | 7 | | cv | 0.599 | | sampleLengths | | 0 | 2 | | 1 | 10 | | 2 | 13 | | 3 | 14 | | 4 | 4 | | 5 | 12 | | 6 | 18 | | 7 | 4 | | 8 | 12 | | 9 | 11 | | 10 | 5 | | 11 | 19 | | 12 | 10 | | 13 | 14 | | 14 | 3 | | 15 | 6 | | 16 | 22 | | 17 | 4 | | 18 | 14 | | 19 | 4 | | 20 | 21 | | 21 | 17 | | 22 | 2 | | 23 | 6 | | 24 | 25 | | 25 | 13 | | 26 | 14 | | 27 | 14 | | 28 | 11 | | 29 | 23 | | 30 | 6 | | 31 | 22 | | 32 | 21 | | 33 | 4 | | 34 | 3 | | 35 | 14 | | 36 | 6 | | 37 | 1 | | 38 | 5 | | 39 | 2 | | 40 | 2 | | 41 | 9 | | 42 | 10 | | 43 | 8 | | 44 | 7 | | 45 | 17 | | 46 | 14 | | 47 | 7 | | 48 | 5 | | 49 | 3 |
| |
| 45.05% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 9 | | diversityRatio | 0.32967032967032966 | | totalSentences | 91 | | uniqueOpeners | 30 | |
| 45.05% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 74 | | matches | | 0 | "Just a narrow opening shaped" |
| | ratio | 0.014 | |
| 57.84% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 30 | | totalSentences | 74 | | matches | | 0 | "He leaped over a pile" | | 1 | "She shifted her weight, muscles" | | 2 | "Her lungs burned, but her" | | 3 | "His eyes widened, reflecting the" | | 4 | "He veered right, diving into" | | 5 | "Her worn leather watch slapped" | | 6 | "He twisted, a violent, jagged" | | 7 | "She hit the brick wall" | | 8 | "He didn't wait for a" | | 9 | "He sprinted toward a rusted" | | 10 | "She landed on the other" | | 11 | "She scanned the area." | | 12 | "She kept her hand near" | | 13 | "It looked like a standard" | | 14 | "He reached a heavy oak" | | 15 | "He reached into his pocket," | | 16 | "He slipped inside." | | 17 | "She grabbed the handle and" | | 18 | "She stared at the slot." | | 19 | "He wore a faded blue" |
| | ratio | 0.405 | |
| 0.54% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 68 | | totalSentences | 74 | | matches | | 0 | "Quinn's voice cracked like a" | | 1 | "The suspect, a wiry man" | | 2 | "He leaped over a pile" | | 3 | "Quinn didn't scream again." | | 4 | "She shifted her weight, muscles" | | 5 | "Her lungs burned, but her" | | 6 | "The man glanced back." | | 7 | "His eyes widened, reflecting the" | | 8 | "He veered right, diving into" | | 9 | "Quinn skidded around the corner." | | 10 | "Her worn leather watch slapped" | | 11 | "He twisted, a violent, jagged" | | 12 | "She hit the brick wall" | | 13 | "He didn't wait for a" | | 14 | "He sprinted toward a rusted" | | 15 | "Quinn climbed the fence." | | 16 | "She landed on the other" | | 17 | "She scanned the area." | | 18 | "The man had disappeared down" | | 19 | "The air changed as she" |
| | ratio | 0.919 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 74 | | matches | (empty) | | ratio | 0 | |
| 51.67% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 47 | | technicalSentenceCount | 6 | | matches | | 0 | "He leaped over a pile of rotting crates, his boots splashing through oily puddles." | | 1 | "Her lungs burned, but her stride remained rhythmic, a predator's pace that closed the gap with every heartbeat." | | 2 | "He wore a faded blue cotton shirt and a Saint Christopher medallion that caught the dim light." | | 3 | "Creatures that looked like oversized insects whispered secrets into the ears of hooded humans." | | 4 | "The noise was a cacophony of a dozen different languages, a low hum that vibrated in her chest." | | 5 | "It didn't speak, but a voice exploded inside Quinn's skull, a thunderous roar that knocked her to her knees." |
| |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 1 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |