| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 1 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 0 | | tagDensity | 1 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 89.51% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1430 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | 0 | "softly" | | 1 | "slowly" | | 2 | "slightly" |
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| 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) | |
| 51.05% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1430 | | totalAiIsms | 14 | | found | | | highlights | | 0 | "rhythmic" | | 1 | "silence" | | 2 | "scanned" | | 3 | "scanning" | | 4 | "pulse" | | 5 | "searing" | | 6 | "etched" | | 7 | "weight" | | 8 | "could feel" | | 9 | "reminder" | | 10 | "looming" |
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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 | 182 | | matches | (empty) | |
| 72.21% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 7 | | hedgeCount | 2 | | narrationSentences | 182 | | filterMatches | | | hedgeMatches | | 0 | "happened to" | | 1 | "seemed to" |
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| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 182 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 36 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1430 | | ratio | 0 | | matches | (empty) | |
| 13.89% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 18 | | unquotedAttributions | 8 | | matches | | 0 | "Because I need your eye, Evie said." | | 1 | "Dead is a polite word for what happened to him, Eva replied, stepping closer." | | 2 | "It looks like a car accident, Harlow muttered." | | 3 | "Veil Compass, Eva whispered." | | 4 | "The needle points to a rift, Eva said." | | 5 | "They think this is a clique job, Harlow said, her voice dropping." | | 6 | "They think the Market is the culprit, Eva corrected." | | 7 | "Someone who knows how to use the compass, she said." |
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| 33.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 64 | | wordCount | 1427 | | uniqueNames | 11 | | maxNameDensity | 2.24 | | worstName | "Harlow" | | maxWindowNameDensity | 4 | | worstWindowName | "Harlow" | | discoveredNames | | Harlow | 32 | | Quinn | 1 | | Morris | 4 | | Kowalski | 1 | | Evie | 1 | | Eva | 17 | | Camden | 1 | | Compass | 1 | | Market | 1 | | London | 1 | | You | 4 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Morris" | | 3 | "Kowalski" | | 4 | "Evie" | | 5 | "Eva" | | 6 | "Compass" | | 7 | "Market" | | 8 | "You" |
| | places | | | globalScore | 0.379 | | windowScore | 0.333 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 116 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1430 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 182 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 57 | | mean | 25.09 | | std | 19.45 | | cv | 0.775 | | sampleLengths | | 0 | 88 | | 1 | 51 | | 2 | 57 | | 3 | 42 | | 4 | 12 | | 5 | 40 | | 6 | 25 | | 7 | 36 | | 8 | 33 | | 9 | 4 | | 10 | 22 | | 11 | 46 | | 12 | 21 | | 13 | 28 | | 14 | 8 | | 15 | 45 | | 16 | 55 | | 17 | 22 | | 18 | 7 | | 19 | 14 | | 20 | 57 | | 21 | 5 | | 22 | 9 | | 23 | 25 | | 24 | 9 | | 25 | 19 | | 26 | 12 | | 27 | 15 | | 28 | 6 | | 29 | 17 | | 30 | 24 | | 31 | 33 | | 32 | 4 | | 33 | 39 | | 34 | 5 | | 35 | 20 | | 36 | 31 | | 37 | 7 | | 38 | 6 | | 39 | 35 | | 40 | 10 | | 41 | 3 | | 42 | 18 | | 43 | 14 | | 44 | 8 | | 45 | 79 | | 46 | 12 | | 47 | 9 | | 48 | 5 | | 49 | 37 |
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| 82.13% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 12 | | totalSentences | 182 | | matches | | 0 | "were swept" | | 1 | "was blackened" | | 2 | "was found" | | 3 | "was gone" | | 4 | "been placed" | | 5 | "was deposited" | | 6 | "was etched" | | 7 | "was used" | | 8 | "been found" | | 9 | "was taken" | | 10 | "was found" | | 11 | "was worn" |
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| 55.60% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 6 | | totalVerbs | 277 | | matches | | 0 | "were searing" | | 1 | "was still, vibrating" | | 2 | "wasn’t spinning" | | 3 | "were breathing" | | 4 | "was watching" | | 5 | "was waiting" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 182 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 177 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 4 | | adverbRatio | 0.022598870056497175 | | lyAdverbCount | 0 | | lyAdverbRatio | 0 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 182 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 182 | | mean | 7.86 | | std | 5.08 | | cv | 0.646 | | sampleLengths | | 0 | 23 | | 1 | 36 | | 2 | 13 | | 3 | 16 | | 4 | 20 | | 5 | 4 | | 6 | 6 | | 7 | 16 | | 8 | 5 | | 9 | 19 | | 10 | 20 | | 11 | 18 | | 12 | 9 | | 13 | 13 | | 14 | 20 | | 15 | 7 | | 16 | 5 | | 17 | 14 | | 18 | 10 | | 19 | 13 | | 20 | 3 | | 21 | 6 | | 22 | 6 | | 23 | 2 | | 24 | 11 | | 25 | 7 | | 26 | 18 | | 27 | 11 | | 28 | 12 | | 29 | 13 | | 30 | 8 | | 31 | 4 | | 32 | 14 | | 33 | 4 | | 34 | 2 | | 35 | 2 | | 36 | 11 | | 37 | 9 | | 38 | 13 | | 39 | 4 | | 40 | 9 | | 41 | 8 | | 42 | 8 | | 43 | 5 | | 44 | 13 | | 45 | 2 | | 46 | 5 | | 47 | 8 | | 48 | 6 | | 49 | 2 |
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| 39.01% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 20 | | diversityRatio | 0.2032967032967033 | | totalSentences | 182 | | uniqueOpeners | 37 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 5 | | totalSentences | 166 | | matches | | 0 | "Just that same ozone taste" | | 1 | "Then how did he get" | | 2 | "Just the body lying there" | | 3 | "Just the clothes." | | 4 | "Then who did it?" |
| | ratio | 0.03 | |
| 60.96% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 66 | | totalSentences | 166 | | matches | | 0 | "She stepped off the final" | | 1 | "Her watch face caught the" | | 2 | "She scanned the tunnel." | | 3 | "It wasn’t supposed to be" | | 4 | "She had her leather satchel" | | 5 | "She stopped a few paces" | | 6 | "You didn’t call for backup," | | 7 | "Her voice was low, flat." | | 8 | "It was a nervous habit" | | 9 | "You know I don’t call" | | 10 | "It’s a body on the" | | 11 | "She kept her hands loose" | | 12 | "Her voice was steady, but" | | 13 | "I need the one person" | | 14 | "He lay face up, arms" | | 15 | "He’s dead, Harlow said." | | 16 | "She leaned in, ignoring the" | | 17 | "It looks like a car" | | 18 | "Her hands hovered over the" | | 19 | "He didn’t walk, Eva said." |
| | ratio | 0.398 | |
| 71.45% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 129 | | totalSentences | 166 | | matches | | 0 | "The air down here tasted" | | 1 | "She stepped off the final" | | 2 | "Her watch face caught the" | | 3 | "Harlow adjusted the brim of" | | 4 | "She scanned the tunnel." | | 5 | "It wasn’t supposed to be" | | 6 | "The manifest said the station" | | 7 | "The grime was too fresh." | | 8 | "Eva Kowalski stood near the" | | 9 | "The researcher wore her round" | | 10 | "She had her leather satchel" | | 11 | "Harlow approached, the leather of" | | 12 | "She stopped a few paces" | | 13 | "Eva looked older than the" | | 14 | "You didn’t call for backup," | | 15 | "Her voice was low, flat." | | 16 | "Eva looked up, tucking a" | | 17 | "It was a nervous habit" | | 18 | "You know I don’t call" | | 19 | "This isn’t less." |
| | ratio | 0.777 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 4 | | totalSentences | 166 | | matches | | 0 | "Because I need your eye," | | 1 | "If he fell, he would" | | 2 | "If it was a sacrifice," | | 3 | "Now, the math didn’t add" |
| | ratio | 0.024 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 51 | | technicalSentenceCount | 2 | | matches | | 0 | "The air down here tasted of stale copper and wet ozone, a sharp metallic tang that coated the back of Harlow Quinn’s throat." | | 1 | "The casing had a patina of verdigris, green oxidation that felt old." |
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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 | |