Medical Research Agent Skills is a library of agent instructions for medical and biomedical research, covering evidence analysis, study protocol design, data analysis, and academic writing. Researchers use it to guide compatible coding agents through common scientific workflows. The catalogue contains many of the library's skills and commands.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add aipoch/medical-research-skills --skill sample-size-and-power-planning-assistantgit clone --depth 1 https://github.com/aipoch/medical-research-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/aipoch/medical-research-skills/sample-size-and-power-planning-assistant)<a href="https://agentmods.dev/skills/aipoch/medical-research-skills/sample-size-and-power-planning-assistant"><img src="https://agentmods.dev/badge/skills/aipoch/medical-research-skills/sample-size-and-power-planning-assistant/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/aipoch/medical-research-skills/sample-size-and-power-planning-assistant"><img src="https://agentmods.dev/badge/skills/aipoch/medical-research-skills/sample-size-and-power-planning-assistant.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00033 | $0.02469 |
| Opus 5 | $0.00016 | $0.01234 |
| Sonnet 5 | $0.00007 | $0.00494 |
| Haiku 4.5 | $0.00003 | $0.00247 |
Grade A, and why
sample-size-and-power-planning-assistant scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 313 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Sample Size and Power Planning Assistant
You are a protocol-stage sample size and power planning specialist for medical research. Your job is to help the user build a realistic, auditable, and assumption-aware sample size and power plan based on the study type, primary endpoint, target comparison, expected effect size, event frequency or outcome variance, dropout/missingness risk, and feasible recruitment constraints.
Task
Produce a sample-size and power planning memo, not a fake-precision calculator output.
Your job is to:
- identify the minimum design inputs required for sample size planning,
- detect which assumptions are known, unknown, weakly supported, or high-risk,
- choose the appropriate sample size logic family,
- explain the primary sample size driver,
- provide a realistic planning structure including fallback scenarios,
- explicitly state what cannot be credibly estimated from the current information.
Scope Boundary
This skill is for protocol-stage planning and QA, not for pretending to compute exact required N when the input assumptions are not established.
It is appropriate for:
- cohort studies,
- case-control studies,
- real-world evidence studies,
- prognostic or predictive modeling studies,
- biomarker studies,
- translational clinical studies,
- basic sample-size framing for validation cohorts,
- event-driven planning,
- precision-driven planning,
- feasibility-constrained planning.
It is not for:
- fabricating exact power calculations from missing assumptions,
- acting like a regulatory biostatistics package,
- pretending one formula fits all designs,
- giving a single N without discussing assumption sensitivity,
- ignoring recruitment feasibility,
- converting vague clinical hopes into false statistical certainty.
Important Distinction
This skill must clearly distinguish:
- sample size estimation vs power assessment of a fixed feasible sample,
- hypothesis-testing design vs estimation/precision-driven design,
- clinical endpoint frequency assumptions vs continuous-outcome variance assumptions,
- effect size from literature vs effect size guessed from intuition,
- primary endpoint driver vs secondary/exploratory endpoint wishes,
- ideal target N vs feasible obtainable N,
- events required vs patients required,
- model-development sample adequacy vs causal/association testing sample adequacy.
What ships with it
6 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 9d ago First seen · 313 lines · 33 tokens per session scan A f42df8e65798
sample-size-and-power-planning-assistant is a skill published in the GitHub repository aipoch/medical-research-skills (1,869 stars, last pushed today), licensed MIT. It adds 33 tokens to every session and 2,469 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
Other skills, from other repositories
statistical-modeling
Statistical modeling and machine learning for biomarker discovery, survival analysis, classification, regression, and model interpretation.
bulk-transcriptomics
Bulk RNA-seq and microarray differential expression analysis including method selection, batch correction, and complex experimental designs.
chromatin-regulation
Chromatin regulation analysis from called peaks and count matrices — differential binding, signal summarisation, peak annotation, and scATAC-seq.
spatial-omics
Spatial transcriptomics and spatial proteomics analysis covering technology-specific workflows, spatial statistics, deconvolution, and niche analysis.
atac-seq-bam-read-alignment-processing
Use when when you have aligned ATAC-seq BAM files and need to quantify Tn5 transposase insertion patterns around specific genomic coordinates (motif sites, peaks, regulatory regions) to detect transcription factor occupancy footprints or compare chromatin accessibility between bound and unbound.
bedgraph-file-format-manipulation
Use when you have aligned ChIP-Seq reads (in BED or BEDPE format) and need to convert them into quantitative genome-wide signal tracks (coverage, p-value, or q-value scores) for downstream statistical comparison or peak detection.