--- name: Bio Agent Skills Hub slug: bio-agent-skills-hub category: AI Engineering description: Bio Agent Skills Hub routes biomedical and bioinformatics requests to the best matching Claude Code skill by searching an index of 1,676 skills, fetching the selected SKILL.md, and following its instructions. Use it for genomics, transcriptomics, single-cell, proteomics, clinical, and multi-omics tasks. github: "https://github.com/BioTender-max/awesome-bio-agent-skills/tree/main/skills/bio-agent-skills-hub" language: Python stars: 174 forks: 30 install: "npx degit https://github.com/BioTender-max/awesome-bio-agent-skills/tree/main/skills/bio-agent-skills-hub ~/.claude/skills/bio-agent-skills-hub" installs_to: ~/.claude/skills/bio-agent-skills-hub source_path: skills/bio-agent-skills-hub/SKILL.md collection_size: 25 category_size: 3475 collection_url: "https://dirskills.com/collections/BioTender-max/awesome-bio-agent-skills" added: 2026-09-07T05:21:53.744Z last_synced: 2026-09-07T05:21:53.744Z canonical_url: "https://dirskills.com/skills/bio-agent-skills-hub" --- # Bio Agent Skills Hub Bio Agent Skills Hub routes biomedical and bioinformatics requests to the best matching Claude Code skill by searching an index of 1,676 skills, fetching the selected SKILL.md, and following its instructions. Use it for genomics, transcriptomics, single-cell, proteomics, clinical, and multi-omics tasks. **Install:** ```bash npx degit https://github.com/BioTender-max/awesome-bio-agent-skills/tree/main/skills/bio-agent-skills-hub ~/.claude/skills/bio-agent-skills-hub ``` ## README # 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. - Repository: **https://github.com/BioTender-max/awesome-bio-agent-skills** - Machine-readable index (authoritative): **`https://raw.githubusercontent.com/BioTender-max/awesome-bio-agent-skills/main/bioskill_index_v3.csv`** (1,676 rows) > 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` = `/` 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: ```python 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`): ```python 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):** ```bash git clone https://github.com/BioTender-max/awesome-bio-agent-skills.git cp -r awesome-bio-agent-skills/skills// /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//.git`): ```bash git clone https://ghfast.top/https://github.com/BioTender-max/awesome-bio-agent-skills.git cp -r awesome-bio-agent-skills/skills// /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`) | Skills | README section | Topics | |------------------|-------:|----------------|--------| | `genomics` | 526 | [Genomics](https://github.com/BioTender-max/awesome-bio-agent-skills#genomics) | WGS/WES, variant calling, GWAS, CNV, structural variants, alignment, assembly | | `biology-other` | 236 | [Biology and AI](https://github.com/BioTender-max/awesome-bio-agent-skills#biology-and-ai) | Drug discovery, molecular docking, protein binder design, cheminformatics | | `proteomics` | 167 | [Proteomics](https://github.com/BioTender-max/awesome-bio-agent-skills#proteomics) | Mass spectrometry, structure prediction (AlphaFold/ESM), binding affinity | | `clinical` | 152 | [Clinical and Medical](https://github.com/BioTender-max/awesome-bio-agent-skills#clinical-and-medical) | EHR, clinical trials, survival analysis, ACMG, precision medicine | | `single-cell` | 144 | [Single-Cell Analysis](https://github.com/BioTender-max/awesome-bio-agent-skills#single-cell-analysis) | scRNA-seq QC, clustering, trajectory, cell communication, spatial, multimodal | | `transcriptomics` | 97 | [Transcriptomics](https://github.com/BioTender-max/awesome-bio-agent-skills#transcriptomics) | Bulk RNA-seq, differential expression, splicing, lncRNA, isoforms | | `bioinformatics-general` | 86 | [Bioinformatics Utilities](https://github.com/BioTender-max/awesome-bio-agent-skills#bioinformatics-utilities) | BLAST, MSA, phylogenetics, sequence utilities, stats libraries | | `multi-omics` | 69 | [Multi-Omics Integration](https://github.com/BioTender-max/awesome-bio-agent-skills#multi-omics-integration) | MOFA, DIABLO, integration, spatial multi-omics | | `database-query` | 63 | [Database Query](https://github.com/BioTender-max/awesome-bio-agent-skills#database-query) | UniProt, PDB, KEGG, Reactome, GEO, ClinVar, Ensembl, dbSNP | | `visualization` | 48 | [Visualization](https://github.com/BioTender-max/awesome-bio-agent-skills#visualization) | Volcano plots, heatmaps, UMAP, genome tracks, interactive charts | | `workflow` | 38 | [Workflow Orchestration](https://github.com/BioTender-max/awesome-bio-agent-skills#workflow-orchestration) | Snakemake, Nextflow, CWL, WDL, HPC orchestration, lab automation | | `epigenomics` | 19 | [Epigenomics](https://github.com/BioTender-max/awesome-bio-agent-skills#epigenomics) | ChIP-seq, ATAC-seq, DNA methylation, Hi-C, chromatin state | | `pathway` | 15 | [Pathway Analysis](https://github.com/BioTender-max/awesome-bio-agent-skills#pathway-analysis) | KEGG, Reactome, GO enrichment, GSEA | | `metagenomics` | 9 | [Metagenomics](https://github.com/BioTender-max/awesome-bio-agent-skills#metagenomics) | 16S, Kraken2/Bracken, MetaPhlAn, QIIME2 | | `protein-design` | 7 | [Protein Design](https://github.com/BioTender-max/awesome-bio-agent-skills#protein-design) | RFdiffusion, 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`) | Skills | Focus | |-----------------------------|-------:|-------| | `bioskills` — [GPTomics/bioSkills](https://github.com/GPTomics/bioSkills) | 536 | Systematic bioinformatics suite from QC to multi-omics. | | `openclaw` — [FreedomIntelligence/OpenClaw-Medical-Skills](https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills) | 359 | Medical AI library aggregating 12 specialized sub-repositories. | | `sciagent` — [jaechang-hits/SciAgent-Skills](https://github.com/jaechang-hits/SciAgent-Skills) | 154 | Statistics, databases, and clinical decision skills. | | `kdense` — [K-Dense-AI/scientific-agent-skills](https://github.com/K-Dense-AI/scientific-agent-skills) | 102 | General scientific computing and HPC workflow skills. | | `neuroclaw` — [CUHK-AIM-Group/NeuroClaw](https://github.com/CUHK-AIM-Group/NeuroClaw) | 86 | Neuroimaging: sMRI, fMRI, dMRI, EEG (BIDS, FreeSurfer, FSL, fMRIPrep). | | `clawbio` — [ClawBio/ClawBio](https://github.com/ClawBio/ClawBio) | 63 | Bioinformatics workflow orchestration for GWAS and single-cell. | | `labclaw` — [wu-yc/LabClaw](https://github.com/wu-yc/LabClaw) | 59 | Lab automation and biomedical research skills. | | `drugclaw` — [QSong-github/DrugClaw](https://github.com/QSong-github/DrugClaw) | 57 | Drug intelligence: DTI, ADR, DDI, pharmacogenomics, repurposing. | | `nobel` — [ChrisLou-bioinfo/nobel-medicine-minds](https://github.com/ChrisLou-bioinfo/nobel-medicine-minds) | 55 | Cognitive frameworks of Nobel Medicine laureates as SKILL.md. | | `bioclaw_hub` — [zongtingwei/Bioclaw_Skills_Hub](https://github.com/zongtingwei/Bioclaw_Skills_Hub) | 46 | Ten-category biological skills hub. | | `bioclaw` — [Runchuan-BU/BioClaw](https://github.com/Runchuan-BU/BioClaw) | 37 | Core bioinformatics tools and database query skills. | | `omics` — [fmschulz/omics-skills](https://github.com/fmschulz/omics-skills) | 29 | Single-cell and spatial omics specialized skills. | | `omicsclaw` — [TianGzlab/OmicsClaw](https://github.com/TianGzlab/OmicsClaw) | 28 | 6-omics domain skills: spatial, scRNA, bulk RNA, genomics, proteomics, metabolomics. | | `adaptyv` — [adaptyvbio/protein-design-skills](https://github.com/adaptyvbio/protein-design-skills) | 21 | Protein design toolkit: RFdiffusion, ProteinMPNN, Boltz, Chai. | | `pantheon` — [aristoteleo/PantheonOS](https://github.com/aristoteleo/PantheonOS) | 18 | Single-cell and spatial transcriptomics (Dynamo/Spateo team). | | `evoskills` — [EvoScientist/EvoSkills](https://github.com/EvoScientist/EvoSkills) | 13 | Research-lifecycle skills: ideation, planning, execution, writing, review. | | `medgeclaw` — [xjtulyc/MedgeClaw](https://github.com/xjtulyc/MedgeClaw) | 7 | Biomedical research skills with dashboard, RStudio, JupyterLab integration. | | `zamushwani` — [zamushwani2/biomedical-ai-skills](https://github.com/zamushwani2/biomedical-ai-skills) | 4 | Cancer multi-omics analysis skills in R. | | `bio-agent-skills-hub` — [BioTender-max/awesome-bio-agent-skills](https://github.com/BioTender-max/awesome-bio-agent-skills) | 1 | Self-referential hub skill that indexes this collection. | | `sragent` — [ArcInstitute/SRAgent](https://github.com/ArcInstitute/SRAgent) | 1 | Intelligent 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.