| 76.54% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 31 | | adverbTagCount | 5 | | adverbTags | | 0 | "I glanced around [around]" | | 1 | "she asked suddenly [suddenly]" | | 2 | "she said softly [softly]" | | 3 | "she said quietly [quietly]" | | 4 | "I said slowly [slowly]" |
| | dialogueSentences | 81 | | tagDensity | 0.383 | | leniency | 0.765 | | rawRatio | 0.161 | | effectiveRatio | 0.123 | |
| 85.92% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1776 | | totalAiIsmAdverbs | 5 | | found | | | highlights | | 0 | "perfectly" | | 1 | "suddenly" | | 2 | "softly" | | 3 | "slowly" |
| |
| 80.00% | AI-ism character names | Target: 0 AI-default names (16 tracked, −20% each) | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 60.59% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1776 | | totalAiIsms | 14 | | found | | | highlights | | 0 | "familiar" | | 1 | "flicker" | | 2 | "weight" | | 3 | "silence" | | 4 | "stomach" | | 5 | "whisper" | | 6 | "could feel" | | 7 | "pulse" | | 8 | "eyebrow" | | 9 | "racing" | | 10 | "trembled" |
| |
| 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 | 1 | | narrationSentences | 93 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 2 | | narrationSentences | 93 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 141 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 38 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1766 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 22 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 19 | | wordCount | 1083 | | uniqueNames | 13 | | maxNameDensity | 0.55 | | worstName | "Eva" | | maxWindowNameDensity | 1 | | worstWindowName | "Eva" | | discoveredNames | | Yu-Fei | 1 | | Raven | 1 | | Nest | 1 | | Ellis | 1 | | Cardiff | 2 | | Evan | 1 | | Didn | 1 | | Greenwich | 1 | | London | 1 | | Malphora | 1 | | Eva | 6 | | Evelyn | 1 | | Marshall | 1 |
| | persons | | 0 | "Yu-Fei" | | 1 | "Raven" | | 2 | "Nest" | | 3 | "Ellis" | | 4 | "Evan" | | 5 | "Eva" | | 6 | "Evelyn" | | 7 | "Marshall" |
| | places | | 0 | "Cardiff" | | 1 | "Greenwich" | | 2 | "London" |
| | globalScore | 1 | | windowScore | 1 | |
| 36.36% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 66 | | glossingSentenceCount | 3 | | matches | | 0 | "looked like she'd stepped out of one of t" | | 1 | "looked like a business suit, and her hand" | | 2 | "someone who'd apparently been hiding from he" |
| |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1766 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 2 | | totalSentences | 141 | | matches | | 0 | "knew that gait" | | 1 | "Knew that way" |
| |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 72 | | mean | 24.53 | | std | 17.46 | | cv | 0.712 | | sampleLengths | | 0 | 82 | | 1 | 1 | | 2 | 15 | | 3 | 38 | | 4 | 36 | | 5 | 73 | | 6 | 20 | | 7 | 32 | | 8 | 29 | | 9 | 39 | | 10 | 2 | | 11 | 15 | | 12 | 3 | | 13 | 3 | | 14 | 22 | | 15 | 22 | | 16 | 28 | | 17 | 38 | | 18 | 24 | | 19 | 15 | | 20 | 29 | | 21 | 24 | | 22 | 3 | | 23 | 28 | | 24 | 41 | | 25 | 9 | | 26 | 44 | | 27 | 40 | | 28 | 33 | | 29 | 6 | | 30 | 36 | | 31 | 20 | | 32 | 3 | | 33 | 20 | | 34 | 58 | | 35 | 40 | | 36 | 9 | | 37 | 32 | | 38 | 13 | | 39 | 33 | | 40 | 22 | | 41 | 31 | | 42 | 4 | | 43 | 49 | | 44 | 26 | | 45 | 6 | | 46 | 20 | | 47 | 3 | | 48 | 23 | | 49 | 22 |
| |
| 93.94% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 93 | | matches | | 0 | "were dulled" | | 1 | "were clenched" | | 2 | "was cracked" |
| |
| 29.06% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 5 | | totalVerbs | 195 | | matches | | 0 | "was holding" | | 1 | "was listening" | | 2 | "was pulling" | | 3 | "wasn't resisting" | | 4 | "was racing" |
| |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 11 | | semicolonCount | 0 | | flaggedSentences | 9 | | totalSentences | 141 | | ratio | 0.064 | | matches | | 0 | "The Raven's Nest hummed around me—low conversations, the green neon sign bleeding through the grimy windows, maps of some forgotten conflicts pinned to walls that smelled of old wood and cheaper spirits." | | 1 | "Her eyes—once bright green like spring grass—were dulled now, clouded with something I couldn't name." | | 2 | "The woman at the end of the bar—a regular, maybe forty, with the build of someone who'd spent too many years in too many fights—paused mid-conversation to glance over." | | 3 | "A flicker of something—anger?" | | 4 | "Hurt?—crossed her face before she smoothed it away." | | 5 | "That was the one that had gotten me kicked out of university, suspended from the police academy—before I'd decided that maybe the system was broken and I needed to fix it myself." | | 6 | "On the screen was a photo—a grainy security camera image of someone delivering food to a house in Greenwich." | | 7 | "In the dim light of the hidden room, I finally saw what she'd brought with her—police reports, photographs, a map of London marked with red dots." | | 8 | "Eva pulled out another photo—her and her sister, happy, laughing, taken just before everything went wrong." |
| |
| 92.73% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1097 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 53 | | adverbRatio | 0.04831358249772106 | | lyAdverbCount | 15 | | lyAdverbRatio | 0.013673655423883319 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 141 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 141 | | mean | 12.52 | | std | 8.76 | | cv | 0.7 | | sampleLengths | | 0 | 19 | | 1 | 31 | | 2 | 32 | | 3 | 1 | | 4 | 15 | | 5 | 12 | | 6 | 22 | | 7 | 4 | | 8 | 2 | | 9 | 3 | | 10 | 5 | | 11 | 26 | | 12 | 30 | | 13 | 15 | | 14 | 28 | | 15 | 13 | | 16 | 7 | | 17 | 10 | | 18 | 2 | | 19 | 18 | | 20 | 2 | | 21 | 5 | | 22 | 22 | | 23 | 2 | | 24 | 29 | | 25 | 10 | | 26 | 2 | | 27 | 3 | | 28 | 12 | | 29 | 3 | | 30 | 3 | | 31 | 10 | | 32 | 12 | | 33 | 4 | | 34 | 8 | | 35 | 10 | | 36 | 16 | | 37 | 12 | | 38 | 7 | | 39 | 7 | | 40 | 24 | | 41 | 14 | | 42 | 10 | | 43 | 10 | | 44 | 5 | | 45 | 20 | | 46 | 9 | | 47 | 12 | | 48 | 12 | | 49 | 3 |
| |
| 56.74% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 10 | | diversityRatio | 0.3829787234042553 | | totalSentences | 141 | | uniqueOpeners | 54 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 89 | | matches | | 0 | "Just stood there looking at" | | 1 | "Just two words, but they" | | 2 | "Instead, she pulled out a" |
| | ratio | 0.034 | |
| 0.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 50 | | totalSentences | 89 | | matches | | 0 | "I turned, glass still halfway" | | 1 | "My college friend." | | 2 | "My confidante through university's chaos." | | 3 | "She was taller than I" | | 4 | "Her eyes—once bright green like" | | 5 | "She wore a leather jacket" | | 6 | "I said, setting the glass" | | 7 | "She didn't move past the" | | 8 | "I gestured to myself" | | 9 | "I flexed my wrist, feeling" | | 10 | "My voice came out quieter" | | 11 | "I said, pulling my hands" | | 12 | "She finally stepped further into" | | 13 | "I glanced around the bar" | | 14 | "She leaned against the bar," | | 15 | "I ordered another whiskey without" | | 16 | "I took a long pull" | | 17 | "She didn't answer immediately." | | 18 | "She must have looked at" | | 19 | "she asked suddenly" |
| | ratio | 0.562 | |
| 38.65% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 75 | | totalSentences | 89 | | matches | | 0 | "The whiskey hit my throat" | | 1 | "The Raven's Nest hummed around" | | 2 | "The voice came from somewhere" | | 3 | "I turned, glass still halfway" | | 4 | "My college friend." | | 5 | "My confidante through university's chaos." | | 6 | "The woman who'd helped me" | | 7 | "She was taller than I" | | 8 | "Her eyes—once bright green like" | | 9 | "She wore a leather jacket" | | 10 | "I said, setting the glass" | | 11 | "She didn't move past the" | | 12 | "I gestured to myself" | | 13 | "I flexed my wrist, feeling" | | 14 | "The woman at the end" | | 15 | "Eva nodded at him curtly," | | 16 | "That was it." | | 17 | "My voice came out quieter" | | 18 | "A flicker of something—anger?" | | 19 | "I said, pulling my hands" |
| | ratio | 0.843 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 89 | | matches | (empty) | | ratio | 0 | |
| 0.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 33 | | technicalSentenceCount | 7 | | matches | | 0 | "The Raven's Nest hummed around me—low conversations, the green neon sign bleeding through the grimy windows, maps of some forgotten conflicts pinned to walls th…" | | 1 | "Standing in the doorway was a woman who looked like she'd stepped out of one of the black-and-white photographs decorating the walls." | | 2 | "The woman who'd helped me pack my bags the night I fled Cardiff, who'd driven me through the night to save me from someone named Evan." | | 3 | "She was taller than I remembered, maybe an inch or two, and her dark hair was cut shorter now, brushed back from a face that had seen too much hardship." | | 4 | "The woman at the end of the bar—a regular, maybe forty, with the build of someone who'd spent too many years in too many fights—paused mid-conversation to glanc…" | | 5 | "Knew that way of walking that suggested someone who'd grown up on the streets, who'd learned to move without making noise." | | 6 | "And then she was moving, faster than I'd expected for someone who'd apparently been hiding from her past for five years." |
| |
| 76.61% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 31 | | uselessAdditionCount | 3 | | matches | | 0 | "She looked up, those green eyes searching mine" | | 1 | "She leaned, her voice dropping" | | 2 | "She shoved, my back hitting the cold wood" |
| |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 10 | | fancyCount | 2 | | fancyTags | | 0 | "I ordered (order)" | | 1 | "I breathed (breathe)" |
| | dialogueSentences | 81 | | tagDensity | 0.123 | | leniency | 0.247 | | rawRatio | 0.2 | | effectiveRatio | 0.049 | |