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bio-agent-skills-hub

Discover and invoke 1,676 deduplicated biomedical AI agent skills from the Awesome Bio Agent Skills repository (20 source repos, 15 categories). Use this skill as a router whenever a user needs a bioinformatics/biomedical task (genomics, transcriptomics, single-cell, proteomics, protein design, clinical, epigenomics, multi-omics, pathway, metagenomics, database queries, visualization, workflows): search the index, locate the best-matching skill, fetch its SKILL.md, and follow it.

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含まれるファイル(1)

  • SKILL.md13.2 KB

SKILL.md(原文)

インストールする前に、エージェントに与えられる指示の中身を確認できます。

Bio Agent Skills Hub

A router/index skill over 1,676 deduplicated biomedical AI agent skills, aggregated and deduplicated from 20 open-source repositories into 15 categories. Each skill is a self-contained SKILL.md folder compatible with Claude-based agent frameworks.

This skill does not duplicate the 1,676 skills. It tells the agent how to (1) search the index, (2) locate the single best-matching skill, (3) fetch that skill's SKILL.md on demand, and (4) follow it. Skill bodies are fetched from GitHub on demand; a git clone fallback (incl. a China mirror) is provided for offline / bulk / private use.


How to use this skill (router workflow)

When a user asks for any bioinformatics task, workflow, or analysis:

Step 1 — Search the index to find candidate skills

The index has columns: skill_name, folder_name, source_repo, category, description, file_count, archive_path. archive_path = <source_repo>/<folder_name> and is the path under skills/.

Search skill_name + description + category + source_repo together (descriptions contain rich "Use when..." text), and present ranked candidates with their category and archive_path so the right one can be chosen:

import pandas as pd

# Authoritative v3 index. Prefer a local copy if this skill bundles one; else read from GitHub raw.
INDEX_URL = "https://raw.githubusercontent.com/BioTender-max/awesome-bio-agent-skills/main/bioskill_index_v3.csv"
df = pd.read_csv(INDEX_URL)   # 1,676 rows

def search_skills(query, category=None, source=None, top=15):
    """Keyword search over name+description+category+source. Returns candidate skills."""
    q = query.lower()
    hay = (df["skill_name"].fillna("") + " | " +
           df["description"].fillna("") + " | " +
           df["category"].fillna("") + " | " +
           df["source_repo"].fillna("")).str.lower()
    hits = df[hay.str.contains(q, regex=False)].copy()
    if category:
        hits = hits[hits["category"] == category]
    if source:
        hits = hits[hits["source_repo"] == source]
    # rank: name match first, then description match
    hits["_name_hit"] = hits["skill_name"].str.lower().str.contains(q, regex=False)
    hits = hits.sort_values(["_name_hit", "file_count"], ascending=[False, False])
    return hits[["skill_name", "category", "source_repo", "archive_path", "description"]].head(top)

print(search_skills("variant calling").to_string(index=False))

If nothing matches, broaden the query (try a synonym), or filter by category (see the table below) and browse that category's README section.

Step 2 — Fetch the chosen skill's SKILL.md (content on demand)

Once you pick a candidate's archive_path (e.g. bioskills/clair3-variants):

import urllib.request

archive_path = "bioskills/clair3-variants"   # from the search result
url = f"https://raw.githubusercontent.com/BioTender-max/awesome-bio-agent-skills/main/skills/{archive_path}/SKILL.md"
skill_md = urllib.request.urlopen(url, timeout=30).read().decode()
print(skill_md)   # read it, then follow its instructions

Some skills ship supporting files (scripts/, references/); list a folder via the GitHub API or clone it (Step 3) if you need them.

Step 3 — Offline / bulk / private fallback (clone)

If raw fetch is unavailable, or you want all supporting files, clone and copy the skill folder:

Standard (international):

git clone https://github.com/BioTender-max/awesome-bio-agent-skills.git
cp -r awesome-bio-agent-skills/skills/<archive_path>/ /path/to/your/agent/skills/

China-accelerated (ghfast.top mirror) — prepend the mirror to the GitHub URL; works for cloning this or any source repo (https://ghfast.top/https://github.com/<owner>/<repo>.git):

git clone https://ghfast.top/https://github.com/BioTender-max/awesome-bio-agent-skills.git
cp -r awesome-bio-agent-skills/skills/<archive_path>/ /path/to/your/agent/skills/

Categories (15) — counts and where to browse

Filter searches with the category key (left column). README section links jump to the browsable table for that category.

Category (key)SkillsREADME sectionTopics
genomics526GenomicsWGS/WES, variant calling, GWAS, CNV, structural variants, alignment, assembly
biology-other236Biology and AIDrug discovery, molecular docking, protein binder design, cheminformatics
proteomics167ProteomicsMass spectrometry, structure prediction (AlphaFold/ESM), binding affinity
clinical152Clinical and MedicalEHR, clinical trials, survival analysis, ACMG, precision medicine
single-cell144Single-Cell AnalysisscRNA-seq QC, clustering, trajectory, cell communication, spatial, multimodal
transcriptomics97TranscriptomicsBulk RNA-seq, differential expression, splicing, lncRNA, isoforms
bioinformatics-general86Bioinformatics UtilitiesBLAST, MSA, phylogenetics, sequence utilities, stats libraries
multi-omics69Multi-Omics IntegrationMOFA, DIABLO, integration, spatial multi-omics
database-query63Database QueryUniProt, PDB, KEGG, Reactome, GEO, ClinVar, Ensembl, dbSNP
visualization48VisualizationVolcano plots, heatmaps, UMAP, genome tracks, interactive charts
workflow38Workflow OrchestrationSnakemake, Nextflow, CWL, WDL, HPC orchestration, lab automation
epigenomics19EpigenomicsChIP-seq, ATAC-seq, DNA methylation, Hi-C, chromatin state
pathway15Pathway AnalysisKEGG, Reactome, GO enrichment, GSEA
metagenomics9Metagenomics16S, Kraken2/Bracken, MetaPhlAn, QIIME2
protein-design7Protein DesignRFdiffusion, ProteinMPNN, Boltz, Chai, LigandMPNN

Source repositories (20)

Skills are aggregated and deduplicated from these repositories. Use the source_repo key to filter the index. (bio-agent-skills-hub is this self-referential hub entry.)

Source repo (source_repo)SkillsFocus
bioskills — GPTomics/bioSkills536Systematic bioinformatics suite from QC to multi-omics.
openclaw — FreedomIntelligence/OpenClaw-Medical-Skills359Medical AI library aggregating 12 specialized sub-repositories.
sciagent — jaechang-hits/SciAgent-Skills154Statistics, databases, and clinical decision skills.
kdense — K-Dense-AI/scientific-agent-skills102General scientific computing and HPC workflow skills.
neuroclaw — CUHK-AIM-Group/NeuroClaw86Neuroimaging: sMRI, fMRI, dMRI, EEG (BIDS, FreeSurfer, FSL, fMRIPrep).
clawbio — ClawBio/ClawBio63Bioinformatics workflow orchestration for GWAS and single-cell.
labclaw — wu-yc/LabClaw59Lab automation and biomedical research skills.
drugclaw — QSong-github/DrugClaw57Drug intelligence: DTI, ADR, DDI, pharmacogenomics, repurposing.
nobel — ChrisLou-bioinfo/nobel-medicine-minds55Cognitive frameworks of Nobel Medicine laureates as SKILL.md.
bioclaw_hub — zongtingwei/Bioclaw_Skills_Hub46Ten-category biological skills hub.
bioclaw — Runchuan-BU/BioClaw37Core bioinformatics tools and database query skills.
omics — fmschulz/omics-skills29Single-cell and spatial omics specialized skills.
omicsclaw — TianGzlab/OmicsClaw286-omics domain skills: spatial, scRNA, bulk RNA, genomics, proteomics, metabolomics.
adaptyv — adaptyvbio/protein-design-skills21Protein design toolkit: RFdiffusion, ProteinMPNN, Boltz, Chai.
pantheon — aristoteleo/PantheonOS18Single-cell and spatial transcriptomics (Dynamo/Spateo team).
evoskills — EvoScientist/EvoSkills13Research-lifecycle skills: ideation, planning, execution, writing, review.
medgeclaw — xjtulyc/MedgeClaw7Biomedical research skills with dashboard, RStudio, JupyterLab integration.
zamushwani — zamushwani2/biomedical-ai-skills4Cancer multi-omics analysis skills in R.
bio-agent-skills-hub — BioTender-max/awesome-bio-agent-skills1Self-referential hub skill that indexes this collection.
sragent — ArcInstitute/SRAgent1Intelligent SRA and GEO dataset retrieval.

Example interactions

User: "I need a GWAS pipeline." Agent: search_skills("gwas") → top hit bio-workflows-gwas-pipeline (genomics, bioskills/gwas-pipeline); also gwas-pipeline (clawbio/gwas-pipeline) and plink2-gwas-analysis (sciagent/plink2-gwas-analysis). Fetch https://raw.githubusercontent.com/BioTender-max/awesome-bio-agent-skills/main/skills/bioskills/gwas-pipeline/SKILL.md and follow it. Browse more: https://github.com/BioTender-max/awesome-bio-agent-skills#genomics

User: "Preprocess and cluster my scRNA-seq data." Agent: search_skills("scrna preprocessing", category="single-cell") → scrna-preprocessing-clustering (bioclaw/scrna-preprocessing-clustering). Fetch its SKILL.md and follow it. 144 single-cell skills total: https://github.com/BioTender-max/awesome-bio-agent-skills#single-cell-analysis

User: "Design a protein binder backbone." Agent: search_skills("rfdiffusion") → rfdiffusion (protein-design, adaptyv/rfdiffusion). Related: proteinmpnn (adaptyv/proteinmpnn), bindcraft (adaptyv/bindcraft). Fetch the SKILL.md for the chosen tool. Browse: https://github.com/BioTender-max/awesome-bio-agent-skills#protein-design

User: "Call variants from long reads." Agent: search_skills("variant calling", category="genomics") → bio-long-read-sequencing-clair3-variants (bioskills/clair3-variants); for short reads see bio-variant-calling-deepvariant (bioskills/deepvariant). Fetch and follow.


Notes

  • The index (bioskill_index_v3.csv) is the single source of truth for what exists and where; always resolve archive_path from it rather than guessing folder names.
  • Counts above (1,676 skills / 20 sources / 15 categories) match the repository README and index.
  • Content fetch requires network access and a public repository; use the clone fallback otherwise.

レビュー

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日本語の概要は準備中です。原文の説明を表示しています。

BioTender-max/awesome-bio-agent-skills2012026年7月2日 更新

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日本語の概要は準備中です。原文の説明を表示しています。

BioTender-max/awesome-bio-agent-skills2012026年7月2日 更新

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日本語の概要は準備中です。原文の説明を表示しています。

BioTender-max/awesome-bio-agent-skills2012026年7月2日 更新

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日本語の概要は準備中です。原文の説明を表示しています。

BioTender-max/awesome-bio-agent-skills2012026年7月2日 更新

atac-seq

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ATAC-seq processing with assay QC, MACS3 peak calling, consensus peak matrices, differential accessibility, and motif or footprint follow-up.

日本語の概要は準備中です。原文の説明を表示しています。

BioTender-max/awesome-bio-agent-skills2012026年7月2日 更新

bindcraft

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End-to-end binder design using BindCraft hallucination. Use this skill when: (1) Designing protein binders with built-in AF2 validation, (2) Running production-quality binder campaigns, (3) Using different design protocols (fast, default, slow), (4) Need joint backbone and sequence optimization, (5) Want high experimental success rate. For backbone-only generation, use rfdiffusion. For QC thresholds, use protein-qc. For tool selection guidance, use binder-design.

日本語の概要は準備中です。原文の説明を表示しています。

BioTender-max/awesome-bio-agent-skills2012026年7月2日 更新

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