| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 16 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 39 | | tagDensity | 0.41 | | leniency | 0.821 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1171 | | 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) | |
| 23.14% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1171 | | totalAiIsms | 18 | | found | | | highlights | | 0 | "gloom" | | 1 | "porcelain" | | 2 | "shattered" | | 3 | "etched" | | 4 | "velvet" | | 5 | "pulse" | | 6 | "stark" | | 7 | "traced" | | 8 | "scanned" | | 9 | "echoed" | | 10 | "jaw clenched" | | 11 | "glint" | | 12 | "echo" | | 13 | "silence" |
| |
| 66.67% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 2 | | maxInWindow | 2 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 1 |
| | 1 | | label | "jaw/fists clenched" | | count | 1 |
|
| | highlights | | 0 | "eyes narrowed" | | 1 | "jaw clenched" |
| |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 169 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 3 | | hedgeCount | 1 | | narrationSentences | 169 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 191 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 25 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1159 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 7 | | unquotedAttributions | 0 | | matches | (empty) | |
| 25.94% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 60 | | wordCount | 927 | | uniqueNames | 18 | | maxNameDensity | 2.48 | | worstName | "Quinn" | | maxWindowNameDensity | 4 | | worstWindowName | "Quinn" | | discoveredNames | | Harlow | 1 | | Quinn | 23 | | Veil | 1 | | Market | 1 | | Kowalski | 1 | | Limp | 1 | | Museum | 1 | | Tick | 1 | | Evidence | 1 | | Tube | 1 | | Blitz | 1 | | Nikes | 1 | | Ink | 1 | | Morris | 2 | | Eva | 19 | | Academic | 1 | | Four | 1 | | Compass | 2 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Kowalski" | | 3 | "Museum" | | 4 | "Ink" | | 5 | "Morris" | | 6 | "Eva" | | 7 | "Compass" |
| | places | (empty) | | globalScore | 0.259 | | windowScore | 0.333 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 62 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.863 | | wordCount | 1159 | | matches | | 0 | "not north, but quivering towards the body's chest" |
| |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 191 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 63 | | mean | 18.4 | | std | 12.7 | | cv | 0.69 | | sampleLengths | | 0 | 44 | | 1 | 53 | | 2 | 3 | | 3 | 41 | | 4 | 42 | | 5 | 11 | | 6 | 32 | | 7 | 22 | | 8 | 33 | | 9 | 8 | | 10 | 30 | | 11 | 26 | | 12 | 48 | | 13 | 16 | | 14 | 11 | | 15 | 15 | | 16 | 25 | | 17 | 34 | | 18 | 11 | | 19 | 16 | | 20 | 19 | | 21 | 21 | | 22 | 52 | | 23 | 33 | | 24 | 33 | | 25 | 12 | | 26 | 22 | | 27 | 9 | | 28 | 9 | | 29 | 14 | | 30 | 23 | | 31 | 15 | | 32 | 13 | | 33 | 32 | | 34 | 13 | | 35 | 5 | | 36 | 6 | | 37 | 19 | | 38 | 19 | | 39 | 12 | | 40 | 25 | | 41 | 7 | | 42 | 10 | | 43 | 5 | | 44 | 8 | | 45 | 22 | | 46 | 16 | | 47 | 2 | | 48 | 6 | | 49 | 8 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 169 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 197 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 191 | | ratio | 0 | | matches | (empty) | |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 937 | | adjectiveStacks | 1 | | stackExamples | | 0 | "Chalk-white, still smoking." |
| | adverbCount | 21 | | adverbRatio | 0.022411953041622197 | | lyAdverbCount | 2 | | lyAdverbRatio | 0.0021344717182497333 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 191 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 191 | | mean | 6.07 | | std | 4.4 | | cv | 0.725 | | sampleLengths | | 0 | 16 | | 1 | 17 | | 2 | 4 | | 3 | 1 | | 4 | 6 | | 5 | 16 | | 6 | 11 | | 7 | 3 | | 8 | 18 | | 9 | 5 | | 10 | 3 | | 11 | 12 | | 12 | 16 | | 13 | 13 | | 14 | 9 | | 15 | 15 | | 16 | 12 | | 17 | 3 | | 18 | 3 | | 19 | 6 | | 20 | 1 | | 21 | 4 | | 22 | 12 | | 23 | 20 | | 24 | 22 | | 25 | 4 | | 26 | 4 | | 27 | 10 | | 28 | 3 | | 29 | 4 | | 30 | 8 | | 31 | 8 | | 32 | 6 | | 33 | 24 | | 34 | 2 | | 35 | 8 | | 36 | 14 | | 37 | 1 | | 38 | 1 | | 39 | 6 | | 40 | 11 | | 41 | 11 | | 42 | 2 | | 43 | 3 | | 44 | 7 | | 45 | 6 | | 46 | 2 | | 47 | 6 | | 48 | 2 | | 49 | 8 |
| |
| 97.56% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 2 | | diversityRatio | 0.5916230366492147 | | totalSentences | 191 | | uniqueOpeners | 113 | |
| 26.25% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 127 | | matches | | 0 | "Then she nodded, slipping behind" |
| | ratio | 0.008 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 20 | | totalSentences | 127 | | matches | | 0 | "Her torch beam sliced across" | | 1 | "She straightened, worn leather watch" | | 2 | "She'd chased whispers of this" | | 3 | "Her worn leather satchel slumped" | | 4 | "She traced a gloved finger" | | 5 | "She scanned the body." | | 6 | "She rocked back on her" | | 7 | "She rose, torch sweeping the" | | 8 | "She pried open the man's" | | 9 | "Her gloved fingers brushed his" | | 10 | "She withdrew a small brass" | | 11 | "She pocketed it" | | 12 | "She followed, ducking low." | | 13 | "She jabbed the body" | | 14 | "She strode back, Eva trailing." | | 15 | "Her nose wrinkled." | | 16 | "She knelt, sifting debris." | | 17 | "She rapped knuckles." | | 18 | "She pocketed compass" | | 19 | "She wedged boot in a" |
| | ratio | 0.157 | |
| 74.17% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 98 | | totalSentences | 127 | | matches | | 0 | "Detective Harlow Quinn gripped the" | | 1 | "Her torch beam sliced across" | | 2 | "Copper flooded her nostrils." | | 3 | "She straightened, worn leather watch" | | 4 | "Military boots crunched over shattered" | | 5 | "The Veil Market." | | 6 | "She'd chased whispers of this" | | 7 | "Eva Kowalski crouched beside a" | | 8 | "Her worn leather satchel slumped" | | 9 | "Quinn holstered her torch and" | | 10 | "The victim, a wiry man" | | 11 | "Pulse points cold." | | 12 | "Quinn prodded his arm" | | 13 | "Rigor just setting in." | | 14 | "Eva nodded, freckles stark under" | | 15 | "She traced a gloved finger" | | 16 | "Quinn's brown eyes narrowed." | | 17 | "She scanned the body." | | 18 | "Fingers splayed unnatural, nails split" | | 19 | "She rocked back on her" |
| | ratio | 0.772 | |
| 39.37% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 127 | | matches | | 0 | "Now it reeked of death." |
| | ratio | 0.008 | |
| 91.84% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 28 | | technicalSentenceCount | 2 | | matches | | 0 | "Military boots crunched over shattered vials that tinkled like wind chimes." | | 1 | "Sheer drop, wind howling up cold fingers that plucked her cropped hair." |
| |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 16 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 98.72% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 2 | | fancyCount | 2 | | fancyTags | | 0 | "Eva murmured (murmur)" | | 1 | "Quinn breathed (breathe)" |
| | dialogueSentences | 39 | | tagDensity | 0.051 | | leniency | 0.103 | | rawRatio | 1 | | effectiveRatio | 0.103 | |