| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 17 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 31 | | tagDensity | 0.548 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 932 | | 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) | |
| 0.00% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 932 | | totalAiIsms | 22 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | | word | "down her spine" | | count | 1 |
| | 13 | | word | "sent shivers down" | | count | 1 |
| | 14 | | | 15 | |
| | highlights | | 0 | "scanning" | | 1 | "flickered" | | 2 | "raced" | | 3 | "echoed" | | 4 | "pulse" | | 5 | "echoing" | | 6 | "footsteps" | | 7 | "quickened" | | 8 | "racing" | | 9 | "could feel" | | 10 | "stomach" | | 11 | "chill" | | 12 | "down her spine" | | 13 | "sent shivers down" | | 14 | "tension" | | 15 | "weight" |
| |
| 33.33% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 3 | | maxInWindow | 3 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 2 |
| | 1 | | label | "stomach dropped/sank" | | count | 1 |
|
| | highlights | | 0 | "eyes narrowed" | | 1 | "stomach dropped" |
| |
| 91.22% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 3 | | narrationSentences | 74 | | matches | | 0 | "t in determination" | | 1 | "e with fear" | | 2 | "felt a chill" |
| |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 74 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 88 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 30 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 928 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 16 | | unquotedAttributions | 0 | | matches | (empty) | |
| 33.72% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 34 | | wordCount | 774 | | uniqueNames | 10 | | maxNameDensity | 2.33 | | worstName | "Quinn" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Quinn" | | discoveredNames | | Soho | 1 | | Harlow | 1 | | Quinn | 18 | | Raven | 1 | | Nest | 1 | | Tomás | 8 | | Herrera | 1 | | Tube | 1 | | Veil | 1 | | Market | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Raven" | | 3 | "Nest" | | 4 | "Tomás" | | 5 | "Herrera" |
| | places | | | globalScore | 0.337 | | windowScore | 0.5 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 57 | | glossingSentenceCount | 1 | | matches | | 0 | "as if searching for an escape" |
| |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 928 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 88 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 43 | | mean | 21.58 | | std | 15.29 | | cv | 0.708 | | sampleLengths | | 0 | 73 | | 1 | 41 | | 2 | 9 | | 3 | 54 | | 4 | 53 | | 5 | 38 | | 6 | 10 | | 7 | 31 | | 8 | 45 | | 9 | 7 | | 10 | 22 | | 11 | 14 | | 12 | 14 | | 13 | 20 | | 14 | 4 | | 15 | 31 | | 16 | 20 | | 17 | 11 | | 18 | 35 | | 19 | 6 | | 20 | 34 | | 21 | 11 | | 22 | 16 | | 23 | 10 | | 24 | 23 | | 25 | 29 | | 26 | 12 | | 27 | 14 | | 28 | 14 | | 29 | 27 | | 30 | 5 | | 31 | 24 | | 32 | 10 | | 33 | 14 | | 34 | 8 | | 35 | 21 | | 36 | 21 | | 37 | 8 | | 38 | 11 | | 39 | 44 | | 40 | 12 | | 41 | 7 | | 42 | 15 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 74 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 147 | | matches | (empty) | |
| 45.45% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 3 | | semicolonCount | 0 | | flaggedSentences | 3 | | totalSentences | 88 | | ratio | 0.034 | | matches | | 0 | "She recognized him—Tomás Herrera, the former paramedic turned underground medic." | | 1 | "The air felt thick, heavy with the scent of wet asphalt and something else—something metallic." | | 2 | "Quinn saw the fear in his expression, but also something else—defiance." |
| |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 778 | | adjectiveStacks | 1 | | stackExamples | | 0 | "former paramedic turned underground medic." |
| | adverbCount | 20 | | adverbRatio | 0.02570694087403599 | | lyAdverbCount | 3 | | lyAdverbRatio | 0.0038560411311053984 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 88 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 88 | | mean | 10.55 | | std | 5.35 | | cv | 0.507 | | sampleLengths | | 0 | 10 | | 1 | 21 | | 2 | 16 | | 3 | 26 | | 4 | 12 | | 5 | 10 | | 6 | 13 | | 7 | 6 | | 8 | 9 | | 9 | 3 | | 10 | 13 | | 11 | 19 | | 12 | 19 | | 13 | 13 | | 14 | 13 | | 15 | 12 | | 16 | 15 | | 17 | 12 | | 18 | 15 | | 19 | 11 | | 20 | 10 | | 21 | 2 | | 22 | 10 | | 23 | 7 | | 24 | 5 | | 25 | 7 | | 26 | 12 | | 27 | 12 | | 28 | 21 | | 29 | 7 | | 30 | 11 | | 31 | 11 | | 32 | 14 | | 33 | 14 | | 34 | 12 | | 35 | 8 | | 36 | 4 | | 37 | 17 | | 38 | 4 | | 39 | 10 | | 40 | 20 | | 41 | 11 | | 42 | 8 | | 43 | 14 | | 44 | 13 | | 45 | 6 | | 46 | 11 | | 47 | 3 | | 48 | 20 | | 49 | 11 |
| |
| 49.62% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 3 | | diversityRatio | 0.3181818181818182 | | totalSentences | 88 | | uniqueOpeners | 28 | |
| 91.32% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 73 | | matches | | 0 | "Instead, he sprinted down the" | | 1 | "Just the sound of her" |
| | ratio | 0.027 | |
| 33.70% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 34 | | totalSentences | 73 | | matches | | 0 | "She peered around the corner," | | 1 | "She recognized him—Tomás Herrera, the" | | 2 | "He had been a ghost" | | 3 | "she shouted, her voice cutting" | | 4 | "He didn’t stop." | | 5 | "She could see him glancing" | | 6 | "He ducked into a narrow" | | 7 | "She plunged into the passage," | | 8 | "she called, her voice echoing" | | 9 | "She quickened her pace, her" | | 10 | "He had to be close." | | 11 | "She could feel it in" | | 12 | "she shouted, her voice firm" | | 13 | "He turned, eyes wide, and" | | 14 | "he said, his voice low," | | 15 | "she shot back, stepping closer" | | 16 | "He shook his head, glancing" | | 17 | "She glanced around, noting the" | | 18 | "she urged, but he hesitated," | | 19 | "he whispered, his voice barely" |
| | ratio | 0.466 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 69 | | totalSentences | 73 | | matches | | 0 | "The rain fell in sheets," | | 1 | "Detective Harlow Quinn pressed her" | | 2 | "She peered around the corner," | | 3 | "The neon glow of The" | | 4 | "A figure darted past, a" | | 5 | "She recognized him—Tomás Herrera, the" | | 6 | "He had been a ghost" | | 7 | "Tonight, he was her only" | | 8 | "she shouted, her voice cutting" | | 9 | "He didn’t stop." | | 10 | "Quinn pushed off the wall," | | 11 | "The sound of her boots" | | 12 | "Tomás rounded a corner, and" | | 13 | "She could see him glancing" | | 14 | "He ducked into a narrow" | | 15 | "The alley was dark, the" | | 16 | "She plunged into the passage," | | 17 | "The air felt thick, heavy" | | 18 | "Quinn pressed on, her instincts" | | 19 | "she called, her voice echoing" |
| | ratio | 0.945 | |
| 68.49% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 73 | | matches | | 0 | "Before he could respond, a" |
| | ratio | 0.014 | |
| 89.29% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 40 | | technicalSentenceCount | 3 | | matches | | 0 | "The neon glow of The Raven's Nest flickered in the distance, casting an eerie light on the puddles that formed like small mirrors on the ground." | | 1 | "The sound of her boots splashing through puddles echoed in the night, a relentless rhythm that matched her pulse." | | 2 | "He shook his head, glancing around as if searching for an escape." |
| |
| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 17 | | uselessAdditionCount | 11 | | matches | | 0 | "she shouted, her voice cutting through the rain" | | 1 | "she called, her voice echoing off the damp walls" | | 2 | "she shouted, her voice firm" | | 3 | "he said, his voice low, almost pleading" | | 4 | "he whispered, his voice barely audible over the rain" | | 5 | "she warned, her voice low" | | 6 | "Quinn snapped, her patience fraying" | | 7 | "she pressed, frustration bubbling to the surface" | | 8 | "she shot back, her voice steady" | | 9 | "she demanded, her voice firm" | | 10 | "Tomás said, his voice urgent" |
| |
| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 14 | | fancyCount | 10 | | fancyTags | | 0 | "she shouted (shout)" | | 1 | "she shouted (shout)" | | 2 | "she urged (urge)" | | 3 | "he whispered (whisper)" | | 4 | "she warned (warn)" | | 5 | "Quinn snapped (snap)" | | 6 | "she insisted (insist)" | | 7 | "she pressed (press)" | | 8 | "she snapped (snap)" | | 9 | "she demanded (demand)" |
| | dialogueSentences | 31 | | tagDensity | 0.452 | | leniency | 0.903 | | rawRatio | 0.714 | | effectiveRatio | 0.645 | |