| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 1 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 3 | | tagDensity | 0.333 | | leniency | 0.667 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 96.58% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1460 | | totalAiIsmAdverbs | 1 | | 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) | |
| 62.33% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1460 | | totalAiIsms | 11 | | found | | | highlights | | 0 | "fractured" | | 1 | "mechanical" | | 2 | "pulsed" | | 3 | "resolved" | | 4 | "weight" | | 5 | "scanned" | | 6 | "comforting" | | 7 | "quivered" | | 8 | "warmth" | | 9 | "stomach" | | 10 | "predator" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "stomach dropped/sank" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 122 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 1 | | narrationSentences | 122 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 124 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 42 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1455 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 5 | | unquotedAttributions | 0 | | matches | (empty) | |
| 66.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 54 | | wordCount | 1441 | | uniqueNames | 19 | | maxNameDensity | 1.25 | | worstName | "Quinn" | | maxWindowNameDensity | 3 | | worstWindowName | "Herrera" | | discoveredNames | | Herrera | 12 | | Camden | 2 | | High | 2 | | Street | 3 | | Raven | 1 | | Nest | 1 | | Saint | 1 | | Christopher | 1 | | Quinn | 18 | | Buck | 1 | | London | 1 | | Marathon | 1 | | Morris | 4 | | Whitechapel | 1 | | Tuesday | 1 | | Tube | 1 | | Underground | 1 | | Market | 1 | | Brixton | 1 |
| | persons | | 0 | "Herrera" | | 1 | "Saint" | | 2 | "Christopher" | | 3 | "Quinn" | | 4 | "Buck" | | 5 | "Morris" |
| | places | | 0 | "Camden" | | 1 | "High" | | 2 | "Raven" | | 3 | "London" | | 4 | "Whitechapel" | | 5 | "Market" | | 6 | "Brixton" |
| | globalScore | 0.875 | | windowScore | 0.667 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 77 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.687 | | wordCount | 1455 | | matches | | 0 | "Not the clean hiss of an empty channel but a thick, granular static" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 124 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 48 | | mean | 30.31 | | std | 24.83 | | cv | 0.819 | | sampleLengths | | 0 | 21 | | 1 | 66 | | 2 | 3 | | 3 | 6 | | 4 | 80 | | 5 | 73 | | 6 | 45 | | 7 | 10 | | 8 | 28 | | 9 | 1 | | 10 | 43 | | 11 | 2 | | 12 | 41 | | 13 | 45 | | 14 | 44 | | 15 | 7 | | 16 | 22 | | 17 | 5 | | 18 | 26 | | 19 | 72 | | 20 | 4 | | 21 | 5 | | 22 | 78 | | 23 | 8 | | 24 | 87 | | 25 | 55 | | 26 | 28 | | 27 | 45 | | 28 | 1 | | 29 | 78 | | 30 | 31 | | 31 | 54 | | 32 | 50 | | 33 | 3 | | 34 | 21 | | 35 | 48 | | 36 | 19 | | 37 | 24 | | 38 | 13 | | 39 | 28 | | 40 | 34 | | 41 | 2 | | 42 | 13 | | 43 | 37 | | 44 | 6 | | 45 | 13 | | 46 | 4 | | 47 | 26 |
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| 96.64% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 122 | | matches | | 0 | "been fifteen" | | 1 | "been blacked" | | 2 | "been fifteen" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 219 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 124 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1446 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 35 | | adverbRatio | 0.024204702627939143 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.003457814661134163 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 124 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 124 | | mean | 11.73 | | std | 9.75 | | cv | 0.831 | | sampleLengths | | 0 | 21 | | 1 | 10 | | 2 | 14 | | 3 | 42 | | 4 | 3 | | 5 | 3 | | 6 | 3 | | 7 | 31 | | 8 | 25 | | 9 | 24 | | 10 | 6 | | 11 | 15 | | 12 | 20 | | 13 | 32 | | 14 | 5 | | 15 | 17 | | 16 | 23 | | 17 | 10 | | 18 | 3 | | 19 | 2 | | 20 | 19 | | 21 | 2 | | 22 | 2 | | 23 | 1 | | 24 | 13 | | 25 | 24 | | 26 | 6 | | 27 | 2 | | 28 | 3 | | 29 | 12 | | 30 | 20 | | 31 | 6 | | 32 | 8 | | 33 | 26 | | 34 | 11 | | 35 | 4 | | 36 | 1 | | 37 | 20 | | 38 | 4 | | 39 | 15 | | 40 | 5 | | 41 | 2 | | 42 | 1 | | 43 | 21 | | 44 | 3 | | 45 | 2 | | 46 | 10 | | 47 | 6 | | 48 | 10 | | 49 | 14 |
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| 53.49% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 12 | | diversityRatio | 0.3790322580645161 | | totalSentences | 124 | | uniqueOpeners | 47 | |
| 64.10% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 104 | | matches | | 0 | "Somewhere on Camden High Street," | | 1 | "Just his radio on the" |
| | ratio | 0.019 | |
| 96.92% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 32 | | totalSentences | 104 | | matches | | 0 | "She kept her eyes locked" | | 1 | "He didn't stop." | | 2 | "They never stopped." | | 3 | "She'd spotted him outside the" | | 4 | "He cut left into Buck" | | 5 | "She was twelve years older" | | 6 | "It toppled behind him, spilling" | | 7 | "He glanced back." | | 8 | "His face caught a streetlight," | | 9 | "He ducked into an alley" | | 10 | "She advanced slowly." | | 11 | "It stood open by two" | | 12 | "She reached for her radio." | | 13 | "She tried again." | | 14 | "She'd found the basement empty." | | 15 | "She pushed the door open." | | 16 | "She scanned the crowd." | | 17 | "He walked with purpose but" | | 18 | "He thought he'd lost her" | | 19 | "She kept her head down" |
| | ratio | 0.308 | |
| 36.92% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 88 | | totalSentences | 104 | | matches | | 0 | "The bone token hit the" | | 1 | "Quinn's boots hammered the wet" | | 2 | "Rain sheeted across the shopfronts," | | 3 | "She kept her eyes locked" | | 4 | "He didn't stop." | | 5 | "They never stopped." | | 6 | "She'd spotted him outside the" | | 7 | "Herrera was the clique's medic," | | 8 | "He cut left into Buck" | | 9 | "Quinn followed, her worn leather" | | 10 | "The rain was getting worse," | | 11 | "She was twelve years older" | | 12 | "Herrera vaulted a recycling bin." | | 13 | "It toppled behind him, spilling" | | 14 | "Quinn sidestepped the worst of" | | 15 | "He glanced back." | | 16 | "His face caught a streetlight," | | 17 | "He ducked into an alley" | | 18 | "Quinn reached the alley's mouth" | | 19 | "The alley dead-ended at a" |
| | ratio | 0.846 | |
| 48.08% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 104 | | matches | | 0 | "Before Herrera entered, he unzipped" |
| | ratio | 0.01 | |
| 38.96% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 55 | | technicalSentenceCount | 8 | | matches | | 0 | "She kept her eyes locked on the back of Herrera's jacket, that dark green field coat slick with rain, his figure weaving between the last stragglers of the even…" | | 1 | "Something stringed and unfamiliar, played in a minor key that made her back teeth ache." | | 2 | "The walls glistened with moisture that caught the faint luminescence rising from below, a phosphorescent blue-green that clung to the mortar between stones like…" | | 3 | "The music grew louder with each step, and the crowd-murmur resolved into distinct sounds: haggling voices, the clink of glass on metal, a bark of laughter that …" | | 4 | "Vendors sold things from tables, from blankets spread on the platform edge, from the open doors of decommissioned carriages that sat on the dead tracks like bea…" | | 5 | "The nearest stall displayed rows of glass phials filled with liquids that moved against gravity, sliding up the inside of their containers in lazy spirals." | | 6 | "Quinn pressed herself against the tiled wall behind a stall selling leather-bound books that whispered when you walked past them." | | 7 | "Crossed the platform toward the blacked-out carriage, weaving between stalls, between bodies that smelled of incense and ozone and wet earth." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 1 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 1 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 3 | | tagDensity | 0.333 | | leniency | 0.667 | | rawRatio | 0 | | effectiveRatio | 0 | |