| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 9 | | adverbTagCount | 1 | | adverbTags | | 0 | "Iyer moved around [around]" |
| | dialogueSentences | 62 | | tagDensity | 0.145 | | leniency | 0.29 | | rawRatio | 0.111 | | effectiveRatio | 0.032 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1823 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 80.00% | AI-ism character names | Target: 0 AI-default names (17 tracked, −20% each) | | codexExemptions | (empty) | | found | | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 78.06% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1823 | | totalAiIsms | 8 | | found | | | highlights | | 0 | "stomach" | | 1 | "familiar" | | 2 | "footsteps" | | 3 | "complex" | | 4 | "traced" | | 5 | "perfect" | | 6 | "echoed" |
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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 | 109 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 1 | | narrationSentences | 109 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 162 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 44 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1823 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 11 | | unquotedAttributions | 0 | | matches | (empty) | |
| 77.27% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 37 | | wordCount | 1100 | | uniqueNames | 8 | | maxNameDensity | 1.45 | | worstName | "Quinn" | | maxWindowNameDensity | 2 | | worstWindowName | "Quinn" | | discoveredNames | | Tube | 1 | | Camden | 1 | | Harlow | 1 | | Quinn | 16 | | Sergeant | 1 | | Iyer | 12 | | Morris | 3 | | Three | 2 |
| | persons | | 0 | "Camden" | | 1 | "Harlow" | | 2 | "Quinn" | | 3 | "Sergeant" | | 4 | "Iyer" | | 5 | "Morris" |
| | places | (empty) | | globalScore | 0.773 | | windowScore | 1 | |
| 45.83% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 72 | | glossingSentenceCount | 3 | | matches | | 0 | "quite place" | | 1 | "something like this before, years ago, on a" | | 2 | "quite a key" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1823 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 162 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 74 | | mean | 24.64 | | std | 19.87 | | cv | 0.806 | | sampleLengths | | 0 | 21 | | 1 | 64 | | 2 | 45 | | 3 | 69 | | 4 | 18 | | 5 | 44 | | 6 | 30 | | 7 | 61 | | 8 | 20 | | 9 | 23 | | 10 | 61 | | 11 | 3 | | 12 | 16 | | 13 | 50 | | 14 | 5 | | 15 | 45 | | 16 | 5 | | 17 | 16 | | 18 | 40 | | 19 | 6 | | 20 | 24 | | 21 | 4 | | 22 | 5 | | 23 | 52 | | 24 | 7 | | 25 | 41 | | 26 | 3 | | 27 | 28 | | 28 | 9 | | 29 | 18 | | 30 | 8 | | 31 | 11 | | 32 | 67 | | 33 | 31 | | 34 | 11 | | 35 | 24 | | 36 | 52 | | 37 | 4 | | 38 | 5 | | 39 | 7 | | 40 | 48 | | 41 | 10 | | 42 | 13 | | 43 | 44 | | 44 | 8 | | 45 | 7 | | 46 | 6 | | 47 | 16 | | 48 | 35 | | 49 | 7 |
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| 79.51% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 8 | | totalSentences | 109 | | matches | | 0 | "were folded" | | 1 | "been killed" | | 2 | "been sealed" | | 3 | "been removed" | | 4 | "been painted" | | 5 | "been dragged" | | 6 | "been drawn" | | 7 | "was broken" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 173 | | matches | | 0 | "were sleeping" | | 1 | "was photographing" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 162 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1102 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 31 | | adverbRatio | 0.028130671506352088 | | lyAdverbCount | 8 | | lyAdverbRatio | 0.007259528130671506 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 162 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 162 | | mean | 11.25 | | std | 8.47 | | cv | 0.752 | | sampleLengths | | 0 | 13 | | 1 | 4 | | 2 | 4 | | 3 | 23 | | 4 | 18 | | 5 | 23 | | 6 | 15 | | 7 | 9 | | 8 | 21 | | 9 | 9 | | 10 | 2 | | 11 | 19 | | 12 | 23 | | 13 | 16 | | 14 | 18 | | 15 | 1 | | 16 | 1 | | 17 | 4 | | 18 | 14 | | 19 | 24 | | 20 | 12 | | 21 | 18 | | 22 | 18 | | 23 | 43 | | 24 | 20 | | 25 | 20 | | 26 | 3 | | 27 | 4 | | 28 | 35 | | 29 | 22 | | 30 | 3 | | 31 | 16 | | 32 | 8 | | 33 | 20 | | 34 | 3 | | 35 | 9 | | 36 | 5 | | 37 | 5 | | 38 | 5 | | 39 | 17 | | 40 | 28 | | 41 | 5 | | 42 | 16 | | 43 | 8 | | 44 | 1 | | 45 | 12 | | 46 | 19 | | 47 | 6 | | 48 | 24 | | 49 | 4 |
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| 70.99% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 10 | | diversityRatio | 0.46296296296296297 | | totalSentences | 162 | | uniqueOpeners | 75 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 4 | | totalSentences | 97 | | matches | | 0 | "Too small for a knife." | | 1 | "Too large for a needle." | | 2 | "Instead, she stood and walked" | | 3 | "Instead, she walked back to" |
| | ratio | 0.041 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 16 | | totalSentences | 97 | | matches | | 0 | "Her shoes clicked against the" | | 1 | "He brushed his knees and" | | 2 | "His hands were folded across" | | 3 | "She leaned closer." | | 4 | "She didn't respond." | | 5 | "She checked each one, running" | | 6 | "It was dried blood, applied" | | 7 | "She turned to the body" | | 8 | "She pointed to a section" | | 9 | "She moved toward the tunnel" | | 10 | "She straightened and walked back" | | 11 | "She had seen something like" | | 12 | "His face shifted." | | 13 | "She looked at the symbol" | | 14 | "She didn't answer." | | 15 | "She thought of Morris, of" |
| | ratio | 0.165 | |
| 94.02% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 71 | | totalSentences | 97 | | matches | | 0 | "The abandoned Tube station beneath" | | 1 | "The copper was new." | | 2 | "That was the blood." | | 3 | "Detective Harlow Quinn ducked beneath" | | 4 | "The tunnel stretched before her," | | 5 | "Her shoes clicked against the" | | 6 | "Detective Sergeant Iyer straightened from" | | 7 | "He brushed his knees and" | | 8 | "Quinn's gaze swept the station" | | 9 | "The platform stretched twenty meters" | | 10 | "A half-dozen forensic techs worked" | | 11 | "The body lay at the" | | 12 | "His hands were folded across" | | 13 | "Quinn crouched beside the body," | | 14 | "The leather of her left" | | 15 | "Iyer consulted his notebook" | | 16 | "Iyer pointed toward the far" | | 17 | "Quinn followed his gesture." | | 18 | "Someone had drawn a symbol" | | 19 | "The symbol was circular, with" |
| | ratio | 0.732 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 3 | | totalSentences | 97 | | matches | | 0 | "Now that she was closer," | | 1 | "While Iyer went to fetch" | | 2 | "As though someone had used" |
| | ratio | 0.031 | |
| 79.37% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 45 | | technicalSentenceCount | 4 | | matches | | 0 | "Detective Harlow Quinn ducked beneath the yellow crime scene tape that hung across the station entrance, its plastic edges catching on her jacket." | | 1 | "His hands were folded across his chest, fingers interlaced as though he were sleeping." | | 2 | "The symbol was circular, with lines radiating from its center in a pattern that reminded her of something she couldn't quite place." | | 3 | "Behind them, older markings showed through, faded lines and shapes that had been painted over decades ago." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 9 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 1 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 62 | | tagDensity | 0.016 | | leniency | 0.032 | | rawRatio | 0 | | effectiveRatio | 0 | |