Agent skill · Backend & API

clinical-research

Use when designing a prospective clinical study before submission — selecting and classifying endpoints (primary / key-secondary / exploratory, with surrogate-endpoint flagging), estimating sample size and power for two-arm designs (means / proportions / survival), or scoring a study plan for feasibility and a GO / GO-WITH-CONDITIONS / REDESIGN / NO-GO phase-gate decision. Every output is an ESTIMATE plus a named human owner (clinician / biostatistician / regulatory owner) — never clinical fact, never a finished protocol. Distinct from ra-qm-team, which handles the regulatory/QM submission (IS

Alireza Rezvani23,369★ · +428/wk · 1 repos on radarProfile →
claude-codecodexcursorships scriptsMIT
Install
npx skills add alirezarezvani/claude-skills --skill clinical-research --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 11
SKILL.md size: 11 KB
Bundled scripts: yes
Version: 2.9.0
Declared author: claude-code-skills
Path: research-ops/skills/clinical-research/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 23,791 · +422 this week
Language: Python
Read our review of the source →

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# clinical-research Prospective clinical study DESIGN: endpoints, sample size / power, and phase-gate feasibility. Every output is an **estimate with stated assumptions** routed to a **named human owner**. This skill never gives clinical advice as fact and never substitutes for a biostatistician or regulatory affairs. ## Purpose R&D clinical teams, medical monitors, and biostatistics functions live at the moment between *we-have-a-hypothesis* and *we-have-a-protocol-ready-for-submission*. This skill structures three of the hardest design decisions: Three deterministic tools: 1. `sample_size_estimator.py` — Closed-form power / sample-size for two-arm **means** (Cohen's d), **proportions** (normal approximation), and **survival** (Schoenfeld events). Inflates for dropout. Prints an "ESTIMATE — confirm with a biostatistician" banner. 2. `endpoint_selector.py` — Scores candidate endpoints across 5 weighted dimensions (clinical relevance, measurability, regulatory acceptance, sensitivity-to-change, burden) and classifies each as **PRIMARY / KEY-SECONDARY / EXPLORATORY**. Penalizes unvalidated surrogate endpoints. 3. `phase_gate_scorer.py` — Scores a study plan 0-100 across recruitment f

What's inside
Steps it walks through
  1. Purpose
  2. When to use
  3. Workflow
  4. Scripts
  5. Onboarding & customization
  6. Optimize with autoresearch (opt-in)
  7. References
  8. Assumptions
  9. Anti-patterns
  10. Distinct from
  11. Quick examples
  12. Forcing-question library (Matt Pocock grill discipline)
Ships with 10 files
  • assets/protocol_synopsis_template.md
  • references/endpoint_and_power.md
  • references/study_design_canon.md
  • references/trial_operations.md
  • scripts/ar_evaluator.py
  • scripts/config_loader.py
  • scripts/endpoint_selector.py
  • scripts/onboard.py
  • scripts/phase_gate_scorer.py
  • scripts/sample_size_estimator.py
Commands it runs
python3 scripts/onboard.py            # interactive (also: --defaults, --set key=value, --reset)
python3 scripts/onboard.py --show     # see the questions + current effective config
python3 scripts/sample_size_estimator.py --sample
python3 scripts/sample_size_estimator.py --design proportions --p1 0.30 --p2 0.45 --dropout 0.15
python3 scripts/endpoint_selector.py --sample
python3 scripts/phase_gate_scorer.py --sample --output json
More from claude-skills
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About this skill
What does the clinical-research skill do?

Use when designing a prospective clinical study before submission — selecting and classifying endpoints (primary / key-secondary / exploratory, with surrogate-endpoint flagging), estimating sample size and power for two-arm designs (means / proportions / survival), or scoring a study plan for feasibility and a GO / GO-WITH-CONDITIONS / REDESIGN / NO-GO phase-gate decision. Every output is an ESTIMATE plus a named human owner (clinician / biostatistician / regulatory owner) — never clinical fact, never a finished protocol. Distinct from ra-qm-team, which handles the regulatory/QM submission (IS

How do I install it?

Run `npx skills add alirezarezvani/claude-skills --skill clinical-research --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From alirezarezvani/claude-skills, a repository with 23,791 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

Keep going