Agent skill

Genomas Guide

by wentorai in wentorai/research-plugins

Automate gene expression analysis with the GenoMAS multi-agent system

MITAuto-check passedResearch & Science

Install Genomas Guide

skills CLI
$ npx skills add wentorai/research-plugins --skill genomas-guide -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install wentorai/research-plugins genomas-guide --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/wentorai/research-plugins.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/domains/biomedical/genomas-guide .claude/skills/genomas-guide && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
genomas-guide
GitHub stars
298
Used in
1 other repo
Token cost
~958 tokens
SKILL.md length
182 words
Files
1
Skills in repo
405
Repo updated
First seen
Licence
MIT

At a glance

Automate gene expression analysis with the GenoMAS multi-agent system

  • Tasks that involve Bioinformatics
  • SKILL.md covers Overview, Installation, Core Workflow and Supported Analyses, plus 2 more sections
  • Calls pip and git; reaches github.com
  • Tasks that involve Multi-agent orchestration

What it does

Genomas Guide is an agent skill from wentorai/research-plugins. Automate gene expression analysis with the GenoMAS multi-agent system

Its SKILL.md is about 960 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Research & Science, covering Bioinformatics and Multi-agent orchestration. The repository describes itself as: 350+ academic research skills, MCP configs, and plugins for Research-Claw and AI agents. The licence is MIT.

When your agent uses it

  • Tasks that involve Bioinformatics
  • Tasks that involve Multi-agent orchestration

Example prompts

  • “/genomas-guide”

Requirements

  • Python 3

What it can do on your machine

Read from SKILL.md and the folder at commit bf44b3c. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • pip
    • git

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • github.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Genomas Guide loads about 958 tokens when it runs. Until then it costs about 21 tokens; SKILL.md has 182 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~21
When it runs · the whole SKILL.md, loaded when a task matches
~958

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from wentorai/research-plugins at commit bf44b3c, republished under its MIT licence (© wentorai). 182 words, ~958 tokens.

Download SKILL.mdSave it as .claude/skills/genomas-guide/SKILL.md (or your agent's skills folder).
name
genomas-guide
description
Automate gene expression analysis with the GenoMAS multi-agent system

GenoMAS Guide

Overview

GenoMAS (Genomics Multi-Agent System) is a minimalist multi-agent framework for automating scientific analysis workflows, particularly gene expression analysis. It orchestrates specialized agents for data retrieval, preprocessing, differential expression analysis, pathway enrichment, and visualization — turning a natural language research question into a complete bioinformatics pipeline.

Installation

bash
pip install genomas
# Or from source
git clone https://github.com/futianfan/GenoMAS.git
cd GenoMAS && pip install -e .

Core Workflow

Natural Language to Pipeline
python
from genomas import GenoMAS

geno = GenoMAS(llm_provider="anthropic")

# Describe analysis in natural language
result = geno.analyze(
    "Compare gene expression between tumor and normal tissue "
    "in the TCGA breast cancer dataset. Identify differentially "
    "expressed genes and run pathway enrichment analysis."
)

# GenoMAS automatically:
# 1. Retrieves TCGA-BRCA data via GDC API
# 2. Normalizes and filters expression data
# 3. Runs DESeq2-style differential expression
# 4. Performs GO and KEGG pathway enrichment
# 5. Generates volcano plots and heatmaps
Agent Roles
AgentResponsibility
Data AgentRetrieves datasets from GEO, TCGA, ArrayExpress
Preprocessing AgentQuality control, normalization, filtering
Analysis AgentDifferential expression, clustering, PCA
Enrichment AgentGO, KEGG, MSigDB pathway analysis
Visualization AgentPlots, heatmaps, volcano plots
Report AgentGenerates methods section and results summary
Step-by-Step Usage
python
from genomas import DataAgent, AnalysisAgent, EnrichmentAgent

# Step 1: Retrieve data
data_agent = DataAgent()
dataset = data_agent.fetch("GSE12345", platform="RNA-seq")

# Step 2: Differential expression
analysis = AnalysisAgent()
de_results = analysis.differential_expression(
    dataset,
    group_col="condition",
    case="tumor",
    control="normal",
    method="deseq2",
)

# Step 3: Filter significant genes
sig_genes = de_results[
    (de_results["padj"] < 0.05) &
    (abs(de_results["log2FoldChange"]) > 1)
]
print(f"Found {len(sig_genes)} differentially expressed genes")

# Step 4: Pathway enrichment
enrichment = EnrichmentAgent()
pathways = enrichment.run(
    gene_list=sig_genes["gene_symbol"].tolist(),
    databases=["GO_BP", "KEGG", "Reactome"],
)

# Step 5: Visualize
from genomas.viz import volcano_plot, pathway_barplot
volcano_plot(de_results, output="volcano.png")
pathway_barplot(pathways, top_n=20, output="pathways.png")

Supported Analyses

AnalysisMethod
Differential expressionDESeq2, edgeR, limma-voom
ClusteringHierarchical, k-means, UMAP
PCAPrincipal component analysis
GO enrichmentGene Ontology term enrichment
KEGG pathwayKEGG pathway mapping
GSEAGene Set Enrichment Analysis
Survival analysisKaplan-Meier, Cox regression

Data Sources

SourceData type
GEO (NCBI)Microarray, RNA-seq
TCGACancer genomics
GTExNormal tissue expression
ArrayExpressEuropean expression data

References

  • GenoMAS GitHub
  • Love, M.I. et al. (2014). "Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2." Genome Biology 15(12).

© wentorai, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/domains/biomedical/genomas-guide of wentorai/research-plugins.

Open the folder on GitHubat commit bf44b3c

Used in 1 other repository

We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in wentorai/research-plugins, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Genomas Guide next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

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ULW Deep Researchcode-yeongyu/oh-my-openagent70k—~14kAutomated safety check: PassCustom licence
Deep ResearchXiaomiMiMo/MiMo-Code14k—~1.2kAutomated safety check: PassMIT
Mcpmed Bioinformatics ServerFreedomIntelligence/OpenClaw-Medical-Skills3.1k1 repos~353Automated safety check: PassMIT
Spatial TrajectoryTianGzlab/OmicsClaw161—~1.3kAutomated safety check: PassApache-2.0

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Questions about Genomas Guide

What does Genomas Guide do?

Automate gene expression analysis with the GenoMAS multi-agent system. Genomas Guide is an agent skill from wentorai/research-plugins.

When should I use Genomas Guide?

Genomas Guide fits situations like: tasks that involve Bioinformatics; tasks that involve Multi-agent orchestration.

How do I install Genomas Guide in Claude Code?

Run `npx skills add wentorai/research-plugins --skill genomas-guide -a claude-code`. Or copy the skill folder (skills/domains/biomedical/genomas-guide in wentorai/research-plugins) into .claude/skills/genomas-guide in your project. Claude Code loads it when a task matches its description.

How do I install Genomas Guide in Codex?

Run `npx skills add wentorai/research-plugins --skill genomas-guide -a codex`. Or copy the skill folder (skills/domains/biomedical/genomas-guide in wentorai/research-plugins) into .agents/skills/genomas-guide in your project. Codex loads it when a task matches its description.

Can I use Genomas Guide in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add wentorai/research-plugins --skill genomas-guide -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/genomas-guide, .gemini/skills/genomas-guide, .github/skills/genomas-guide and .opencode/skills/genomas-guide in your project.

What does Genomas Guide need to run?

Going by SKILL.md and its folder, Genomas Guide needs the command-line tools its instructions call (pip and git). Our summary lists: Python 3.

Does Genomas Guide access the network?

SKILL.md names 1 domain. In commands or code: github.com; the agent is likely to contact it when it follows the instructions. This is read from the text; nothing was executed.

Is Genomas Guide safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Genomas Guide use?

Genomas Guide is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Genomas Guide use?

About 958 tokens (SKILL.md is roughly 3.8k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Genomas Guide?

Skills that share tags, products or a category with Genomas Guide: MFA Pipeline Orchestrator (aiming-lab/AutoResearchClaw, 15k stars), ULW Deep Research (code-yeongyu/oh-my-openagent, 70k stars), Deep Research (XiaomiMiMo/MiMo-Code, 14k stars) and Mcpmed Bioinformatics Server (FreedomIntelligence/OpenClaw-Medical-Skills, 3.1k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Genomas Guide?

wentorai (a GitHub user) maintains it in wentorai/research-plugins, which has 298 GitHub stars. The repository holds 405 skills in this directory. The repository was last updated on June 19, 2026.

Source: wentorai/research-plugins on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.