Clinical study design. Select and classify endpoints, estimate sample size / power (means / proportions / survival), and score a study plan for a GO / GO-WITH-CONDITIONS / REDESIGN / NO-GO phase-gate decision. Every output is an ESTIMATE plus a named clinical owner — never clinical fact. Direct invocation of the clinical-research skill.
Copy the command definition below into:
~/.claude/commands/cs-clinical-research-alirezarezvani-2.md---
description: Clinical study design. Select and classify endpoints, estimate sample size / power (means / proportions / survival), and score a study plan for a GO / GO-WITH-CONDITIONS / REDESIGN / NO-GO phase-gate decision. Every output is an ESTIMATE plus a named clinical owner — never clinical fact. Direct invocation of the clinical-research skill.
argument-hint: "<study context: indication, design, endpoints, effect size, target enrollment>"
---
# /cs:clinical-research — Endpoint selection + sample-size + phase-gate feasibility
Run the `clinical-research` skill on this input:
**$ARGUMENTS**
## Three-tool workflow
1. **`endpoint_selector.py`** — Score candidate endpoints across clinical relevance, measurability, regulatory acceptance, sensitivity-to-change, and burden. Classify PRIMARY / KEY-SECONDARY / EXPLORATORY. Flags unvalidated surrogates (cannot be primary). Industry tuning via `--profile`.
2. **`sample_size_estimator.py`** — Closed-form power / sample size for two-arm means (Cohen's d), proportions (normal approx), or survival (Schoenfeld events). Inflates for dropout. The effect/difference/HR must trace to a published or anchor-based source.
3. **`phase_gate_scorer.py`** — Score the study plan 0-100 across recruitment feasibility, endpoint readiness, statistical power, operational complexity, and budget fit. Verdict + named owners (PI, Medical Monitor, Biostatistician, Regulatory Owner).
## Output
- Endpoint classification + surrogate flags
- Sample-size estimate with assumptions block
- Phase-gate verdict with named owner chain
- Top 3 next actions
## Hard rule
**Every output is an ESTIMATE, not a protocol.** A biostatistician, medical monitor, and regulatory owner sign the final design.
## First run + optimization
- **Onboard first:** `python3 skills/clinical-research/scripts/onboard.py` (area, alpha, power, dropout, named owners) — saved config pre-configures every tool. `--show` lists the questions.
- **Optimize (opt-in):** only if the user asks to optimize/run a loop, hand off to autoresearch via `skills/clinical-research/scripts/ar_evaluator.py` (`feasibility_composite`, higher is better).
## Distinct from
- `ra-qm-team` — that's the regulatory **submission**. This designs the **study**.
- `research/grants` — that **finds funding**. This **designs the trial**.
- `product-team/experiment-designer` — that's a **product A/B**. This is a **clinical trial**.
Clinical study design. Select and classify endpoints, estimate sample size / power (means / proportions / survival), and score a study plan for a GO. Slash command for Claude Code, Codex CLI, Gemini CLI.
/cs:deep-research <question> — Disciplined multi-source investigation for a high-stakes question. Reframes into falsifiable hypotheses, plans, fans out parallel search sub-agents, triangulates every thesis against >=3 independent sources, saves each source to its own file with verbatim quotes, runs an adversarial pass, and emits an auditable, reusable research folder with a refresh protocol. The heavyweight alternative to the fast research router.
/cs:grants <research-idea> — NIH funding intelligence. 6-Q grill-me intake (idea + career stage + prelim + environment + posture + institutes) → 5-facet Consensus positioning + RePORTER POST institute mapping + NOSI fetches → 9-section .docx with mandatory program officer recommendation.