| name | medical-translation |
| description | Use medical translation for academic writing workflows that need structured execution, explicit assumptions, and clear output boundaries. |
| license | MIT |
| author | AIPOCH |
Source: https://github.com/aipoch/medical-research-skills
Medical Translation - Precise Medical Terminology Translation
When to Use
- Use this skill when the task needs Use medical translation for academic writing workflows that need structured execution, explicit assumptions, and clear output boundaries.
- Use this skill for academic writing tasks that require explicit assumptions, bounded scope, and a reproducible output format.
- Use this skill when you need a documented fallback path for missing inputs, execution errors, or partial evidence.
Key Features
- Scope-focused workflow aligned to: Use medical translation for academic writing workflows that need structured execution, explicit assumptions, and clear output boundaries.
- Packaged executable path(s):
scripts/main.py plus 1 additional script(s).
- Reference material available in
references/ for task-specific guidance.
- Structured execution path designed to keep outputs consistent and reviewable.
Dependencies
See ## Prerequisites above for related details.
Python: 3.10+. Repository baseline for current packaged skills.Third-party packages: not explicitly version-pinned in this skill package. Add pinned versions if this skill needs stricter environment control.
Example Usage
See ## Usage above for related details.
cd "20260318/scientific-skills/Academic Writing/medical-translation"
python -m py_compile scripts/main.py
python scripts/main.py --help
Example run plan:
- Confirm the user input, output path, and any required config values.
- Edit the in-file
CONFIG block or documented parameters if the script uses fixed settings.
- Run
python scripts/main.py with the validated inputs.
- Review the generated output and return the final artifact with any assumptions called out.
Implementation Details
See ## Workflow above for related details.
- Execution model: validate the request, choose the packaged workflow, and produce a bounded deliverable.
- Input controls: confirm the source files, scope limits, output format, and acceptance criteria before running any script.
- Primary implementation surface:
scripts/main.py with additional helper scripts under scripts/.
- Reference guidance:
references/ contains supporting rules, prompts, or checklists.
- Parameters to clarify first: input path, output path, scope filters, thresholds, and any domain-specific constraints.
- Output discipline: keep results reproducible, identify assumptions explicitly, and avoid undocumented side effects.
Quick Check
Use this command to verify that the packaged script entry point can be parsed before deeper execution.
python -m py_compile scripts/main.py
Audit-Ready Commands
Use these concrete commands for validation. They are intentionally self-contained and avoid placeholder paths.
python -m py_compile scripts/main.py
python scripts/smoke_test.py
python scripts/smoke_test.py
Workflow
- Confirm the user objective, required inputs, and non-negotiable constraints before doing detailed work.
- Validate that the request matches the documented scope and stop early if the task would require unsupported assumptions.
- Use the packaged script path or the documented reasoning path with only the inputs that are actually available.
- Return a structured result that separates assumptions, deliverables, risks, and unresolved items.
- If execution fails or inputs are incomplete, switch to the fallback path and state exactly what blocked full completion.
Audit Note
The main script expects positional translation arguments and returns a non-zero status for argument-only help calls. Audit validation therefore uses scripts/smoke_test.py as the deterministic fallback command for structural verification.
Description
Focuses on precise translation of medical terminology (such as Chinese-English translation, Spanish-English translation), rather than general translation. Ensures accurate communication of medical concepts across different languages.
Usage
Provide medical terms or paragraphs, specify source and target languages, and obtain professional-grade medical translation.
Parameters
- term: Medical term or text to be translated
- source_lang: Source language (e.g., Chinese, English)
- target_lang: Target language (e.g., English, Chinese)
- context: Optional, provide context for more accurate translation
Example
Input:
- term: "Acute Myeloid Leukemia"
- source_lang: English
- target_lang: Chinese
Output: "Acute myeloid leukemia (AML)"
Risk Assessment
| Risk Indicator | Assessment | Level |
|---|
| Code Execution | Python/R scripts executed locally | Medium |
| Network Access | No external API calls | Low |
| File System Access | Read input files, write output files | Medium |
| Instruction Tampering | Standard prompt guidelines | Low |
| Data Exposure | Output files saved to workspace | Low |
Security Checklist
Prerequisites
No additional Python packages required.
Evaluation Criteria
Success Metrics
Test Cases
- Basic Functionality: Standard input → Expected output
- Edge Case: Invalid input → Graceful error handling
- Performance: Large dataset → Acceptable processing time
Lifecycle Status
- Current Stage: Draft
- Next Review Date: 2026-03-06
- Known Issues: None
- Planned Improvements:
- Performance optimization
- Additional feature support
Output Requirements
Every final response should make these items explicit when they are relevant:
- Objective or requested deliverable
- Inputs used and assumptions introduced
- Workflow or decision path
- Core result, recommendation, or artifact
- Constraints, risks, caveats, or validation needs
- Unresolved items and next-step checks
Error Handling
- If required inputs are missing, state exactly which fields are missing and request only the minimum additional information.
- If the task goes outside the documented scope, stop instead of guessing or silently widening the assignment.
- If
scripts/main.py fails, report the failure point, summarize what still can be completed safely, and provide a manual fallback.
- Do not fabricate files, citations, data, search results, or execution outcomes.
Input Validation
This skill accepts requests that match the documented purpose of medical-translation and include enough context to complete the workflow safely.
Do not continue the workflow when the request is out of scope, missing a critical input, or would require unsupported assumptions. Instead respond:
medical-translation only handles its documented workflow. Please provide the missing required inputs or switch to a more suitable skill.
References
Response Template
Use the following fixed structure for non-trivial requests:
- Objective
- Inputs Received
- Assumptions
- Workflow
- Deliverable
- Risks and Limits
- Next Checks
If the request is simple, you may compress the structure, but still keep assumptions and limits explicit when they affect correctness.
