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Two Sample Mr Research Planner

v0.1.0

Generates tailored two-sample Mendelian randomization study plans with four workload options, detailed workflows, validation, figures, and publication strate...

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by@shanruoyu
MIT-0
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LicenseMIT-0 · Free to use, modify, and redistribute. No attribution required.
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high confidence
✓
Purpose & Capability
The name/description (two-sample MR research planner) matches the content: stepwise study designs, instrument benchmarks, GWAS source recommendations, and deliverables. Required binaries/env/configs are none, which is appropriate for a prose planning tool.
✓
Instruction Scope
SKILL.md and the two reference files contain prescriptive guidance for designing MR studies (data selection, instrument thresholds, sensitivity analyses, figure plans). Instructions remain within the domain of study design and reporting; they reference external GWAS resources but do not tell the agent to read unrelated system files, access credentials, or transmit data to hidden endpoints.
✓
Install Mechanism
No install spec and no code files — the skill is instruction-only, which minimizes on-disk risk. There are no downloads, third-party packages, or binaries requested.
✓
Credentials
The skill declares no required environment variables, credentials, or config paths. The references point to public GWAS portals and literature; no disproportionate secret access is requested.
✓
Persistence & Privilege
The skill does not request persistent or elevated privileges (always:false). It does not attempt to modify other skills or system settings; autonomous invocation is platform-default but this skill's content does not increase that risk.
Assessment
This skill is an instruction-only MR study planner and appears internally consistent. Before relying on outputs: (1) verify any specific dataset availability/dates and citations the planner cites (LLMs can hallucinate details); (2) do not paste unpublished or participant-level genetic/clinical data into the chat — the skill assumes summary-statistic-level planning only; (3) have an MR/statistics expert review final analysis plans and code before execution or publication; (4) if you plan to attach this skill to an agent that can fetch external GWAS files, review that agent's data-access behavior and ensure it uses authorized APIs and protects any sensitive tokens. Overall the skill is coherent for its stated purpose, but standard domain validation and data-handling care are still required.

Like a lobster shell, security has layers — review code before you run it.

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License

MIT-0
Free to use, modify, and redistribute. No attribution required.
Termshttps://spdx.org/licenses/MIT-0.html

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