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
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/aipoch/medical-research-skillsnpx agentmods add skills/aipoch/medical-research-skills/consensus-clustering-analysisWrote 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/consensus-clustering-analysis)<a href="https://agentmods.dev/skills/aipoch/medical-research-skills/consensus-clustering-analysis"><img src="https://agentmods.dev/badge/skills/aipoch/medical-research-skills/consensus-clustering-analysis/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/consensus-clustering-analysis"><img src="https://agentmods.dev/badge/skills/aipoch/medical-research-skills/consensus-clustering-analysis.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Data Exfiltration · line 138 Code or instructions that leak agent conversation context to external services, potentially exposing sensitive user interactions.Fix: Remove any code that sends prompts, responses, or session data externally. Preserve user privacy; never exfiltrate conversation content.
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 | $0.00051 | $0.02025 |
| Opus 5 | $0.00026 | $0.01012 |
| Sonnet 5 | $0.00010 | $0.00405 |
| Haiku 4.5 | $0.00005 | $0.00202 |
Grade A, and why
consensus-clustering-analysis 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 11d 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 — 265 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Consensus Clustering Analysis
When to Use
Use this skill when you need to identify stable sample subtypes from a bulk expression matrix with ConsensusClusterPlus, compare candidate clustering settings with PAC, and export consensus matrix/CDF visualizations.
Do not use this skill for differential expression analysis, single-cell clustering, or non-expression tabular data.
When to Read External Files
| Situation | File to Read | Purpose |
|---|---|---|
| Need algorithm details | references/algorithm.md |
Consensus clustering, PAC scoring, and preprocessing assumptions |
| Need to run analysis | scripts/main.R |
Execute: Rscript scripts/main.R --input_file ... --group_file ... |
| Encounter errors | references/troubleshooting.md |
Common errors and solutions |
| Need CLI examples | references/cli-guide.md |
Detailed CLI usage examples with verified local runs |
Usage
Rscript scripts/main.R \
--input_file ./expression_matrix.csv \
--group_file ./groups.csv \
--disease_group case \
--max_k 4 \
--output_dir ./output/ \
--gene_selection highly_variable \
--top_n 5000 \
--reps 1000 \
--p_item 0.8 \
--p_feature 1.0 \
--timeout_seconds 3600 \
--seed 42
Arguments
| Short | Long | Type | Default | Description |
|---|---|---|---|---|
-i |
--input_file |
character | required | Expression matrix file (genes as rows, samples as columns) |
-g |
--group_file |
character | required | Group information file (sample ID + group columns) |
-d |
--disease_group |
character | case |
Group label retained for clustering |
-k |
--max_k |
integer | 4 |
Maximum cluster count to evaluate |
-o |
--output_dir |
character | ./output/ |
Output directory |
-m |
--gene_selection |
character | highly_variable |
Gene selection mode: highly_variable or custom |
-n |
--top_n |
integer | 5000 |
Number of top variable genes to keep |
-l |
--gene_list |
character | NULL |
Custom gene list file when gene_selection=custom |
-c |
--center_data |
logical | TRUE |
Median-center each gene before clustering |
-r |
--reps |
integer | 1000 |
Consensus resampling repetitions |
--p_item |
double | 0.8 |
Sample resampling proportion | |
--p_feature |
double | 1.0 |
Feature resampling proportion | |
-t |
--timeout_seconds |
integer | 3600 |
Elapsed timeout in seconds |
-s |
--seed |
integer | 42 |
Random seed for reproducibility |
What ships with it
19 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.
- DESCRIPTION 549 B
- eval_report_consensus-clustering-analysis_result.json 15 KB
- references/algorithm.md 2.2 KB
- references/cli-guide.md 11 KB
- references/troubleshooting.md 2.9 KB
- scripts/functions_analysis.R 5.6 KB
- scripts/io_utils.R 2.0 KB
- scripts/main.R 5.1 KB
- scripts/run_analysis.R 5.8 KB
- scripts/utils.R 3.6 KB
- scripts/visualization.R 2.8 KB
- tests/data/expression_matrix.csv 47 KB
- tests/data/genes.csv 267 B
- tests/data/groups.csv 674 B
- tests/run_tests.R 773 B
- tests/testthat.R 889 B
- tests/testthat/setup.R 251 B
- tests/testthat/test-cli-smoke.R 5.5 KB
- tests/testthat/test-functions.R 2.1 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.
- 11d ago First seen · 265 lines · 51 tokens per session scan A e38454ea939a
consensus-clustering-analysis is a skill published in the GitHub repository aipoch/medical-research-skills (1,855 stars, last pushed 1mo ago), licensed MIT. It adds 51 tokens to every session and 2,025 once invoked, about $0.0003 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.
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