| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 6 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 29 | | tagDensity | 0.207 | | leniency | 0.414 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 94.26% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 871 | | 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) | |
| 31.11% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 871 | | totalAiIsms | 12 | | found | | | highlights | | 0 | "jaw clenched" | | 1 | "silence" | | 2 | "implication" | | 3 | "flicked" | | 4 | "racing" | | 5 | "pounding" | | 6 | "etched" | | 7 | "pulse" | | 8 | "raced" | | 9 | "echoed" | | 10 | "glinting" |
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| 66.67% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 2 | | maxInWindow | 2 | | found | | 0 | | label | "clenched jaw/fists" | | count | 1 |
| | 1 | | label | "jaw/fists clenched" | | count | 1 |
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| | highlights | | 0 | "clenched into fists" | | 1 | "jaw clenched" |
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| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 90 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 90 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 109 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 25 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 5 | | markdownWords | 5 | | totalWords | 867 | | ratio | 0.006 | | matches | | 0 | "wrong" | | 1 | "down" | | 2 | "thud" | | 3 | "moved" | | 4 | "away" |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 6 | | unquotedAttributions | 0 | | matches | (empty) | |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 38 | | wordCount | 755 | | uniqueNames | 6 | | maxNameDensity | 3.84 | | worstName | "Quinn" | | maxWindowNameDensity | 5.5 | | worstWindowName | "Quinn" | | discoveredNames | | Tube | 1 | | Harlow | 1 | | Quinn | 29 | | Kowalski | 1 | | Veil | 3 | | Market | 3 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Kowalski" | | 3 | "Market" |
| | places | (empty) | | globalScore | 0 | | windowScore | 0 | |
| 16.07% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 56 | | glossingSentenceCount | 3 | | matches | | 0 | "looked like old newspapers, the edges sin" | | 1 | "as if trying to still the motion" | | 2 | "as if trying to reach something" |
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| 84.66% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 1.153 | | wordCount | 867 | | matches | | 0 | "not gonna believe me, but I think she was tracking something" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 109 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 54 | | mean | 16.06 | | std | 14.38 | | cv | 0.895 | | sampleLengths | | 0 | 76 | | 1 | 63 | | 2 | 2 | | 3 | 5 | | 4 | 7 | | 5 | 14 | | 6 | 11 | | 7 | 11 | | 8 | 15 | | 9 | 7 | | 10 | 7 | | 11 | 17 | | 12 | 4 | | 13 | 5 | | 14 | 37 | | 15 | 8 | | 16 | 2 | | 17 | 25 | | 18 | 8 | | 19 | 10 | | 20 | 36 | | 21 | 11 | | 22 | 2 | | 23 | 30 | | 24 | 39 | | 25 | 30 | | 26 | 28 | | 27 | 16 | | 28 | 7 | | 29 | 17 | | 30 | 6 | | 31 | 8 | | 32 | 6 | | 33 | 9 | | 34 | 15 | | 35 | 16 | | 36 | 8 | | 37 | 14 | | 38 | 31 | | 39 | 4 | | 40 | 28 | | 41 | 17 | | 42 | 18 | | 43 | 3 | | 44 | 28 | | 45 | 11 | | 46 | 5 | | 47 | 21 | | 48 | 11 | | 49 | 25 |
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| 81.87% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 6 | | totalSentences | 90 | | matches | | 0 | "was matted" | | 1 | "were clenched" | | 2 | "were wrapped" | | 3 | "were locked" | | 4 | "was gone" | | 5 | "was gone" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 139 | | matches | | |
| 64.22% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 4 | | semicolonCount | 0 | | flaggedSentences | 3 | | totalSentences | 109 | | ratio | 0.028 | | matches | | 0 | "And if this was another one of those shifts—" | | 1 | "Quinn pushed through a collapsed wall, the scent of damp earth and something older—something *wrong*—washing over her." | | 2 | "And if this was one of those markets—" |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 759 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 28 | | adverbRatio | 0.03689064558629776 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.006587615283267457 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 109 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 109 | | mean | 7.95 | | std | 4.96 | | cv | 0.623 | | sampleLengths | | 0 | 20 | | 1 | 23 | | 2 | 18 | | 3 | 15 | | 4 | 10 | | 5 | 19 | | 6 | 11 | | 7 | 7 | | 8 | 16 | | 9 | 2 | | 10 | 4 | | 11 | 1 | | 12 | 5 | | 13 | 2 | | 14 | 9 | | 15 | 5 | | 16 | 7 | | 17 | 4 | | 18 | 9 | | 19 | 2 | | 20 | 8 | | 21 | 7 | | 22 | 3 | | 23 | 4 | | 24 | 7 | | 25 | 4 | | 26 | 13 | | 27 | 3 | | 28 | 1 | | 29 | 5 | | 30 | 8 | | 31 | 7 | | 32 | 16 | | 33 | 3 | | 34 | 3 | | 35 | 8 | | 36 | 2 | | 37 | 3 | | 38 | 8 | | 39 | 8 | | 40 | 6 | | 41 | 8 | | 42 | 8 | | 43 | 2 | | 44 | 10 | | 45 | 10 | | 46 | 7 | | 47 | 9 | | 48 | 11 | | 49 | 2 |
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| 41.74% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 9 | | diversityRatio | 0.24770642201834864 | | totalSentences | 109 | | uniqueOpeners | 27 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 82 | | matches | | 0 | "Then she turned back to" | | 1 | "Instead, she grabbed her satchel" | | 2 | "Then the shadows *moved*." |
| | ratio | 0.037 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 19 | | totalSentences | 82 | | matches | | 0 | "She stepped over a half-buried" | | 1 | "Her sharp jaw clenched as" | | 2 | "She reached for her radio," | | 3 | "She didn’t look up." | | 4 | "It was a place where" | | 5 | "She didn’t answer." | | 6 | "She didn’t see the figure" | | 7 | "His hands were wrapped around" | | 8 | "It pointed *down*." | | 9 | "She didn’t need to see" | | 10 | "His fingers twitched around the" | | 11 | "He didn’t look at her." | | 12 | "She didn’t need to see" | | 13 | "Her eyes rolled back just" | | 14 | "She drove the knife into" | | 15 | "She didn’t think." | | 16 | "She pulled the compass closer," | | 17 | "It didn’t point down." | | 18 | "It pointed *away*." |
| | ratio | 0.232 | |
| 27.07% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 71 | | totalSentences | 82 | | matches | | 0 | "The flickering fluorescent hum of" | | 1 | "Detective Harlow Quinn adjusted the" | | 2 | "She stepped over a half-buried" | | 3 | "Her sharp jaw clenched as" | | 4 | "A woman lay motionless, her" | | 5 | "Eva Kowalski’s curly red hair" | | 6 | "The air smelled of ozone" | | 7 | "Quinn’s watch ticked loudly in" | | 8 | "She reached for her radio," | | 9 | "She didn’t look up." | | 10 | "Quinn stood abruptly, her boots" | | 11 | "The voice was rough, strained" | | 12 | "Quinn’s fingers tightened around the" | | 13 | "The voice cracked" | | 14 | "Quinn exhaled sharply." | | 15 | "A beat of silence." | | 16 | "Quinn’s jaw tightened." | | 17 | "The words hung between them," | | 18 | "Quinn’s eyes flicked to the" | | 19 | "The woman’s hands were clenched" |
| | ratio | 0.866 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 82 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 35 | | technicalSentenceCount | 1 | | matches | | 0 | "She stepped over a half-buried bag of what looked like old newspapers, the edges singed as if scorched." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 6 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 46.55% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 5 | | fancyCount | 3 | | fancyTags | | 0 | "Quinn demanded (demand)" | | 1 | "Quinn demanded (demand)" | | 2 | "Quinn whispered (whisper)" |
| | dialogueSentences | 29 | | tagDensity | 0.172 | | leniency | 0.345 | | rawRatio | 0.6 | | effectiveRatio | 0.207 | |