| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 9 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 36 | | tagDensity | 0.25 | | leniency | 0.5 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 82.27% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 846 | | totalAiIsmAdverbs | 3 | | 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) | |
| 11.35% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 846 | | totalAiIsms | 15 | | found | | | highlights | | 0 | "gloom" | | 1 | "pulse" | | 2 | "glistening" | | 3 | "weight" | | 4 | "pulsed" | | 5 | "flickered" | | 6 | "etched" | | 7 | "flicked" | | 8 | "standard" | | 9 | "tracing" | | 10 | "navigate" | | 11 | "racing" | | 12 | "silence" |
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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 | 0 | | narrationSentences | 71 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 0 | | narrationSentences | 71 | | filterMatches | | | hedgeMatches | (empty) | |
| 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 | 24 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 1 | | markdownWords | 1 | | totalWords | 844 | | ratio | 0.001 | | matches | | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 8 | | unquotedAttributions | 0 | | matches | (empty) | |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 30 | | wordCount | 593 | | uniqueNames | 4 | | maxNameDensity | 2.87 | | worstName | "Quinn" | | maxWindowNameDensity | 5.5 | | worstWindowName | "Quinn" | | discoveredNames | | | persons | | | places | (empty) | | globalScore | 0.067 | | windowScore | 0 | |
| 38.89% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 45 | | glossingSentenceCount | 2 | | matches | | 0 | "as if reaching for something" | | 1 | "looked like blood" |
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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 | 844 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 98 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 46 | | mean | 18.35 | | std | 14.2 | | cv | 0.774 | | sampleLengths | | 0 | 51 | | 1 | 4 | | 2 | 69 | | 3 | 18 | | 4 | 28 | | 5 | 42 | | 6 | 7 | | 7 | 13 | | 8 | 39 | | 9 | 6 | | 10 | 5 | | 11 | 13 | | 12 | 34 | | 13 | 10 | | 14 | 39 | | 15 | 16 | | 16 | 1 | | 17 | 14 | | 18 | 12 | | 19 | 1 | | 20 | 46 | | 21 | 3 | | 22 | 10 | | 23 | 12 | | 24 | 14 | | 25 | 21 | | 26 | 10 | | 27 | 23 | | 28 | 7 | | 29 | 16 | | 30 | 8 | | 31 | 11 | | 32 | 27 | | 33 | 18 | | 34 | 24 | | 35 | 22 | | 36 | 35 | | 37 | 13 | | 38 | 6 | | 39 | 8 | | 40 | 15 | | 41 | 21 | | 42 | 18 | | 43 | 15 | | 44 | 14 | | 45 | 5 |
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| 80.55% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 5 | | totalSentences | 71 | | matches | | 0 | "was frozen" | | 1 | "were covered" | | 2 | "were curled" | | 3 | "been dragged" | | 4 | "was clutched" | | 5 | "was scrawled" |
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| 77.68% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 109 | | matches | | 0 | "was watching" | | 1 | "weren't adding" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 1 | | semicolonCount | 0 | | flaggedSentences | 1 | | totalSentences | 98 | | ratio | 0.01 | | matches | | 0 | "The walls were covered in layers of tags, but one stood out—a fresh sigil painted in what looked like blood." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 596 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 23 | | adverbRatio | 0.03859060402684564 | | lyAdverbCount | 7 | | lyAdverbRatio | 0.01174496644295302 | |
| 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 | 8.6 | | std | 5.42 | | cv | 0.63 | | sampleLengths | | 0 | 10 | | 1 | 13 | | 2 | 18 | | 3 | 10 | | 4 | 4 | | 5 | 18 | | 6 | 24 | | 7 | 13 | | 8 | 14 | | 9 | 18 | | 10 | 23 | | 11 | 5 | | 12 | 7 | | 13 | 4 | | 14 | 12 | | 15 | 9 | | 16 | 10 | | 17 | 7 | | 18 | 12 | | 19 | 1 | | 20 | 7 | | 21 | 20 | | 22 | 12 | | 23 | 6 | | 24 | 3 | | 25 | 2 | | 26 | 6 | | 27 | 5 | | 28 | 2 | | 29 | 15 | | 30 | 11 | | 31 | 8 | | 32 | 10 | | 33 | 9 | | 34 | 11 | | 35 | 8 | | 36 | 11 | | 37 | 2 | | 38 | 5 | | 39 | 9 | | 40 | 1 | | 41 | 3 | | 42 | 11 | | 43 | 12 | | 44 | 10 | | 45 | 15 | | 46 | 21 | | 47 | 3 | | 48 | 8 | | 49 | 2 |
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| 62.59% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 2 | | diversityRatio | 0.3877551020408163 | | totalSentences | 98 | | uniqueOpeners | 38 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 66 | | matches | | 0 | "Just a single bone token" | | 1 | "Then the lights went out." |
| | ratio | 0.03 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 14 | | totalSentences | 66 | | matches | | 0 | "She adjusted the worn leather" | | 1 | "His face was frozen in" | | 2 | "She plucked it between gloved" | | 3 | "It pulsed faintly under her" | | 4 | "She moved to the edge" | | 5 | "she ordered, swinging herself down" | | 6 | "She picked it up, brushing" | | 7 | "She turned the compass over." | | 8 | "She looked up." | | 9 | "She stepped carefully over the" | | 10 | "Her satchel thumped against her" | | 11 | "She pried them open." | | 12 | "She unfolded it carefully." | | 13 | "She looked at the compass," |
| | ratio | 0.212 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 63 | | totalSentences | 66 | | matches | | 0 | "The abandoned Tube station reeked" | | 1 | "Quinn stepped over the police" | | 2 | "The beam of her torch" | | 3 | "A uniformed officer nodded at" | | 4 | "She adjusted the worn leather" | | 5 | "The victim lay sprawled near" | | 6 | "His face was frozen in" | | 7 | "A pool of dark liquid" | | 8 | "Quinn crouched beside the body," | | 9 | "The officer shifted his weight," | | 10 | "Quinn's fingers hovered over the" | | 11 | "She plucked it between gloved" | | 12 | "The edges were rough, carved" | | 13 | "The officer shrugged" | | 14 | "Quinn stood, her gaze sweeping" | | 15 | "The walls were covered in" | | 16 | "It pulsed faintly under her" | | 17 | "The officer squinted." | | 18 | "The sigil flickered again, then" | | 19 | "Quinn exhaled through her nose." |
| | ratio | 0.955 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 66 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 24 | | technicalSentenceCount | 1 | | matches | | 0 | "The victim lay sprawled near the edge of the platform, one arm twisted beneath him, the other flung out as if reaching for something." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 9 | | uselessAdditionCount | 3 | | matches | | 0 | "Quinn crouched, her sharp jaw tightening as she took in the details" | | 1 | "The officer shifted, his radio crackling with static" | | 2 | "Eva turned, her thumb brushing the verdigris patina" |
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| 94.44% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 2 | | fancyCount | 2 | | fancyTags | | 0 | "she muttered (mutter)" | | 1 | "she ordered (order)" |
| | dialogueSentences | 36 | | tagDensity | 0.056 | | leniency | 0.111 | | rawRatio | 1 | | effectiveRatio | 0.111 | |