| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 10 | | adverbTagCount | 1 | | adverbTags | | 0 | "She knelt again [again]" |
| | dialogueSentences | 41 | | tagDensity | 0.244 | | leniency | 0.488 | | rawRatio | 0.1 | | effectiveRatio | 0.049 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 931 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 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) | |
| 62.41% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 931 | | totalAiIsms | 7 | | found | | | highlights | | 0 | "scanning" | | 1 | "glistening" | | 2 | "traced" | | 3 | "pulsed" | | 4 | "trembled" | | 5 | "footsteps" | | 6 | "echoing" |
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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 | 79 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 79 | | 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 | 1 | | markdownWords | 1 | | totalWords | 922 | | ratio | 0.001 | | matches | | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 7 | | unquotedAttributions | 0 | | matches | (empty) | |
| 57.12% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 29 | | wordCount | 646 | | uniqueNames | 6 | | maxNameDensity | 1.86 | | worstName | "Cole" | | maxWindowNameDensity | 3 | | worstWindowName | "Cole" | | discoveredNames | | Tube | 1 | | Sergeant | 1 | | Cole | 12 | | Quinn | 12 | | Eva | 2 | | Kowalski | 1 |
| | persons | | 0 | "Sergeant" | | 1 | "Cole" | | 2 | "Quinn" | | 3 | "Eva" | | 4 | "Kowalski" |
| | places | (empty) | | globalScore | 0.571 | | windowScore | 0.667 | |
| 51.96% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 51 | | glossingSentenceCount | 2 | | matches | | 0 | "looked like something clawed its way out" | | 1 | "seemed thicker like the shadows were breathing" |
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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 | 922 | | matches | (empty) | |
| 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 | 45 | | mean | 20.49 | | std | 16.25 | | cv | 0.793 | | sampleLengths | | 0 | 55 | | 1 | 26 | | 2 | 7 | | 3 | 24 | | 4 | 41 | | 5 | 3 | | 6 | 29 | | 7 | 34 | | 8 | 5 | | 9 | 12 | | 10 | 7 | | 11 | 6 | | 12 | 65 | | 13 | 7 | | 14 | 27 | | 15 | 2 | | 16 | 25 | | 17 | 17 | | 18 | 57 | | 19 | 4 | | 20 | 6 | | 21 | 8 | | 22 | 59 | | 23 | 9 | | 24 | 14 | | 25 | 7 | | 26 | 10 | | 27 | 21 | | 28 | 52 | | 29 | 18 | | 30 | 19 | | 31 | 6 | | 32 | 31 | | 33 | 7 | | 34 | 33 | | 35 | 14 | | 36 | 10 | | 37 | 15 | | 38 | 23 | | 39 | 28 | | 40 | 21 | | 41 | 21 | | 42 | 6 | | 43 | 8 | | 44 | 23 |
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| 83.06% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 5 | | totalSentences | 79 | | matches | | 0 | "was frozen" | | 1 | "were curled" | | 2 | "were covered" | | 3 | "were rusted" | | 4 | "were scuffed" |
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| 84.06% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 115 | | matches | | 0 | "were breathing" | | 1 | "was staring" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 7 | | semicolonCount | 0 | | flaggedSentences | 7 | | totalSentences | 109 | | ratio | 0.064 | | matches | | 0 | "She touched the back of his hand—still warm." | | 1 | "The walls were covered in graffiti, but one symbol stood out—a jagged sigil, fresh, the paint still glistening." | | 2 | "A faint residue clung to the fabric—same texture, same sheen." | | 3 | "But something glinted near the edge—a small brass object half-buried in the gravel." | | 4 | "No mud, no dirt—just dust." | | 5 | "And his clothes—cheap, but new." | | 6 | "The screen lit up with a single name—Eva Kowalski." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 653 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 23 | | adverbRatio | 0.03522205206738132 | | lyAdverbCount | 4 | | lyAdverbRatio | 0.006125574272588055 | |
| 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 | 8.46 | | std | 5.26 | | cv | 0.622 | | sampleLengths | | 0 | 10 | | 1 | 13 | | 2 | 16 | | 3 | 16 | | 4 | 16 | | 5 | 6 | | 6 | 4 | | 7 | 4 | | 8 | 3 | | 9 | 16 | | 10 | 8 | | 11 | 5 | | 12 | 17 | | 13 | 11 | | 14 | 8 | | 15 | 3 | | 16 | 6 | | 17 | 23 | | 18 | 5 | | 19 | 18 | | 20 | 11 | | 21 | 5 | | 22 | 2 | | 23 | 10 | | 24 | 5 | | 25 | 2 | | 26 | 6 | | 27 | 14 | | 28 | 10 | | 29 | 6 | | 30 | 25 | | 31 | 10 | | 32 | 5 | | 33 | 2 | | 34 | 10 | | 35 | 17 | | 36 | 2 | | 37 | 9 | | 38 | 16 | | 39 | 4 | | 40 | 13 | | 41 | 13 | | 42 | 8 | | 43 | 13 | | 44 | 10 | | 45 | 2 | | 46 | 11 | | 47 | 2 | | 48 | 2 | | 49 | 4 |
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| 56.88% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 3 | | diversityRatio | 0.3577981651376147 | | totalSentences | 109 | | uniqueOpeners | 39 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 71 | | matches | (empty) | | ratio | 0 | |
| 67.89% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 27 | | totalSentences | 71 | | matches | | 0 | "She adjusted the worn leather" | | 1 | "His breath fogged in the" | | 2 | "She ignored the jab." | | 3 | "He jerked his chin toward" | | 4 | "His fingers were curled into" | | 5 | "She touched the back of" | | 6 | "It looked like something clawed" | | 7 | "She pointed at the sigil." | | 8 | "She traced the edges of" | | 9 | "She knelt again, brushing her" | | 10 | "She stood, wiping her gloves" | | 11 | "She shook her head" | | 12 | "She picked it up, turning" | | 13 | "She pocketed it" | | 14 | "She turned back to the" | | 15 | "She reached in and pulled" | | 16 | "She slipped it into an" | | 17 | "She walked to the edge" | | 18 | "She pulled out her phone" | | 19 | "She stepped closer to the" |
| | ratio | 0.38 | |
| 2.25% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 65 | | totalSentences | 71 | | matches | | 0 | "The abandoned Tube station smelled" | | 1 | "Quinn stepped over the police" | | 2 | "The air hummed with the" | | 3 | "She adjusted the worn leather" | | 4 | "Detective Sergeant Cole stood near" | | 5 | "His breath fogged in the" | | 6 | "She ignored the jab." | | 7 | "He jerked his chin toward" | | 8 | "Quinn crouched beside the corpse." | | 9 | "The man’s face was frozen" | | 10 | "His fingers were curled into" | | 11 | "She touched the back of" | | 12 | "Quinn stood, scanning the platform." | | 13 | "The walls were covered in" | | 14 | "It looked like something clawed" | | 15 | "She pointed at the sigil." | | 16 | "Quinn pulled a pair of" | | 17 | "She traced the edges of" | | 18 | "The paint was thick, almost" | | 19 | "She knelt again, brushing her" |
| | ratio | 0.915 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 71 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 27 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 10 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 2 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 41 | | tagDensity | 0.049 | | leniency | 0.098 | | rawRatio | 0 | | effectiveRatio | 0 | |