| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 6 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 10 | | tagDensity | 0.6 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 77.45% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 887 | | totalAiIsmAdverbs | 4 | | found | | | highlights | | 0 | "suddenly" | | 1 | "sharply" | | 2 | "nervously" | | 3 | "slowly" |
| |
| 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) | |
| 26.72% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 887 | | totalAiIsms | 13 | | found | | 0 | | | 1 | | | 2 | | word | "down her spine" | | count | 2 |
| | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | |
| | highlights | | 0 | "flickered" | | 1 | "chill" | | 2 | "down her spine" | | 3 | "footsteps" | | 4 | "echoing" | | 5 | "scanned" | | 6 | "intricate" | | 7 | "shattered" | | 8 | "glinting" | | 9 | "etched" |
| |
| 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 | 60 | | matches | (empty) | |
| 0.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 6 | | narrationSentences | 60 | | filterMatches | (empty) | | hedgeMatches | | 0 | "seemed to" | | 1 | "tried to" | | 2 | "try to" |
| |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 64 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 29 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 890 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 6 | | unquotedAttributions | 0 | | matches | (empty) | |
| 77.71% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 20 | | wordCount | 830 | | uniqueNames | 7 | | maxNameDensity | 1.45 | | worstName | "Quinn" | | maxWindowNameDensity | 2 | | worstWindowName | "Quinn" | | discoveredNames | | Harlow | 1 | | Quinn | 12 | | Raven | 1 | | Nest | 1 | | Soho | 1 | | Veil | 2 | | Market | 2 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Raven" | | 3 | "Nest" |
| | places | | | globalScore | 0.777 | | windowScore | 1 | |
| 0.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 56 | | glossingSentenceCount | 5 | | matches | | 0 | "felt like a ghost among them, her polic" | | 1 | "looked like preserved animal parts" | | 2 | "looked like human organs floating in jars" | | 3 | "devices that seemed to move on their own" | | 4 | "symbols that seemed to writhe in the flickering light" |
| |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 890 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 64 | | matches | (empty) | |
| 47.73% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 27 | | mean | 32.96 | | std | 10.45 | | cv | 0.317 | | sampleLengths | | 0 | 42 | | 1 | 45 | | 2 | 45 | | 3 | 32 | | 4 | 57 | | 5 | 46 | | 6 | 36 | | 7 | 41 | | 8 | 39 | | 9 | 42 | | 10 | 41 | | 11 | 16 | | 12 | 21 | | 13 | 16 | | 14 | 33 | | 15 | 39 | | 16 | 32 | | 17 | 13 | | 18 | 30 | | 19 | 25 | | 20 | 21 | | 21 | 28 | | 22 | 20 | | 23 | 33 | | 24 | 34 | | 25 | 33 | | 26 | 30 |
| |
| 99.42% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 60 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 156 | | matches | | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 5 | | semicolonCount | 0 | | flaggedSentences | 5 | | totalSentences | 64 | | ratio | 0.078 | | matches | | 0 | "She knew this part of town well - too well." | | 1 | "The air grew thick with the smell of damp earth and something else - something that made her skin crawl." | | 2 | "There - a flash of black hoodie disappearing behind a stall selling what looked like preserved animal parts." | | 3 | "And then she saw him - the man in the hoodie, standing before a stall draped in black cloth." | | 4 | "But this one was different - etched with strange symbols that seemed to writhe in the flickering light." |
| |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 827 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 28 | | adverbRatio | 0.03385731559854897 | | lyAdverbCount | 7 | | lyAdverbRatio | 0.008464328899637243 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 64 | | echoCount | 0 | | echoWords | (empty) | |
| 85.67% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 64 | | mean | 13.91 | | std | 5.06 | | cv | 0.364 | | sampleLengths | | 0 | 22 | | 1 | 20 | | 2 | 18 | | 3 | 15 | | 4 | 12 | | 5 | 11 | | 6 | 12 | | 7 | 22 | | 8 | 16 | | 9 | 16 | | 10 | 18 | | 11 | 11 | | 12 | 10 | | 13 | 18 | | 14 | 17 | | 15 | 11 | | 16 | 18 | | 17 | 16 | | 18 | 20 | | 19 | 25 | | 20 | 3 | | 21 | 13 | | 22 | 23 | | 23 | 16 | | 24 | 11 | | 25 | 18 | | 26 | 13 | | 27 | 12 | | 28 | 29 | | 29 | 12 | | 30 | 4 | | 31 | 14 | | 32 | 7 | | 33 | 4 | | 34 | 12 | | 35 | 13 | | 36 | 12 | | 37 | 8 | | 38 | 14 | | 39 | 13 | | 40 | 12 | | 41 | 19 | | 42 | 13 | | 43 | 6 | | 44 | 7 | | 45 | 13 | | 46 | 17 | | 47 | 13 | | 48 | 12 | | 49 | 7 |
| |
| 65.63% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 3 | | diversityRatio | 0.421875 | | totalSentences | 64 | | uniqueOpeners | 27 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 59 | | matches | | 0 | "Suddenly, the man in the" | | 1 | "Then, with a sudden movement," |
| | ratio | 0.034 | |
| 70.85% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 22 | | totalSentences | 59 | | matches | | 0 | "She'd been tailing her suspect" | | 1 | "Her hand instinctively went to" | | 2 | "she muttered, picking up her" | | 3 | "She'd spent 18 years on" | | 4 | "he shouted, but she was" | | 5 | "She knew this part of" | | 6 | "It was a place where" | | 7 | "She hesitated for only a" | | 8 | "She'd heard whispers of it" | | 9 | "She scanned the crowd, searching" | | 10 | "She spun around, ready to" | | 11 | "he said, his voice low" | | 12 | "She took a deep breath," | | 13 | "She'd come too far to" | | 14 | "he said, his voice distorted" | | 15 | "It shattered, releasing a cloud" | | 16 | "She cursed under her breath," | | 17 | "She'd lost him, but she" | | 18 | "She'd find out what he" | | 19 | "She bent down and picked" |
| | ratio | 0.373 | |
| 87.12% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 44 | | totalSentences | 59 | | matches | | 0 | "Detective Harlow Quinn's breath came" | | 1 | "The neon glow of the" | | 2 | "She'd been tailing her suspect" | | 3 | "Her hand instinctively went to" | | 4 | "she muttered, picking up her" | | 5 | "The man in the black" | | 6 | "She'd spent 18 years on" | | 7 | "he shouted, but she was" | | 8 | "The chase led them deeper" | | 9 | "Quinn's heart pounded in her" | | 10 | "She knew this part of" | | 11 | "It was a place where" | | 12 | "Quinn skidded to a halt," | | 13 | "A chill ran down her" | | 14 | "She hesitated for only a" | | 15 | "The air grew thick with" | | 16 | "The Veil Market." | | 17 | "She'd heard whispers of it" | | 18 | "People of all shapes and" | | 19 | "Quinn felt like a ghost" |
| | ratio | 0.746 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 59 | | matches | (empty) | | ratio | 0 | |
| 49.69% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 46 | | technicalSentenceCount | 6 | | matches | | 0 | "She hesitated for only a moment before plunging downward, her footsteps echoing off the concrete walls." | | 1 | "The air grew thick with the smell of damp earth and something else - something that made her skin crawl." | | 2 | "People of all shapes and sizes milled about, their eyes darting nervously as they haggled over strange objects and vials of glowing liquid." | | 3 | "Another displayed intricate clockwork devices that seemed to move on their own." | | 4 | "It shattered, releasing a cloud of shimmering dust that filled the air." | | 5 | "But this one was different - etched with strange symbols that seemed to writhe in the flickering light." |
| |
| 41.67% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 6 | | uselessAdditionCount | 1 | | matches | | 0 | "he said, his voice low and dangerous" |
| |
| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 6 | | fancyCount | 4 | | fancyTags | | 0 | "she muttered (mutter)" | | 1 | "he shouted (shout)" | | 2 | "she growled (growl)" | | 3 | "Quinn shouted (shout)" |
| | dialogueSentences | 10 | | tagDensity | 0.6 | | leniency | 1 | | rawRatio | 0.667 | | effectiveRatio | 0.667 | |