| 46.15% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 6 | | adverbTagCount | 1 | | adverbTags | | 0 | "he said quietly [quietly]" |
| | dialogueSentences | 13 | | tagDensity | 0.462 | | leniency | 0.923 | | rawRatio | 0.167 | | effectiveRatio | 0.154 | |
| 95.88% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1213 | | 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) | |
| 54.66% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1213 | | totalAiIsms | 11 | | found | | | highlights | | 0 | "familiar" | | 1 | "unsettled" | | 2 | "navigating" | | 3 | "echoing" | | 4 | "mechanical" | | 5 | "reminder" | | 6 | "scanned" | | 7 | "silence" | | 8 | "shimmered" | | 9 | "gloom" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 1 | | narrationSentences | 91 | | matches | | |
| 95.76% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 1 | | narrationSentences | 91 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 98 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 35 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 1 | | markdownWords | 5 | | totalWords | 1214 | | ratio | 0.004 | | matches | | 0 | "Camden Town Station - Closed" |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 9 | | unquotedAttributions | 0 | | matches | (empty) | |
| 90.59% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 39 | | wordCount | 1094 | | uniqueNames | 14 | | maxNameDensity | 1.19 | | worstName | "Quinn" | | maxWindowNameDensity | 2 | | worstWindowName | "Quinn" | | discoveredNames | | Harlow | 1 | | Quinn | 13 | | Camden | 3 | | High | 1 | | Street | 1 | | Herrera | 9 | | Saint | 1 | | Christopher | 1 | | Town | 1 | | Station | 1 | | Tube | 1 | | Morris | 4 | | Metropolitan | 1 | | Police | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Herrera" | | 3 | "Saint" | | 4 | "Christopher" | | 5 | "Morris" |
| | places | | 0 | "Camden" | | 1 | "High" | | 2 | "Street" | | 3 | "Town" | | 4 | "Station" | | 5 | "Metropolitan" |
| | globalScore | 0.906 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 71 | | 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 | 1214 | | matches | (empty) | |
| 64.63% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 3 | | totalSentences | 98 | | matches | | 0 | "own that night" | | 1 | "convinced that the" | | 2 | "feeling that the" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 28 | | mean | 43.36 | | std | 24.3 | | cv | 0.561 | | sampleLengths | | 0 | 75 | | 1 | 68 | | 2 | 49 | | 3 | 64 | | 4 | 56 | | 5 | 66 | | 6 | 33 | | 7 | 12 | | 8 | 52 | | 9 | 46 | | 10 | 109 | | 11 | 42 | | 12 | 23 | | 13 | 31 | | 14 | 27 | | 15 | 34 | | 16 | 22 | | 17 | 77 | | 18 | 29 | | 19 | 17 | | 20 | 55 | | 21 | 4 | | 22 | 4 | | 23 | 35 | | 24 | 73 | | 25 | 27 | | 26 | 57 | | 27 | 27 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 91 | | matches | | |
| 0.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 6 | | totalVerbs | 181 | | matches | | 0 | "was navigating" | | 1 | "wasn’t running" | | 2 | "was warning" | | 3 | "wasn't threatening" | | 4 | "was hiding" | | 5 | "was hunting" |
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| 55.39% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 1 | | semicolonCount | 2 | | flaggedSentences | 3 | | totalSentences | 98 | | ratio | 0.031 | | matches | | 0 | "He sprinted toward a rusted iron gate marked with faded graffiti that read *Camden Town Station - Closed*." | | 1 | "He wasn’t running blindly; he was navigating." | | 2 | "He wasn't threatening her; he was warning her." |
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| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1096 | | adjectiveStacks | 1 | | stackExamples | | 0 | "heavier, pressing against her" |
| | adverbCount | 22 | | adverbRatio | 0.020072992700729927 | | lyAdverbCount | 6 | | lyAdverbRatio | 0.005474452554744526 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 98 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 98 | | mean | 12.39 | | std | 7.43 | | cv | 0.6 | | sampleLengths | | 0 | 17 | | 1 | 5 | | 2 | 29 | | 3 | 24 | | 4 | 27 | | 5 | 3 | | 6 | 19 | | 7 | 16 | | 8 | 3 | | 9 | 4 | | 10 | 2 | | 11 | 21 | | 12 | 22 | | 13 | 16 | | 14 | 23 | | 15 | 4 | | 16 | 3 | | 17 | 18 | | 18 | 10 | | 19 | 16 | | 20 | 15 | | 21 | 15 | | 22 | 4 | | 23 | 35 | | 24 | 9 | | 25 | 18 | | 26 | 15 | | 27 | 7 | | 28 | 11 | | 29 | 10 | | 30 | 2 | | 31 | 4 | | 32 | 24 | | 33 | 11 | | 34 | 2 | | 35 | 5 | | 36 | 6 | | 37 | 10 | | 38 | 22 | | 39 | 14 | | 40 | 7 | | 41 | 12 | | 42 | 16 | | 43 | 28 | | 44 | 17 | | 45 | 7 | | 46 | 3 | | 47 | 19 | | 48 | 7 | | 49 | 13 |
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| 30.61% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 19 | | diversityRatio | 0.2755102040816326 | | totalSentences | 98 | | uniqueOpeners | 27 | |
| 38.31% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 87 | | matches | | | ratio | 0.011 | |
| 0.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 48 | | totalSentences | 87 | | matches | | 0 | "She did not slow down." | | 1 | "Her boots hammered the slick" | | 2 | "Her breath came in ragged," | | 3 | "She drew her service weapon," | | 4 | "She didn’t want to spook" | | 5 | "She wanted answers." | | 6 | "She knew the man." | | 7 | "She had tracked his movements" | | 8 | "He didn’t stop." | | 9 | "He sprinted toward a rusted" | | 10 | "Her military precision kicked in," | | 11 | "She reached the gate just" | | 12 | "She squeezed through after him," | | 13 | "They were in the abandoned" | | 14 | "He wasn’t running blindly; he" | | 15 | "she shouted, her voice echoing" | | 16 | "He didn’t look back." | | 17 | "He reached a heavy steel" | | 18 | "He fumbled in his pocket" | | 19 | "It looked like a bone." |
| | ratio | 0.552 | |
| 5.98% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 79 | | totalSentences | 87 | | matches | | 0 | "Rain lashed against Harlow Quinn’s" | | 1 | "She did not slow down." | | 2 | "Her boots hammered the slick" | | 3 | "Her breath came in ragged," | | 4 | "Quinn didn’t hesitate." | | 5 | "She drew her service weapon," | | 6 | "She didn’t want to spook" | | 7 | "She wanted answers." | | 8 | "She knew the man." | | 9 | "The name had been on" | | 10 | "She had tracked his movements" | | 11 | "The figure turned at the" | | 12 | "He didn’t stop." | | 13 | "He sprinted toward a rusted" | | 14 | "Quinn holstered the weapon and" | | 15 | "Her military precision kicked in," | | 16 | "She reached the gate just" | | 17 | "She squeezed through after him," | | 18 | "The air changed instantly." | | 19 | "The roar of the city" |
| | ratio | 0.908 | |
| 57.47% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 87 | | matches | | 0 | "If she stepped through, she" |
| | ratio | 0.011 | |
| 19.23% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 52 | | technicalSentenceCount | 9 | | matches | | 0 | "Rain lashed against Harlow Quinn’s face, stinging her eyes and matting the salt-and-pepper hair against her skull." | | 1 | "Her boots hammered the slick pavement of Camden High Street, the sound swallowed by the drumming of the downpour and the distant wail of a siren that wasn’t her…" | | 2 | "Ahead, the figure ducked under the awning of a closed newsstand, then bolted into the mouth of an alleyway that smelled of wet brick and rotting refuse." | | 3 | "She had tracked his movements for weeks, piecing together a pattern that led her here, to the edge of the city’s underbelly." | | 4 | "He sprinted toward a rusted iron gate marked with faded graffiti that read *Camden Town Station - Closed*." | | 5 | "Her military precision kicked in, suppressing the burn in her lungs, focusing only on the target." | | 6 | "The tiles were grimy, the tracks overgrown with weeds that seemed too dark, too thick for this depth." | | 7 | "The floor was paved with cobblestones, and stalls lined the walls, selling goods that shimmered with an unnatural luster." | | 8 | "She moved deeper into the market, the worn leather of her watch creaking against her wrist, a small anchor in a world that had lost its gravity." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 6 | | uselessAdditionCount | 2 | | matches | | 0 | "she shouted, her voice echoing off the damp concrete" | | 1 | "Quinn said, her voice low and steady" |
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| 73.08% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 6 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 13 | | tagDensity | 0.462 | | leniency | 0.923 | | rawRatio | 0.167 | | effectiveRatio | 0.154 | |