| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | |
| 91.87% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1230 | | totalAiIsmAdverbs | 2 | | found | | | highlights | | |
| 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) | |
| 55.28% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1230 | | totalAiIsms | 11 | | found | | | highlights | | 0 | "familiar" | | 1 | "velvet" | | 2 | "scanning" | | 3 | "rhythmic" | | 4 | "echoing" | | 5 | "etched" | | 6 | "whisper" | | 7 | "wavered" | | 8 | "resolve" |
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| 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 | 0 | | narrationSentences | 87 | | matches | (empty) | |
| 93.60% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 1 | | narrationSentences | 87 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 87 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 36 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1225 | | ratio | 0 | | matches | (empty) | |
| 62.50% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 8 | | unquotedAttributions | 2 | | matches | | 0 | "The indigo stain, Quinn said, pointing with a gloved finger." | | 1 | "Eva, she said when the line clicked open, her voice cold and lethal." |
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| 83.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 44 | | wordCount | 1225 | | uniqueNames | 15 | | maxNameDensity | 0.9 | | worstName | "Quinn" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Miller" | | discoveredNames | | Camden | 1 | | Tube | 1 | | Harlow | 1 | | Quinn | 11 | | Veil | 3 | | Market | 1 | | Miller | 10 | | Detective | 2 | | Compass | 3 | | Morris | 2 | | British | 1 | | Museum | 1 | | Kowalski | 1 | | Eva | 3 | | You | 3 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Market" | | 3 | "Miller" | | 4 | "Morris" | | 5 | "Museum" | | 6 | "Kowalski" | | 7 | "Eva" | | 8 | "You" |
| | places | | | globalScore | 1 | | windowScore | 0.833 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 74 | | glossingSentenceCount | 1 | | matches | | 0 | "as if reaching for an object that didn't exist" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1225 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 87 | | matches | (empty) | |
| 81.99% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 26 | | mean | 47.12 | | std | 20.59 | | cv | 0.437 | | sampleLengths | | 0 | 85 | | 1 | 74 | | 2 | 41 | | 3 | 60 | | 4 | 48 | | 5 | 38 | | 6 | 53 | | 7 | 20 | | 8 | 27 | | 9 | 65 | | 10 | 41 | | 11 | 50 | | 12 | 58 | | 13 | 37 | | 14 | 26 | | 15 | 81 | | 16 | 6 | | 17 | 31 | | 18 | 28 | | 19 | 56 | | 20 | 42 | | 21 | 43 | | 22 | 85 | | 23 | 35 | | 24 | 72 | | 25 | 23 |
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| 77.03% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 7 | | totalSentences | 87 | | matches | | 0 | "was gone" | | 1 | "were twisted" | | 2 | "was tagged" | | 3 | "were stained" | | 4 | "was pinned" | | 5 | "been terrified" | | 6 | "being manipulated" | | 7 | "were pulled" |
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| 48.48% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 5 | | totalVerbs | 220 | | matches | | 0 | "wasn't looking" | | 1 | "were trying" | | 2 | "were holding" | | 3 | "wasn't spinning" | | 4 | "were using" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 5 | | semicolonCount | 3 | | flaggedSentences | 7 | | totalSentences | 87 | | ratio | 0.08 | | matches | | 0 | "This wasn't a death by chemical consumption; it was a ritual interruption." | | 1 | "The victim wasn't looking for a high, she murmured, her voice steady despite the prickle at the back of her neck—a ghost of the sensation she felt the day she lost DS Morris." | | 2 | "She recognized the quality of the leather—the kind of rugged, scholarly craftsmanship that smelled of library dust and old parchment." | | 3 | "The needle wasn't spinning wildly as it did when near a rift; it was pinned hard to the north, pointing directly toward the victim’s chest, frozen in a state of absolute, terrifying lock." | | 4 | "Eva Kowalski had been talking about these rifts for weeks—she’d been terrified of the energy signatures being manipulated." | | 5 | "The Compass didn't guide them; it betrayed them." | | 6 | "If the clique was responsible for this—if they were using the market to tear holes in the fabric of the city—she wasn't going to wait for a forensic report to stop them." |
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| 88.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1238 | | adjectiveStacks | 2 | | stackExamples | | 0 | "small, silver-rimmed monocle" | | 1 | "similar, long-forgotten file." |
| | adverbCount | 30 | | adverbRatio | 0.024232633279483037 | | lyAdverbCount | 12 | | lyAdverbRatio | 0.009693053311793215 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 87 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 87 | | mean | 14.08 | | std | 8.38 | | cv | 0.595 | | sampleLengths | | 0 | 15 | | 1 | 20 | | 2 | 21 | | 3 | 29 | | 4 | 13 | | 5 | 32 | | 6 | 5 | | 7 | 24 | | 8 | 12 | | 9 | 3 | | 10 | 26 | | 11 | 13 | | 12 | 12 | | 13 | 35 | | 14 | 19 | | 15 | 3 | | 16 | 11 | | 17 | 15 | | 18 | 15 | | 19 | 23 | | 20 | 12 | | 21 | 14 | | 22 | 21 | | 23 | 6 | | 24 | 6 | | 25 | 14 | | 26 | 5 | | 27 | 14 | | 28 | 8 | | 29 | 9 | | 30 | 15 | | 31 | 3 | | 32 | 26 | | 33 | 12 | | 34 | 33 | | 35 | 6 | | 36 | 2 | | 37 | 12 | | 38 | 26 | | 39 | 8 | | 40 | 4 | | 41 | 5 | | 42 | 12 | | 43 | 15 | | 44 | 20 | | 45 | 6 | | 46 | 16 | | 47 | 21 | | 48 | 15 | | 49 | 11 |
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| 50.96% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 4 | | diversityRatio | 0.3333333333333333 | | totalSentences | 87 | | uniqueOpeners | 29 | |
| 77.52% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 86 | | matches | | 0 | "Probably one of those street" | | 1 | "Probably why they died." |
| | ratio | 0.023 | |
| 47.91% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 37 | | totalSentences | 86 | | matches | | 0 | "She checked the worn leather" | | 1 | "She pulled her flashlight from" | | 2 | "It was wrong." | | 3 | "She didn't need to look" | | 4 | "It’s an overdose." | | 5 | "She reached into her pocket," | | 6 | "She stood slowly, her military" | | 7 | "It’s just residue, Miller scoffed." | | 8 | "They handle these banned substances," | | 9 | "It’s a clean-cut case of" | | 10 | "She pulled a small, silver-rimmed" | | 11 | "They were trying to anchor" | | 12 | "You’re obsessing again, Quinn, Miller" | | 13 | "You come into these holes" | | 14 | "She stepped over to a" | | 15 | "It was empty, the seams" | | 16 | "She recognized the quality of" | | 17 | "It belonged to no street" | | 18 | "She knelt again, picking up" | | 19 | "It was a page from" |
| | ratio | 0.43 | |
| 47.21% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 71 | | totalSentences | 86 | | matches | | 0 | "The air in the abandoned" | | 1 | "Detective Harlow Quinn stepped over" | | 2 | "She checked the worn leather" | | 3 | "She pulled her flashlight from" | | 4 | "The beam caught the familiar" | | 5 | "The market was a tomb," | | 6 | "A chalk outline lay sprawled" | | 7 | "It was wrong." | | 8 | "The limbs were twisted in" | | 9 | "Quinn knelt, her sharp jaw" | | 10 | "She didn't need to look" | | 11 | "The soft, rhythmic shuffle of" | | 12 | "Whatever you’re looking for, it" | | 13 | "It’s an overdose." | | 14 | "The body was tagged and" | | 15 | "Quinn shifted her gaze, tracking" | | 16 | "She reached into her pocket," | | 17 | "An overdose in a space" | | 18 | "She stood slowly, her military" | | 19 | "A civilian wouldn't even know" |
| | ratio | 0.826 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 4 | | totalSentences | 86 | | matches | | 0 | "If Eva’s research was as" | | 1 | "Whoever this was, they didn't" | | 2 | "If I put this in" | | 3 | "If the clique was responsible" |
| | ratio | 0.047 | |
| 68.97% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 58 | | technicalSentenceCount | 6 | | matches | | 0 | "The soft, rhythmic shuffle of boots against debris announced the arrival of the local precinct’s liaison, a man named Miller who treated every crime scene like …" | | 1 | "Whatever you’re looking for, it isn't here, Detective, Miller said, his voice echoing flatly against the curved station walls." | | 2 | "She reached into her pocket, her fingers brushing the cool brass casing of her own evidence locker key, though her mind was elsewhere." | | 3 | "It was empty, the seams burst as if forced open by something expanding from within." | | 4 | "She recognized the quality of the leather—the kind of rugged, scholarly craftsmanship that smelled of library dust and old parchment." | | 5 | "As she exited the station, the dark, stagnant air of the market seemed to ripple behind her, a whisper of unseen movement that sounded uncomfortably like a name…" |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 0 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |