| 69.57% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 10 | | adverbTagCount | 3 | | adverbTags | | 0 | "She advanced slowly [slowly]" | | 1 | "She burst back [back]" | | 2 | "He peered back [back]" |
| | dialogueSentences | 46 | | tagDensity | 0.217 | | leniency | 0.435 | | rawRatio | 0.3 | | effectiveRatio | 0.13 | |
| 86.23% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1452 | | totalAiIsmAdverbs | 4 | | found | | 0 | | | 1 | | adverb | "reluctantly" | | count | 1 |
| | 2 | | | 3 | |
| | highlights | | 0 | "cautiously" | | 1 | "reluctantly" | | 2 | "slowly" | | 3 | "carefully" |
| |
| 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) | |
| 58.68% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1452 | | totalAiIsms | 12 | | found | | | highlights | | 0 | "echoed" | | 1 | "electric" | | 2 | "hulking" | | 3 | "footsteps" | | 4 | "raced" | | 5 | "shimmered" | | 6 | "shattered" | | 7 | "gleaming" |
| |
| 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 | "air was thick with" | | count | 1 |
|
| | highlights | | 0 | "eyes widened" | | 1 | "The air was thick with" |
| |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 130 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 130 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 164 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 27 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1432 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 6 | | unquotedAttributions | 0 | | matches | (empty) | |
| 97.64% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 32 | | wordCount | 1146 | | uniqueNames | 15 | | maxNameDensity | 1.05 | | worstName | "Quinn" | | maxWindowNameDensity | 2 | | worstWindowName | "Quinn" | | discoveredNames | | London | 1 | | Harlow | 1 | | Quinn | 12 | | Raven | 1 | | Nest | 1 | | Camden | 2 | | Morris | 4 | | Tube | 1 | | Veil | 1 | | Market | 1 | | Chaos | 1 | | Saint | 1 | | Christopher | 1 | | Spanish | 1 | | Tomás | 3 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Raven" | | 3 | "Morris" | | 4 | "Chaos" | | 5 | "Saint" | | 6 | "Christopher" | | 7 | "Tomás" |
| | places | | | globalScore | 0.976 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 85 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1432 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 164 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 69 | | mean | 20.75 | | std | 16.13 | | cv | 0.777 | | sampleLengths | | 0 | 70 | | 1 | 63 | | 2 | 59 | | 3 | 29 | | 4 | 37 | | 5 | 8 | | 6 | 35 | | 7 | 10 | | 8 | 16 | | 9 | 6 | | 10 | 27 | | 11 | 4 | | 12 | 9 | | 13 | 7 | | 14 | 69 | | 15 | 3 | | 16 | 23 | | 17 | 40 | | 18 | 39 | | 19 | 16 | | 20 | 27 | | 21 | 39 | | 22 | 29 | | 23 | 4 | | 24 | 25 | | 25 | 16 | | 26 | 5 | | 27 | 3 | | 28 | 21 | | 29 | 1 | | 30 | 17 | | 31 | 26 | | 32 | 10 | | 33 | 19 | | 34 | 5 | | 35 | 5 | | 36 | 35 | | 37 | 7 | | 38 | 22 | | 39 | 20 | | 40 | 6 | | 41 | 21 | | 42 | 2 | | 43 | 26 | | 44 | 4 | | 45 | 15 | | 46 | 22 | | 47 | 42 | | 48 | 8 | | 49 | 36 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 130 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 205 | | matches | | 0 | "was leading" | | 1 | "was telling" |
| |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 12 | | semicolonCount | 1 | | flaggedSentences | 11 | | totalSentences | 164 | | ratio | 0.067 | | matches | | 0 | "Ahead, a figure darted around a corner into an alleyway—slick black coat, hunched shoulders, moving with the desperate speed of prey." | | 1 | "Then movement—a flash of dark fabric slipping through a half-open metal door set into the pavement, like a maintenance hatch leading underground." | | 2 | "The air carried a strange mix of odors—ozone, wet earth, something metallic and sharp." | | 3 | "By then, the suspect—and whatever this place was—would be gone." | | 4 | "They descended into a wide, vaulted space—an abandoned Tube station, she realized." | | 5 | "Faces turned toward her—some curious, some hostile." | | 6 | "A sound echoed from the darkness behind him—soft footfalls, multiple." | | 7 | "One of the figures moved—a blur of motion—and caught him by the collar, lifting him off his feet." | | 8 | "Quinn fired—a deafening crack in the confined space." | | 9 | "The leader flinched but didn’t fall; something shimmered around him, like heat haze." | | 10 | "He pulled her sideways, into a gap between two stalls, through a heavy curtain into a small, cluttered space—a makeshift medical station." |
| |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1164 | | adjectiveStacks | 1 | | stackExamples | | 0 | "short curly dark hair." |
| | adverbCount | 24 | | adverbRatio | 0.020618556701030927 | | lyAdverbCount | 9 | | lyAdverbRatio | 0.007731958762886598 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 164 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 164 | | mean | 8.73 | | std | 5.32 | | cv | 0.609 | | sampleLengths | | 0 | 22 | | 1 | 27 | | 2 | 21 | | 3 | 24 | | 4 | 17 | | 5 | 22 | | 6 | 6 | | 7 | 13 | | 8 | 11 | | 9 | 12 | | 10 | 13 | | 11 | 4 | | 12 | 22 | | 13 | 7 | | 14 | 3 | | 15 | 9 | | 16 | 14 | | 17 | 11 | | 18 | 5 | | 19 | 3 | | 20 | 8 | | 21 | 12 | | 22 | 11 | | 23 | 4 | | 24 | 3 | | 25 | 7 | | 26 | 9 | | 27 | 7 | | 28 | 6 | | 29 | 5 | | 30 | 10 | | 31 | 11 | | 32 | 1 | | 33 | 4 | | 34 | 6 | | 35 | 3 | | 36 | 7 | | 37 | 9 | | 38 | 12 | | 39 | 15 | | 40 | 12 | | 41 | 21 | | 42 | 3 | | 43 | 3 | | 44 | 10 | | 45 | 10 | | 46 | 10 | | 47 | 11 | | 48 | 19 | | 49 | 3 |
| |
| 59.55% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 9 | | diversityRatio | 0.3902439024390244 | | totalSentences | 164 | | uniqueOpeners | 64 | |
| 26.67% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 125 | | matches | | 0 | "Then movement—a flash of dark" |
| | ratio | 0.008 | |
| 72.80% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 46 | | totalSentences | 125 | | matches | | 0 | "She’d been tailing him for" | | 1 | "He’d bolted the moment he’d" | | 2 | "Her shoes slapped against wet" | | 3 | "He vaulted it, coat flapping," | | 4 | "It felt wrong." | | 5 | "She thought of DS Morris," | | 6 | "Her radio crackled." | | 7 | "She thumbed the button, rain" | | 8 | "She knew the drill: wait," | | 9 | "she said, her voice flat" | | 10 | "She clicked off before they" | | 11 | "They descended into a wide," | | 12 | "She’d heard whispers." | | 13 | "Her suspect was thirty feet" | | 14 | "He glanced back, saw her," | | 15 | "He shoved past a hulking" | | 16 | "His smile revealed pointed teeth." | | 17 | "She ignored him, keeping her" | | 18 | "He ducked under a low" | | 19 | "He went down hard, sliding" |
| | ratio | 0.368 | |
| 24.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 109 | | totalSentences | 125 | | matches | | 0 | "The rain came down in" | | 1 | "Detective Harlow Quinn’s breath fogged" | | 2 | "She’d been tailing him for" | | 3 | "He’d bolted the moment he’d" | | 4 | "Her shoes slapped against wet" | | 5 | "The alley dead-ended at a" | | 6 | "He vaulted it, coat flapping," | | 7 | "Quinn followed, hauling herself over," | | 8 | "Light glowed from below, a" | | 9 | "Quinn approached cautiously." | | 10 | "Rainwater streamed down the steps" | | 11 | "The air carried a strange" | | 12 | "Voices echoed up, muffled, layered" | | 13 | "This wasn’t on any map." | | 14 | "It felt wrong." | | 15 | "She thought of DS Morris," | | 16 | "The case file that made" | | 17 | "The quiet dread that had" | | 18 | "This smelled like that." | | 19 | "Her radio crackled." |
| | ratio | 0.872 | |
| 40.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 125 | | matches | | 0 | "Now he was leading her" |
| | ratio | 0.008 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 50 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 10 | | uselessAdditionCount | 3 | | matches | | 0 | "she said, her voice flat" | | 1 | "She advanced slowly, carefully" | | 2 | "He turned, his expression serious" |
| |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 2 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 46 | | tagDensity | 0.043 | | leniency | 0.087 | | rawRatio | 0 | | effectiveRatio | 0 | |