Agent skill · research science · borghei
clinical-research
Clinical study operations — protocol structure, endpoint selection, eligibility design, sample-size and power planning, site feasibility, and documentation readiness. Use when planning, auditing, or costing a study.
Why this skill is useful
Provides domain-specific knowledge for structuring clinical study protocols and calculating sample sizes that the AI wouldn't reliably generate on its own.
What it needs
About 8k tokens when loaded. Last updated 2026-07-21. 462 stars on the source repository.
What this skill does
Clinical Research Operational support for running clinical studies: structuring a protocol so it survives review, choosing endpoints that are actually analysable, designing eligibility criteria that do not strangle accrual, planning sample size and power, and testing whether the site network can deliver the enrolment target. Scope and limits. This skill supports study operations — planning, structuring, and auditing. It is not a substitute for a qualified biostatistician, and it is not regulatory advice. The sample-size calculator assumes a simple parallel design with no interim analyses, multiplicity adjustment, covariate adjustment, or clustering; any design departing from those assumptions requires a statistician. The protocol auditor checks structure and internal consistency, not regulatory acceptability. Every artifact produced here needs sign-off from qualified biostatistics, clinical, and regulatory affairs personnel before it enters a submission. When to use this skill Planning a study and needing a defensible sample size before the budget and site count can be set Auditing a draft protocol for missing ICH E6 elements before it goes to an ethics committee or a sponsor review board Choosing between candidate endpoints where one is clinically meaningful and the other is achievable in the available sample Designing inclusion and exclusion criteria and needing to see the accrual cost of each additional restriction Assessing site feasibility — deciding how many sites, and which, are needed to hit an enrolment target inside the accrual window Diagnosing an under-accruing study and deciding between adding sites, extending the window, or amending eligibility Inputs the skill expects Study phase, design (parallel, crossover, single-arm), and blinding The primary question in a form that names the comparison Candidate endpoints with their measurement instrument and timepoint Effect size assumptions and their source — prior study, pilot, or literature Expected dropout r …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills borghei/clinical-research