| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 15 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 51 | | tagDensity | 0.294 | | leniency | 0.588 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 97.17% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1769 | | 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) | |
| 74.56% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1769 | | totalAiIsms | 9 | | found | | | highlights | | 0 | "etched" | | 1 | "footsteps" | | 2 | "echoing" | | 3 | "silence" | | 4 | "weight" | | 5 | "flickered" |
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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 | 1 | | narrationSentences | 106 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 106 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 140 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 67 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 1 | | markdownWords | 1 | | totalWords | 1760 | | ratio | 0.001 | | matches | | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 17 | | unquotedAttributions | 0 | | matches | (empty) | |
| 16.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 37 | | wordCount | 1051 | | uniqueNames | 10 | | maxNameDensity | 1.9 | | worstName | "Quinn" | | maxWindowNameDensity | 4.5 | | worstWindowName | "Quinn" | | discoveredNames | | Harlow | 1 | | Quinn | 20 | | Tube | 1 | | Camden | 1 | | Transport | 1 | | London | 1 | | Veil | 1 | | Market | 1 | | Kowalski | 1 | | Eva | 9 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Tube" | | 3 | "Camden" | | 4 | "Kowalski" | | 5 | "Eva" |
| | places | | | globalScore | 0.549 | | windowScore | 0.167 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 73 | | glossingSentenceCount | 1 | | matches | | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.568 | | wordCount | 1760 | | matches | | 0 | "not for what he knew, but for what he was about to find" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 140 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 59 | | mean | 29.83 | | std | 22.11 | | cv | 0.741 | | sampleLengths | | 0 | 50 | | 1 | 6 | | 2 | 61 | | 3 | 66 | | 4 | 54 | | 5 | 48 | | 6 | 10 | | 7 | 65 | | 8 | 65 | | 9 | 38 | | 10 | 9 | | 11 | 28 | | 12 | 66 | | 13 | 34 | | 14 | 4 | | 15 | 11 | | 16 | 51 | | 17 | 30 | | 18 | 49 | | 19 | 6 | | 20 | 5 | | 21 | 2 | | 22 | 5 | | 23 | 79 | | 24 | 8 | | 25 | 2 | | 26 | 54 | | 27 | 21 | | 28 | 1 | | 29 | 49 | | 30 | 11 | | 31 | 65 | | 32 | 3 | | 33 | 32 | | 34 | 9 | | 35 | 39 | | 36 | 3 | | 37 | 50 | | 38 | 47 | | 39 | 25 | | 40 | 11 | | 41 | 12 | | 42 | 9 | | 43 | 24 | | 44 | 18 | | 45 | 11 | | 46 | 38 | | 47 | 35 | | 48 | 16 | | 49 | 75 |
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| 95.33% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 106 | | matches | | 0 | "been sealed" | | 1 | "was frayed" | | 2 | "was blocked" |
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| 8.43% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 5 | | totalVerbs | 174 | | matches | | 0 | "was humming" | | 1 | "wasn't looking" | | 2 | "was already moving" | | 3 | "was reading" | | 4 | "was already moving" |
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| 20.41% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 8 | | semicolonCount | 0 | | flaggedSentences | 6 | | totalSentences | 140 | | ratio | 0.043 | | matches | | 0 | "The air changed instantly—grew thick, syrupy with incense and wet stone and something metallic she couldn't name." | | 1 | "“Detective Quinn.” The constable—young, fresh-faced, barely old enough to shave—gestured toward the far end of the platform." | | 2 | "His face was slack, peaceful almost, except for the eyes—wide open, fixed on the curved ceiling tiles with an expression that might have been wonder or terror." | | 3 | "She studied the woman's hands—trembling, but not with fear." | | 4 | "She saw footprints—many of them, overlapping, from the market's patrons earlier in the evening." | | 5 | "She tucked a strand of hair behind her left ear—nervous habit—and offered a thin smile." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1066 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 29 | | adverbRatio | 0.027204502814258912 | | lyAdverbCount | 6 | | lyAdverbRatio | 0.005628517823639775 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 140 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 140 | | mean | 12.57 | | std | 10.4 | | cv | 0.827 | | sampleLengths | | 0 | 24 | | 1 | 26 | | 2 | 6 | | 3 | 17 | | 4 | 18 | | 5 | 26 | | 6 | 13 | | 7 | 15 | | 8 | 17 | | 9 | 4 | | 10 | 17 | | 11 | 21 | | 12 | 12 | | 13 | 21 | | 14 | 17 | | 15 | 31 | | 16 | 3 | | 17 | 7 | | 18 | 15 | | 19 | 12 | | 20 | 3 | | 21 | 2 | | 22 | 27 | | 23 | 6 | | 24 | 12 | | 25 | 7 | | 26 | 25 | | 27 | 21 | | 28 | 6 | | 29 | 3 | | 30 | 29 | | 31 | 3 | | 32 | 6 | | 33 | 26 | | 34 | 2 | | 35 | 66 | | 36 | 8 | | 37 | 10 | | 38 | 7 | | 39 | 9 | | 40 | 4 | | 41 | 11 | | 42 | 7 | | 43 | 18 | | 44 | 12 | | 45 | 14 | | 46 | 30 | | 47 | 7 | | 48 | 9 | | 49 | 2 |
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| 56.90% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 12 | | diversityRatio | 0.39285714285714285 | | totalSentences | 140 | | uniqueOpeners | 55 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 4 | | totalSentences | 96 | | matches | | 0 | "Light, quick, with a slight" | | 1 | "More rustling, then a pause." | | 2 | "Then she tucked her hair" | | 3 | "Somewhere in the distance, a" |
| | ratio | 0.042 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 22 | | totalSentences | 96 | | matches | | 0 | "She pushed through into the" | | 1 | "Her leather-soled shoes found the" | | 2 | "She didn't answer." | | 3 | "She was already moving toward" | | 4 | "His face was slack, peaceful" | | 5 | "She noted the way his" | | 6 | "She straightened, rolled her shoulders" | | 7 | "She wore layers of dark" | | 8 | "She studied the woman's hands—trembling," | | 9 | "She walked the perimeter of" | | 10 | "She stopped at the edge" | | 11 | "She saw footprints—many of them," | | 12 | "Her leather satchel was slung" | | 13 | "She tucked a strand of" | | 14 | "She stepped past Quinn and" | | 15 | "They didn't leave people looking" | | 16 | "She walked back to the" | | 17 | "She didn't climb." | | 18 | "She stood there, staring at" | | 19 | "she asked, not turning" |
| | ratio | 0.229 | |
| 48.54% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 79 | | totalSentences | 96 | | matches | | 0 | "The bone token felt cold" | | 1 | "Detective Harlow Quinn pressed it" | | 2 | "She pushed through into the" | | 3 | "The air changed instantly—grew thick," | | 4 | "Her leather-soled shoes found the" | | 5 | "The abandoned Tube station beneath" | | 6 | "Quinn's fingers brushed the worn" | | 7 | "This one was humming, buzzing" | | 8 | "The walls wept moisture." | | 9 | "Graffiti crawled over the curved" | | 10 | "The market stalls were empty" | | 11 | "The constable—young, fresh-faced, barely old" | | 12 | "She didn't answer." | | 13 | "She was already moving toward" | | 14 | "The body lay sprawled on" | | 15 | "His face was slack, peaceful" | | 16 | "Quinn crouched, balancing on the" | | 17 | "Military precision kept her movements" | | 18 | "She noted the way his" | | 19 | "The casing had a patina" |
| | ratio | 0.823 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 96 | | matches | (empty) | | ratio | 0 | |
| 83.33% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 48 | | technicalSentenceCount | 4 | | matches | | 0 | "The bone token felt cold against her palm, a knuckle of something that might have been human once, now polished smooth by countless fingers." | | 1 | "Her leather-soled shoes found the top of a concrete staircase that spiraled down into a dim amber glow." | | 2 | "The abandoned Tube station beneath Camden had been sealed by Transport for London in 1994, but nobody had told the people who ran the Veil Market." | | 3 | "His face was slack, peaceful almost, except for the eyes—wide open, fixed on the curved ceiling tiles with an expression that might have been wonder or terror." |
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| 58.33% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 15 | | uselessAdditionCount | 2 | | matches | | 0 | "Eva looked up, her green eyes sharp behind the lenses" | | 1 | "she asked, not turning" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 7 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 51 | | tagDensity | 0.137 | | leniency | 0.275 | | rawRatio | 0.143 | | effectiveRatio | 0.039 | |