| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 4 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 7 | | tagDensity | 0.571 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 84.08% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 314 | | 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) | |
| 68.15% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 314 | | totalAiIsms | 2 | | found | | | highlights | | |
| 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 | 10 | | matches | (empty) | |
| 0.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 10 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 13 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 51 | | ratio | 0 | | matches | (empty) | |
| 0.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 5 | | markdownWords | 76 | | totalWords | 312 | | ratio | 0.244 | | matches | | 0 | "ooze in a petri dish" | | 1 | "cross knows this shouldn't be possible... But it is" | | 2 | "Quinn interjected" | | 3 | "God, she hated this place. Hatred so thick you could still smell it, taste the blood in the air like old wine and wool smoke. The murder investigation at the Loveless campgrounds may have put Quinn on the trail of something big—if only she'd have just a little more time" | | 4 | "Action: See if she lets you look at the body" |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 3 | | unquotedAttributions | 0 | | matches | (empty) | |
| 37.64% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 10 | | wordCount | 178 | | uniqueNames | 6 | | maxNameDensity | 2.25 | | worstName | "Quinn" | | maxWindowNameDensity | 2 | | worstWindowName | "Quinn" | | discoveredNames | | Harlow | 1 | | Quinn | 4 | | Anderson | 2 | | Jackisms | 1 | | Loveless | 1 | | See | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Anderson" | | 3 | "Jackisms" |
| | places | | | globalScore | 0.376 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 8 | | 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 | 312 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 13 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 10 | | mean | 31.2 | | std | 18.31 | | cv | 0.587 | | sampleLengths | | 0 | 21 | | 1 | 30 | | 2 | 9 | | 3 | 53 | | 4 | 31 | | 5 | 13 | | 6 | 65 | | 7 | 30 | | 8 | 50 | | 9 | 10 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 10 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 28 | | matches | (empty) | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 1 | | semicolonCount | 0 | | flaggedSentences | 1 | | totalSentences | 13 | | ratio | 0.077 | | matches | | 0 | "*God, she hated this place. Hatred so thick you could still smell it, taste the blood in the air like old wine and wool smoke. The murder investigation at the Loveless campgrounds may have put Quinn on the trail of something big—if only she'd have just a little more time*" |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 194 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 5 | | adverbRatio | 0.02577319587628866 | | lyAdverbCount | 1 | | lyAdverbRatio | 0.005154639175257732 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 13 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 13 | | mean | 24 | | std | 14.75 | | cv | 0.615 | | sampleLengths | | 0 | 21 | | 1 | 30 | | 2 | 6 | | 3 | 3 | | 4 | 12 | | 5 | 41 | | 6 | 31 | | 7 | 13 | | 8 | 19 | | 9 | 46 | | 10 | 30 | | 11 | 50 | | 12 | 10 |
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| 100.00% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 0 | | diversityRatio | 0.9230769230769231 | | totalSentences | 13 | | uniqueOpeners | 12 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 9 | | matches | | 0 | "very little had begun to" |
| | ratio | 0.111 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 0 | | totalSentences | 9 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 5 | | totalSentences | 9 | | matches | | 0 | "Detective Harlow Quinn squinted at" | | 1 | "*cross knows this shouldn't be" | | 2 | "Quinn interjected* \"- and my" | | 3 | "Anderson looked ready to shoot" | | 4 | "*God, she hated this place." |
| | ratio | 0.556 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 9 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 4 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 4 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 2 | | fancyCount | 2 | | fancyTags | | 0 | "Quinn interjected (interject)" | | 1 | "she snarled (snarl)" |
| | dialogueSentences | 7 | | tagDensity | 0.286 | | leniency | 0.571 | | rawRatio | 1 | | effectiveRatio | 0.571 | |