| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 11 | | adverbTagCount | 1 | | adverbTags | | 0 | "Tomás said grimly [grimly]" |
| | dialogueSentences | 27 | | tagDensity | 0.407 | | leniency | 0.815 | | rawRatio | 0.091 | | effectiveRatio | 0.074 | |
| 81.43% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1346 | | totalAiIsmAdverbs | 5 | | found | | | highlights | | 0 | "carefully" | | 1 | "suddenly" | | 2 | "cautiously" | | 3 | "sharply" | | 4 | "nervously" |
| |
| 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) | |
| 66.57% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1346 | | totalAiIsms | 9 | | found | | | highlights | | 0 | "footsteps" | | 1 | "echoing" | | 2 | "scanning" | | 3 | "flicked" | | 4 | "disrupting" | | 5 | "familiar" | | 6 | "echoed" | | 7 | "reminder" |
| |
| 66.67% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 2 | | maxInWindow | 2 | | found | | 0 | | label | "blood ran cold" | | count | 1 |
| | 1 | | label | "air was thick with" | | count | 1 |
|
| | highlights | | 0 | "blood went cold" | | 1 | "The air was thick with" |
| |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 1 | | narrationSentences | 95 | | matches | | |
| 52.63% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 5 | | narrationSentences | 95 | | filterMatches | | | hedgeMatches | | 0 | "appeared to" | | 1 | "seemed to" | | 2 | "happened to" | | 3 | "started to" |
| |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 111 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 34 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1328 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 11 | | unquotedAttributions | 0 | | matches | (empty) | |
| 50.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 47 | | wordCount | 1114 | | uniqueNames | 15 | | maxNameDensity | 1.89 | | worstName | "Quinn" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Quinn" | | discoveredNames | | Charing | 1 | | Cross | 1 | | Road | 1 | | Camden | 2 | | Morris | 4 | | Lock | 1 | | Tube | 2 | | Quinn | 21 | | Veil | 1 | | Market | 1 | | Tomás | 8 | | Herrera | 1 | | Saint | 1 | | Christopher | 1 | | London | 1 |
| | persons | | 0 | "Morris" | | 1 | "Quinn" | | 2 | "Tomás" | | 3 | "Herrera" | | 4 | "Saint" | | 5 | "Christopher" |
| | places | | 0 | "Charing" | | 1 | "Cross" | | 2 | "Road" | | 3 | "Camden" | | 4 | "London" |
| | globalScore | 0.557 | | windowScore | 0.5 | |
| 0.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 80 | | glossingSentenceCount | 5 | | matches | | 0 | "looked like fear, but not the kind she us" | | 1 | "patterns that seemed to shift in her peripheral vision" | | 2 | "looked like genuine regret" | | 3 | "quite add up" | | 4 | "not quite echoed through the chamber" | | 5 | "sounded like gunshots—but not quite—echoed" |
| |
| 49.40% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 2 | | per1kWords | 1.506 | | wordCount | 1328 | | matches | | 0 | "No response but" | | 1 | "Not just one or two, but many" |
| |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 111 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 44 | | mean | 30.18 | | std | 16.49 | | cv | 0.546 | | sampleLengths | | 0 | 55 | | 1 | 48 | | 2 | 24 | | 3 | 55 | | 4 | 55 | | 5 | 42 | | 6 | 39 | | 7 | 41 | | 8 | 36 | | 9 | 14 | | 10 | 9 | | 11 | 56 | | 12 | 38 | | 13 | 63 | | 14 | 51 | | 15 | 36 | | 16 | 61 | | 17 | 46 | | 18 | 30 | | 19 | 25 | | 20 | 5 | | 21 | 28 | | 22 | 16 | | 23 | 13 | | 24 | 13 | | 25 | 22 | | 26 | 29 | | 27 | 51 | | 28 | 5 | | 29 | 9 | | 30 | 9 | | 31 | 39 | | 32 | 14 | | 33 | 18 | | 34 | 15 | | 35 | 28 | | 36 | 17 | | 37 | 28 | | 38 | 37 | | 39 | 14 | | 40 | 13 | | 41 | 32 | | 42 | 33 | | 43 | 16 |
| |
| 86.80% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 5 | | totalSentences | 95 | | matches | | 0 | "was lost" | | 1 | "been connected" | | 2 | "being peddled" | | 3 | "was obscured" | | 4 | "was gone" |
| |
| 0.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 6 | | totalVerbs | 199 | | matches | | 0 | "wasn't running" | | 1 | "was speaking" | | 2 | "was dispersing" | | 3 | "was happening, was disrupting" | | 4 | "was spreading" |
| |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 14 | | semicolonCount | 0 | | flaggedSentences | 11 | | totalSentences | 111 | | ratio | 0.099 | | matches | | 0 | "The water stung her eyes, but she didn't dare wipe it away—not when her quarry was so close." | | 1 | "The figure—male, slim, wearing a dark hoodie—glanced back." | | 2 | "Her partner's unexplained death had been connected to this network—this \"clique\" as her informants called them." | | 3 | "But backup meant paperwork, and paperwork meant explaining where her investigation had led—into territory her superiors had explicitly forbidden." | | 4 | "A sound—footsteps on metal—drew her attention to a back corner where a service door stood ajar." | | 5 | "Graffiti marked the surfaces—but not the usual tags and crude drawings." | | 6 | "Not just one or two, but many—a murmur that suggested a crowd." | | 7 | "The tunnel opened into a vast chamber—an abandoned Tube station platform transformed into something out of a fever dream." | | 8 | "She'd heard whispers of it during her investigation—an underground bazaar where the clique and their ilk traded." | | 9 | "She didn't believe in the supernatural—refused to believe, even after what happened to Morris." | | 10 | "Something that sounded like gunshots—but not quite—echoed through the chamber." |
| |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1131 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 39 | | adverbRatio | 0.034482758620689655 | | lyAdverbCount | 19 | | lyAdverbRatio | 0.016799292661361626 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 111 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 111 | | mean | 11.96 | | std | 5.91 | | cv | 0.494 | | sampleLengths | | 0 | 20 | | 1 | 18 | | 2 | 17 | | 3 | 17 | | 4 | 9 | | 5 | 22 | | 6 | 9 | | 7 | 15 | | 8 | 8 | | 9 | 12 | | 10 | 20 | | 11 | 3 | | 12 | 1 | | 13 | 11 | | 14 | 13 | | 15 | 11 | | 16 | 16 | | 17 | 15 | | 18 | 8 | | 19 | 12 | | 20 | 6 | | 21 | 16 | | 22 | 5 | | 23 | 15 | | 24 | 19 | | 25 | 10 | | 26 | 15 | | 27 | 16 | | 28 | 16 | | 29 | 20 | | 30 | 12 | | 31 | 2 | | 32 | 9 | | 33 | 13 | | 34 | 20 | | 35 | 11 | | 36 | 12 | | 37 | 9 | | 38 | 12 | | 39 | 9 | | 40 | 8 | | 41 | 19 | | 42 | 11 | | 43 | 14 | | 44 | 19 | | 45 | 3 | | 46 | 17 | | 47 | 19 | | 48 | 12 | | 49 | 16 |
| |
| 72.37% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 8 | | diversityRatio | 0.4774774774774775 | | totalSentences | 111 | | uniqueOpeners | 53 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 92 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 17 | | totalSentences | 92 | | matches | | 0 | "she shouted, though she knew" | | 1 | "They veered north toward Camden," | | 2 | "Her partner's unexplained death had" | | 3 | "She crossed the threshold, gun" | | 4 | "she called out, her voice" | | 5 | "She'd heard whispers of it" | | 6 | "She needed to blend in," | | 7 | "She moved through the crowd," | | 8 | "She didn't believe in the" | | 9 | "She spotted her suspect near" | | 10 | "He was speaking urgently to" | | 11 | "She was close enough to" | | 12 | "She turned sharply to find" | | 13 | "His olive skin tightened around" | | 14 | "He broke off, shaking his" | | 15 | "she said, her voice tight" | | 16 | "He'd never been so familiar." |
| | ratio | 0.185 | |
| 46.96% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 76 | | totalSentences | 92 | | matches | | 0 | "Quinn's boots splashed through puddles" | | 1 | "The water stung her eyes," | | 2 | "The suspect darted across Charing" | | 3 | "The driver's curse was lost" | | 4 | "Quinn followed, raising a hand" | | 5 | "she shouted, though she knew" | | 6 | "The word scattered in the" | | 7 | "The figure—male, slim, wearing a" | | 8 | "Quinn caught a glimpse of" | | 9 | "This was different." | | 10 | "They veered north toward Camden," | | 11 | "Quinn's lungs burned, but the" | | 12 | "Her partner's unexplained death had" | | 13 | "People who trafficked in things" | | 14 | "The rain intensified as they" | | 15 | "The suspect suddenly ducked into" | | 16 | "Quinn slowed, drawing her service" | | 17 | "The building looked condemned, windows" | | 18 | "Quinn hesitated at the entrance." | | 19 | "Every instinct honed over eighteen" |
| | ratio | 0.826 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 3 | | totalSentences | 92 | | matches | | 0 | "As if he wasn't running" | | 1 | "Before he could answer, a" | | 2 | "Even if it led her" |
| | ratio | 0.033 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 55 | | technicalSentenceCount | 2 | | matches | | 0 | "The suspect darted across Charing Cross Road, narrowly missing a black cab that screeched to a halt." | | 1 | "A child who turned to watch her pass, revealing a face that was smooth and featureless except for a single mouth." |
| |
| 34.09% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 11 | | uselessAdditionCount | 2 | | matches | | 0 | "she called out, her voice echoing in the confined space" | | 1 | "she said, her voice tight" |
| |
| 75.93% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 4 | | fancyCount | 2 | | fancyTags | | 0 | "she shouted (shout)" | | 1 | "she called out (call out)" |
| | dialogueSentences | 27 | | tagDensity | 0.148 | | leniency | 0.296 | | rawRatio | 0.5 | | effectiveRatio | 0.148 | |