scientific-skills/Protocol Design/basic-research-design/SKILL.md
A biomedical research topic designer that generates progressive experimental subtitles and detailed research outlines based on a given subject. Use when the user wants to design a research proposal, outline experiments for a topic, or structure a biomedical study.
npx skillsauth add aipoch/medical-research-skills basic-research-designInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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This skill helps users design a biomedical research topic by generating progressive subtitles and a detailed experimental outline.
references/ for task-specific guidance.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.Skill directory: 20260316/scientific-skills/Protocol Design/basic-research-design
No packaged executable script was detected.
Use the documented workflow in SKILL.md together with the references/assets in this folder.
Example run plan:
See ## Workflow above for related details.
SKILL.md.references/ contains supporting rules, prompts, or checklists.Follow these steps to generate the research design.
references/prompt_templates.md) to generate 6 progressive subtitles.<Subject>: The user's subject.references/prompt_templates.md) to generate the detailed outline.<Subject>: The original subject.<Subtitles>: The output from Step 1.Present the final result in Markdown, following the format specified in the prompt templates.
basic_research_design_result.md unless the skill documentation defines a better convention.Run this minimal verification path before full execution when possible:
No local script validation step is required for this skill.
Expected output format:
Result file: basic_research_design_result.md
Validation summary: PASS/FAIL with brief notes
Assumptions: explicit list if any
tools
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development
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tools
Plans confounder control, variable adjustment logic, and bias mitigation strategies at the protocol stage for clinical, epidemiologic, translational, observational, and biomarker studies. Always use this skill when a user needs to identify major confounders, decide which variables should or should not be adjusted for, compare matching/stratification/weighting approaches, anticipate selection or measurement bias, or pressure-test a study design before execution. Focus on bias sensing, causal structure awareness, variable-role classification, and critical design review rather than generic statistical advice.
testing
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