| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 19 | | adverbTagCount | 2 | | adverbTags | | 0 | "Quinn said suddenly [suddenly]" | | 1 | "Eva said finally [finally]" |
| | dialogueSentences | 70 | | tagDensity | 0.271 | | leniency | 0.543 | | rawRatio | 0.105 | | effectiveRatio | 0.057 | |
| 85.77% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 2108 | | totalAiIsmAdverbs | 6 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | adverb | "barely above a whisper" | | count | 1 |
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| | highlights | | 0 | "carefully" | | 1 | "lazily" | | 2 | "very" | | 3 | "suddenly" | | 4 | "barely above a whisper" |
| |
| 80.00% | AI-ism character names | Target: 0 AI-default names (17 tracked, −20% each) | | codexExemptions | (empty) | | found | | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 69.17% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 2108 | | totalAiIsms | 13 | | found | | | highlights | | 0 | "flicked" | | 1 | "weight" | | 2 | "measured" | | 3 | "etched" | | 4 | "database" | | 5 | "pristine" | | 6 | "flicker" | | 7 | "tracing" | | 8 | "perfect" | | 9 | "pulse" | | 10 | "whisper" | | 11 | "footsteps" | | 12 | "echoing" |
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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 | 123 | | matches | (empty) | |
| 96.40% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 2 | | narrationSentences | 123 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 172 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 53 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 2095 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 20 | | unquotedAttributions | 0 | | matches | (empty) | |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 79 | | wordCount | 1387 | | uniqueNames | 12 | | maxNameDensity | 2.24 | | worstName | "Quinn" | | maxWindowNameDensity | 5.5 | | worstWindowName | "Eva" | | discoveredNames | | Quinn | 31 | | Brixton | 1 | | Tube | 1 | | Veil | 3 | | Market | 2 | | Morris | 5 | | Eva | 25 | | Kowalski | 4 | | Metropolitan | 1 | | Police | 1 | | Compass | 2 | | Two | 3 |
| | persons | | 0 | "Quinn" | | 1 | "Market" | | 2 | "Morris" | | 3 | "Eva" | | 4 | "Kowalski" | | 5 | "Compass" |
| | places | | | globalScore | 0.382 | | windowScore | 0 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 88 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 2 | | per1kWords | 0.955 | | wordCount | 2095 | | matches | | 0 | "neither north nor" | | 1 | "not to tuck her hair, but to grip the strap like a lifeline" |
| |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 172 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 80 | | mean | 26.19 | | std | 23.39 | | cv | 0.893 | | sampleLengths | | 0 | 70 | | 1 | 44 | | 2 | 12 | | 3 | 66 | | 4 | 15 | | 5 | 58 | | 6 | 21 | | 7 | 34 | | 8 | 11 | | 9 | 11 | | 10 | 47 | | 11 | 4 | | 12 | 52 | | 13 | 18 | | 14 | 44 | | 15 | 4 | | 16 | 4 | | 17 | 39 | | 18 | 6 | | 19 | 60 | | 20 | 9 | | 21 | 46 | | 22 | 11 | | 23 | 13 | | 24 | 13 | | 25 | 40 | | 26 | 78 | | 27 | 18 | | 28 | 3 | | 29 | 4 | | 30 | 64 | | 31 | 51 | | 32 | 8 | | 33 | 4 | | 34 | 50 | | 35 | 11 | | 36 | 3 | | 37 | 52 | | 38 | 6 | | 39 | 31 | | 40 | 12 | | 41 | 18 | | 42 | 2 | | 43 | 43 | | 44 | 2 | | 45 | 44 | | 46 | 48 | | 47 | 9 | | 48 | 14 | | 49 | 1 |
| |
| 96.71% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 123 | | matches | | 0 | "been sealed" | | 1 | "was etched" | | 2 | "been taken" |
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| 70.30% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 5 | | totalVerbs | 257 | | matches | | 0 | "were escaping" | | 1 | "was packing" | | 2 | "was looking" | | 3 | "was lying" | | 4 | "was wrapping" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 12 | | semicolonCount | 0 | | flaggedSentences | 11 | | totalSentences | 172 | | ratio | 0.064 | | matches | | 0 | "Her partner Morris, three years cold in the ground, who'd been investigating something down here when—" | | 1 | "She tucked a strand of hair behind her left ear—a nervous habit Quinn had catalogued months ago, during a different investigation." | | 2 | "This spray arced upward, away from the victim, in a way that suggested—" | | 3 | "The full moon had been last night, which meant the market would move soon—if it hadn't already started." | | 4 | "\"—unusual materials. Creates instruments for people who need to find things that don't want to be found.\"" | | 5 | "One caught her eye—a small compass with a patina of verdigris on its casing." | | 6 | "Not just clean—unworn." | | 7 | "Eva Kowalski was lying about something, but the skill of it was impressive—enough truth mixed with the deception that most detectives wouldn't notice the seams." | | 8 | "But something else had caught her attention—a bare spot in the display, a perfect circle in the dust where something had recently sat." | | 9 | "Eva's composure cracked—just for a moment—and Quinn saw something beneath it." | | 10 | "Eva's hand moved to her satchel—not to tuck her hair, but to grip the strap like a lifeline." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1031 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 26 | | adverbRatio | 0.02521823472356935 | | lyAdverbCount | 3 | | lyAdverbRatio | 0.002909796314258002 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 172 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 172 | | mean | 12.18 | | std | 8.56 | | cv | 0.703 | | sampleLengths | | 0 | 8 | | 1 | 27 | | 2 | 35 | | 3 | 3 | | 4 | 7 | | 5 | 8 | | 6 | 10 | | 7 | 16 | | 8 | 12 | | 9 | 25 | | 10 | 14 | | 11 | 12 | | 12 | 15 | | 13 | 8 | | 14 | 7 | | 15 | 16 | | 16 | 21 | | 17 | 21 | | 18 | 7 | | 19 | 14 | | 20 | 21 | | 21 | 13 | | 22 | 11 | | 23 | 11 | | 24 | 12 | | 25 | 22 | | 26 | 13 | | 27 | 4 | | 28 | 18 | | 29 | 12 | | 30 | 13 | | 31 | 9 | | 32 | 5 | | 33 | 13 | | 34 | 5 | | 35 | 13 | | 36 | 13 | | 37 | 13 | | 38 | 4 | | 39 | 2 | | 40 | 2 | | 41 | 15 | | 42 | 24 | | 43 | 6 | | 44 | 3 | | 45 | 17 | | 46 | 4 | | 47 | 15 | | 48 | 7 | | 49 | 2 |
| |
| 56.78% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 9 | | diversityRatio | 0.37209302325581395 | | totalSentences | 172 | | uniqueOpeners | 64 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 113 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 21 | | totalSentences | 113 | | matches | | 0 | "She'd confiscated it from a" | | 1 | "She'd heard whispers about it" | | 2 | "Her partner Morris, three years" | | 3 | "She tucked a strand of" | | 4 | "They walked together to the" | | 5 | "It had pooled beneath the" | | 6 | "She was looking at the" | | 7 | "His nails were clean." | | 8 | "She stood, her knees protesting" | | 9 | "She stopped, choosing her words" | | 10 | "She had maybe twenty minutes" | | 11 | "She'd have to return it" | | 12 | "She walked back to the" | | 13 | "She paused, watching Eva's reaction" | | 14 | "She knew what had happened" | | 15 | "It was warm against her" | | 16 | "She met Eva's eyes" | | 17 | "She paused at the bottom" | | 18 | "She climbed the first step," | | 19 | "She looked down at the" |
| | ratio | 0.186 | |
| 57.35% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 91 | | totalSentences | 113 | | matches | | 0 | "The bone token felt wrong" | | 1 | "She'd confiscated it from a" | | 2 | "The Veil Market." | | 3 | "She'd heard whispers about it" | | 4 | "Drug busts where the substances" | | 5 | "Her partner Morris, three years" | | 6 | "Quinn pushed the memory aside" | | 7 | "The abandoned platform stretched away" | | 8 | "The air smelled of incense," | | 9 | "Something that made her sinuses" | | 10 | "The voice came from her" | | 11 | "Eva Kowalski stood near the" | | 12 | "The young woman's red curls" | | 13 | "She tucked a strand of" | | 14 | "Quinn kept her voice neutral" | | 15 | "Eva's green eyes flicked toward" | | 16 | "Quinn let that sit for" | | 17 | "Eva Kowalski had credentials that" | | 18 | "The researcher shifted her weight," | | 19 | "They walked together to the" |
| | ratio | 0.805 | |
| 44.25% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 113 | | matches | | | ratio | 0.009 | |
| 46.91% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 67 | | technicalSentenceCount | 9 | | matches | | 0 | "Now she stood at the bottom of a spiral staircase that shouldn't exist, in a Tube station that had been sealed since 1932, watching forensics techs photograph a…" | | 1 | "Her partner Morris, three years cold in the ground, who'd been investigating something down here when—" | | 2 | "Something that made her sinuses ache and her teeth feel too large for her mouth." | | 3 | "She had maybe twenty minutes before someone higher up got word of her presence here and started asking questions about how a Metropolitan Police detective had g…" | | 4 | "Italian leather, hand-stitched, the kind of shoes that cost more than her monthly rent." | | 5 | "The forensics team was wrapping up, loading equipment into cases that would be logged and filed and eventually forgotten." | | 6 | "It was warm against her fingers, humming with a frequency just below the threshold of hearing." | | 7 | "Quinn stood alone on the platform, surrounded by covered stalls and fairy lights and a body that had been dead before it arrived." | | 8 | "The Veil Compass sat waiting, its needle spinning toward something she couldn't see." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 19 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 5 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 70 | | tagDensity | 0.071 | | leniency | 0.143 | | rawRatio | 0 | | effectiveRatio | 0 | |