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 gseagit 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/gsea)<a href="https://agentmods.dev/skills/aipoch/medical-research-skills/gsea"><img src="https://agentmods.dev/badge/skills/aipoch/medical-research-skills/gsea/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/gsea"><img src="https://agentmods.dev/badge/skills/aipoch/medical-research-skills/gsea.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 | $0.00025 | $0.02725 |
| Opus 5 | $0.00013 | $0.01362 |
| Sonnet 5 | $0.00005 | $0.00545 |
| Haiku 4.5 | $0.00003 | $0.00272 |
Grade A, and why
gsea 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 13d 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 — 183 lines — stays where its author put it; the contents beside it link to each section on GitHub.
When to read external files
| Situation | Read | Purpose |
|---|---|---|
| Need algorithm details | references/algorithm.md |
Statistical method and formulas |
| Need to run an analysis | scripts/main.R |
Full command reference |
| Hit an error | references/troubleshooting.md |
Look up error codes and fixes |
| Need CLI examples | references/cli-guide.md |
Worked argument examples |
Scope
Use this skill for:
- Running GSEA on a gene list ranked by a statistic
- Generating enrichment curve plots from existing
enrichGSEA.csvandgsea_running_scores.csv - Smoke-testing the pipeline with
tests/data/sample_deg_results.csv
Do not use it for:
- Differential expression on raw expression matrices
- Single-sample ssGSEA
- Network analysis or multi-omics integration
Usage
Analysis mode:
Rscript scripts/main.R --input tests/data/sample_deg_results.csv --outdir ./GSEA_analysis --type KEGG --species human --seed 42 --timeout 300
Plot mode:
Rscript scripts/main.R --running_file ./GSEA_analysis/Table/gsea_running_scores.csv --enrich_file ./GSEA_analysis/Table/enrichGSEA.csv --plot_output ./GSEA_analysis/plot/gsea_plot.pdf --top_n 5 --plot_format pdf --seed 42 --timeout 300
See references/cli-guide.md for more.
Mode selection:
- Passing only
--inputruns analysis mode - Passing both
--running_fileand--enrich_fileruns plot mode - If both sets of arguments are provided, plot mode takes precedence; analysis mode is skipped and a warning is logged
Arguments
Analysis-mode arguments
| Short | Long | Type | Default | Required | Description |
|---|---|---|---|---|---|
-i |
--input |
character | NULL |
yes | Input CSV file |
-o |
--outdir |
character | GSEA_analysis |
no | Output directory |
-g |
--gene_col |
character | name |
no | Gene column name |
-f |
--fc_col |
character | logFC |
no | Ranking-statistic column name |
-t |
--type |
character | KEGG |
no | Gene-set type: KEGG, HALLMARKS, GO_BP, GO_MF, GO_CC. With a preloaded RDS, HALLMARKS is automatically mapped to the asset key Hallmarks |
-s |
--species |
character | human |
no | Species: human, mouse, rat |
-p |
--pvalue_cutoff |
numeric | 0.05 |
no | Significance threshold |
-m |
--method |
character | fgsea |
no | GSEA backend: fgsea or DOSE |
-c |
--chunk_size |
numeric | 1000 |
no | Chunk size for large gene-set conversion |
-r |
--rds_path |
character | NULL |
no | Path to a pre-stored gene-set RDS |
-v |
--verbose |
logical | FALSE |
no | Verbose logging |
--seed |
integer | 42 |
no | Random seed | |
--timeout |
integer | 300 |
no | Timeout in seconds; <=0 disables it |
|
-h |
--help |
logical | FALSE |
no | Show help |
What ships with it
11 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.
- assets/ssGSEA.rds 2739 KB
- eval_report_gsea_result.json 15 KB
- references/algorithm.md 1.2 KB
- references/cli-guide.md 1.4 KB
- references/troubleshooting.md 1.6 KB
- scripts/functions.R 7.4 KB
- scripts/main.R 13 KB
- scripts/plot_functions.R 17 KB
- scripts/run_analysis.R 12 KB
- scripts/utils.R 6.1 KB
- tests/data/sample_deg_results.csv 1.2 KB
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.
- 13d ago First seen · 183 lines · 25 tokens per session scan A f8dfcb232500
gsea is a skill published in the GitHub repository aipoch/medical-research-skills (1,860 stars, last pushed 1mo ago), licensed MIT. It adds 25 tokens to every session and 2,725 once invoked, about $0.0001 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 2026-08-30.
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.