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Strategies for translating academic papers while preserving technical accuracy
Passed 12 of 25 test cases with the skill, and 7 of 25 without it.
and 7 more in the full report
7 fixed5 passed either way11 still failing2 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 7 test cases the skill fixed. Same model, same prompt, with and without the skill.
What is the Python function signature and return type structure for a terminology enforcement helper that takes a translated text string and a glossary list, corrects term variants, and tracks warnings?
| Checked | Without skill | With skill |
|---|---|---|
| Names the terminology enforcement helper enforce_terminology. | Passed | Passed |
| Returns a tuple where the second item is a list of warning messages. | Missed | Passed |
The instructions your model reads when the skill loads.
A skill for translating academic papers, theses, and research documents between languages while preserving technical precision, citation integrity, and discipline-specific terminology. Covers workflow design, terminology management, and quality assurance.
Source Document
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1. Document Preparation
- Extract text (OCR if scanned)
- Identify formulas, figures, tables (do NOT translate these)
- Build terminology glossary
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2. Segmentation
- Split into translatable units (sentences/paragraphs)
- Tag non-translatable elements: equations, citations, proper nouns
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3. Translation
- Apply machine translation (first pass)
- Human post-editing (second pass)
- Terminology consistency check (third pass)
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4. Quality Assurance
- Back-translation verification (sample)
- Domain expert review
- Formatting and citation check
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Target Document
test cases passed, vs 7 / 25 without
More skills from the same source and nearby in the registry, with their headline benchmark lift.