Alphagenome Single Variant Analysis
google-deepmind/science-skills
Analyzes genetic variant effects on gene expression (RNA-seq), chromatin accessibility (DNASE), histone marks (ChIP), and transcription factors using the AlphaGenome API.
Galaxy tool discovery, intelligent recommendation, and execution — 8,000+ bioinformatics tools from usegalaxy.org with multi-signal scoring and workflow suggestions
Install Galaxy Bridge
$ npx skills add ClawBio/ClawBio --skill galaxy-bridge -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install ClawBio/ClawBio galaxy-bridge --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/ClawBio/ClawBio.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/galaxy-bridge .claude/skills/galaxy-bridge && rm -rf skills-srcUse ~/.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/
Install the "galaxy-bridge" agent skill from https://github.com/ClawBio/ClawBio/tree/main/skills/galaxy-bridge into .claude/skills/galaxy-bridge/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "galaxy-bridge", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/ClawBio/ClawBio/tree/main/skills/galaxy-bridgeType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add ClawBio/ClawBio --skill galaxy-bridge -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install ClawBio/ClawBio galaxy-bridge --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ClawBio/ClawBio.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/galaxy-bridge .agents/skills/galaxy-bridge && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "galaxy-bridge" agent skill from https://github.com/ClawBio/ClawBio/tree/main/skills/galaxy-bridge into .agents/skills/galaxy-bridge/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "galaxy-bridge", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add ClawBio/ClawBio --skill galaxy-bridge -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install ClawBio/ClawBio galaxy-bridge --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ClawBio/ClawBio.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/galaxy-bridge .cursor/skills/galaxy-bridge && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "galaxy-bridge" agent skill from https://github.com/ClawBio/ClawBio/tree/main/skills/galaxy-bridge into .cursor/skills/galaxy-bridge/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "galaxy-bridge", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/ClawBio/ClawBio.git --path skills/galaxy-bridge--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add ClawBio/ClawBio --skill galaxy-bridge -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install ClawBio/ClawBio galaxy-bridge --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ClawBio/ClawBio.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/galaxy-bridge .gemini/skills/galaxy-bridge && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "galaxy-bridge" agent skill from https://github.com/ClawBio/ClawBio/tree/main/skills/galaxy-bridge into .gemini/skills/galaxy-bridge/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "galaxy-bridge", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install ClawBio/ClawBio galaxy-bridgeInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add ClawBio/ClawBio --skill galaxy-bridge -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/ClawBio/ClawBio.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/galaxy-bridge .github/skills/galaxy-bridge && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "galaxy-bridge" agent skill from https://github.com/ClawBio/ClawBio/tree/main/skills/galaxy-bridge into .github/skills/galaxy-bridge/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "galaxy-bridge", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add ClawBio/ClawBio --skill galaxy-bridge -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install ClawBio/ClawBio galaxy-bridge --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ClawBio/ClawBio.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/galaxy-bridge .opencode/skills/galaxy-bridge && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "galaxy-bridge" agent skill from https://github.com/ClawBio/ClawBio/tree/main/skills/galaxy-bridge into .opencode/skills/galaxy-bridge/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "galaxy-bridge", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
galaxy-bridge- GitHub stars
- 1.2k
- Used in
- 2 other repos
- Token cost
- ~2.4k tokens
- SKILL.md length
- 782 words
- Files
- 214
- Skills in repo
- 104
- Repo updated
- First seen
- Licence
- MIT
At a glance
Galaxy tool discovery, intelligent recommendation, and execution — 8,000+ bioinformatics tools from usegalaxy.org with multi-signal scoring and workflow suggestions
- Works in 11 steps: Intelligent tool recommendation —… → Workflow suggestions — 8 pre-defined… → Input format awareness — provide your… → …
- Tasks that involve Bioinformatics
- SKILL.md covers Why This Exists, Core Capabilities, Input Formats and Workflow, plus 9 more sections
- Runs Shell and Python scripts from its folder; calls python; reaches usegalaxy.org; needs GALAXY_API_KEY
What it does
Galaxy Bridge is an agent skill from ClawBio/ClawBio. Galaxy tool discovery, intelligent recommendation, and execution — 8,000+ bioinformatics tools from usegalaxy.org with multi-signal scoring and workflow suggestions
Its SKILL.md is about 2.4k tokens, which your agent loads only when the skill is triggered. The skill folder holds 216 other files (for example `demo/reproducibility/commands.sh`, `galaxy_bridge.py` and `galaxy_catalog.json`).
It sits in Research & Science, covering Bioinformatics. The repository describes itself as: 🦖 ClawBio - The first bioinformatics-native AI agent skill library. Local-first. Reproducible. Open. Free. The licence is MIT.
When your agent uses it
- Tasks that involve Bioinformatics
Example prompts
- “/galaxy-bridge”
Requirements
- Python 3
- A Bash shell
- A credential in GALAXY_API_KEY
Workflow steps
11 steps, taken from the first numbered list in SKILL.md.
- Intelligent tool recommendation — describe a task in plain English; multi-signal scoring across 7 dimensions returns the best Galaxy tool…
- Workflow suggestions — 8 pre-defined pipeline templates (RNA-seq DE, metagenomics, variant calling, WES germline, ChIP-seq, nanopore…
- Input format awareness — provide your file extension (.fastq, .bam, .vcf) for format-aware recommendations
- Version deduplication — 8,182 catalog entries collapse to ~2,300 unique tools; latest version preferred, version count as maturity signal
- EDAM ontology resolution — 108 EDAM topic/operation IDs resolved to human-readable labels for richer matching
- Natural language search — keyword-based search across 8,000+ Galaxy tools by name, description, section, and EDAM terms
- Remote execution — run Galaxy tools on usegalaxy.org via BioBlend API
- Category browsing — explore 86 ToolShed categories with tool counts
- Tool detail inspection — view inputs, outputs, and parameter schemas
- Offline demo mode — FastQC demo with pre-cached results (no API key needed)
- Cross-platform chaining — Galaxy VEP → ClawBio PharmGx, Galaxy Kraken2 → ClawBio metagenomics
What it can do on your machine
Read from SKILL.md and the folder at commit dece754. 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
Ships script files (Shell and Python, from the files we listed), which the agent can run.
Shell commands in SKILL.md call:
python
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:
usegalaxy.org
Also links to:
galaxyproject.orgbioblend.readthedocs.iotoolshed.g2.bx.psu.edu
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names these keys or tokens, usually read from environment variables:
GALAXY_API_KEY
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Galaxy Bridge loads about 2.4k tokens when it runs. Until then it costs about 45 tokens; SKILL.md has 782 words of instructions outside code blocks.
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 ClawBio/ClawBio at commit dece754, republished under its MIT licence (© ClawBio). 782 words, ~2,444 tokens.
Download SKILL.mdSave it as
.claude/skills/galaxy-bridge/SKILL.md (or your agent's skills folder). This skill also uses 213 other files; get the full folder from GitHub.- name
- galaxy-bridge
- description
- Galaxy tool discovery, intelligent recommendation, and execution — 8,000+ bioinformatics tools from usegalaxy.org with multi-signal scoring and workflow suggestions
- license
- MIT
- metadata.version
- 0.2.0
- metadata.author
- Manuel Corpas
- metadata.tags
- galaxy, bioinformatics, tool-discovery, workflows, NGS, genomics, proteomics, metagenomics
Galaxy Bridge
ClawBio's gateway to the Galaxy ecosystem — 1,770+ production bioinformatics tools, discoverable and executable through natural language.
Why This Exists
Galaxy (usegalaxy.org) hosts the world's largest collection of curated bioinformatics tools — 1,770+ on the main server alone, covering everything from FASTQ QC to metagenomics to protein structure prediction. But discovering the right tool requires knowing exact tool IDs, navigating nested ToolShed categories, and understanding parameter schemas.
Galaxy Bridge makes these tools agent-accessible: search by natural language, execute via CLI, and chain Galaxy tools with ClawBio's local skills for cross-platform workflows that neither system can do alone.
Core Capabilities
- Intelligent tool recommendation — describe a task in plain English; multi-signal scoring across 7 dimensions returns the best Galaxy tool with explanations
- Workflow suggestions — 8 pre-defined pipeline templates (RNA-seq DE, metagenomics, variant calling, WES germline, ChIP-seq, nanopore, genome assembly, variant annotation)
- Input format awareness — provide your file extension (.fastq, .bam, .vcf) for format-aware recommendations
- Version deduplication — 8,182 catalog entries collapse to ~2,300 unique tools; latest version preferred, version count as maturity signal
- EDAM ontology resolution — 108 EDAM topic/operation IDs resolved to human-readable labels for richer matching
- Natural language search — keyword-based search across 8,000+ Galaxy tools by name, description, section, and EDAM terms
- Remote execution — run Galaxy tools on usegalaxy.org via BioBlend API
- Category browsing — explore 86 ToolShed categories with tool counts
- Tool detail inspection — view inputs, outputs, and parameter schemas
- Offline demo mode — FastQC demo with pre-cached results (no API key needed)
- Cross-platform chaining — Galaxy VEP → ClawBio PharmGx, Galaxy Kraken2 → ClawBio metagenomics
Input Formats
| Format | Extension | Required Fields | Example |
|---|---|---|---|
| FASTQ | .fq, .fastq, .fq.gz | Sequence reads | Illumina paired-end reads |
| VCF | .vcf, .vcf.gz | Variant calls | Annotated VCF for VEP |
| BAM | .bam | Aligned reads | BWA-MEM2 output |
| FASTA | .fa, .fasta | Sequences | Reference genome |
| Tabular | .tsv, .csv | Varies by tool | Gene expression matrix |
Workflow
- Search — User describes what they need → bridge searches local catalog + Galaxy API
- Select — Ranked results with descriptions, versions, and categories
- Configure — Show tool inputs/outputs schema; user provides files and parameters
- Execute — Upload input to Galaxy, run tool, poll for completion
- Retrieve — Download outputs to local directory
- Bundle — Generate reproducibility package (commands.sh, environment.yml, checksums)
CLI Reference
# Intelligent tool recommendation (new in v0.2.0)
python galaxy_bridge.py --recommend "quality control on my sequencing reads"
python galaxy_bridge.py --recommend "classify microbial species" --format .fastq
python galaxy_bridge.py --recommend "call variants" --format .bam
python galaxy_bridge.py --recommend "annotate variants from WES" --format .vcf
# Workflow / pipeline suggestions (new in v0.2.0)
python galaxy_bridge.py --workflow "RNA-seq differential expression"
python galaxy_bridge.py --workflow "metagenomics"
python galaxy_bridge.py --workflow "whole exome sequencing"
# Search for tools by keyword
python galaxy_bridge.py --search "metagenomics profiling"
python galaxy_bridge.py --search "variant annotation"
python galaxy_bridge.py --search "RNA-seq differential expression"
# Browse Galaxy ToolShed categories
python galaxy_bridge.py --list-categories
# View tool details (inputs, outputs, parameters)
python galaxy_bridge.py --tool-details toolshed.g2.bx.psu.edu/repos/devteam/fastqc/fastqc/0.74+galaxy1
# Run a tool on Galaxy (requires GALAXY_API_KEY)
python galaxy_bridge.py --run fastqc --input reads.fq.gz --output /tmp/qc_results
# Demo mode (works offline, no API key needed)
python galaxy_bridge.py --demoRecommendation Engine
The --recommend flag uses multi-signal scoring across 7 dimensions to rank tools:
| Signal | Max Points | Description |
|---|---|---|
| Section match | 30 | Tool's Galaxy category matches the detected task |
| Preferred tool | 20 | Tool is a known best-in-class for the task |
| Exact name match | 15 | Tool name appears in the query |
| Keyword match | 15 | Query words found in tool name/description |
| EDAM ontology | 10 | EDAM topic/operation IDs match the task |
| Format compatibility | 10 | Tool accepts the specified input format |
| Version maturity | 5 | Tools with more versions score higher (log scale) |
15 task categories are recognised: Quality Control, Read Mapping, Variant Calling, Variant Annotation, WES/WGS, RNA-seq, Metagenomics, Genome Assembly, Genome Annotation, Phylogenetics, ChIP-seq, Single-cell, Proteomics, Nanopore, BAM Processing.
8 workflow templates: WES Germline, WES Annotation, RNA-seq DE, Metagenomics Profiling, Variant Calling, ChIP-seq, Nanopore Assembly, Genome Assembly.
Show full SKILL.md (281 more words)Show less
Demo
Running --demo executes a simulated FastQC analysis using pre-cached results:
$ python galaxy_bridge.py --demo
Galaxy Bridge — Demo Mode (offline)
====================================
Tool: FastQC v0.74+galaxy1
Input: demo/demo_reads.fq (bundled synthetic FASTQ, 1000 reads)
Output: demo/fastqc_demo_output.html
Result: PASS — Per base sequence quality ✓
PASS — Per sequence quality scores ✓
WARN — Per base sequence content (normal for Illumina)
PASS — Sequence length distribution ✓
Reproducibility bundle written to demo/reproducibility/Galaxy Tool Categories
The bridge indexes tools across all 56 Galaxy ToolShed categories, including:
- Sequence Analysis (~30 tools): FastQC, Trimmomatic, Cutadapt, fastp
- Metagenomics (~25 tools): Kraken2, MetaPhlAn, HUMAnN, QIIME2
- Variant Analysis (~25 tools): VEP, SnpSift, BCFtools, FreeBayes
- RNA (~20 tools): HISAT2, StringTie, featureCounts, DESeq2
- Proteomics (~15 tools): MaxQuant, SearchGUI, PeptideShaker
- Phylogenetics (~15 tools): IQ-TREE, RAxML, MAFFT, MUSCLE
- Genome Annotation (~15 tools): Prokka, Augustus, MAKER
- Assembly (~15 tools): SPAdes, Flye, Unicycler, MEGAHIT
- Single Cell (~10 tools): Scanpy, CellRanger, Seurat
- ChIP-seq/Epigenetics (~10 tools): MACS2, deepTools, DiffBind
- GWAS (~10 tools): PLINK, REGENIE, BOLT-LMM
- Nanopore (~10 tools): NanoPlot, Medaka, minimap2
Output Structure
output_dir/
├── report.md # Analysis summary with methods and results
├── result.json # Machine-readable: tool ID, version, parameters, output paths
├── galaxy_outputs/ # Raw outputs downloaded from Galaxy
│ ├── fastqc_report.html
│ └── ...
└── reproducibility/
├── commands.sh # Portable replay recipe (CLAWBIO_ROOT / OUTPUT_DIR)
├── environment.yml # Conda environment for the run (python + bioblend)
└── checksums.sha256 # SHA-256 of the input and the downloaded outputsDependencies
Required:
- Python 3.9+
- bioblend (Galaxy Python SDK)
Optional (for execution):
GALAXY_URLenvironment variable (default:https://usegalaxy.org)GALAXY_API_KEYenvironment variable (register at usegalaxy.org)
Safety
- Local-first search: Tool discovery uses the bundled
galaxy_catalog.json— no API calls needed - API key optional: Demo mode and search work without credentials
- No data retention: Uploaded files are deleted from Galaxy after output retrieval
- Reproducibility: Every execution generates a full provenance bundle
- Disclaimer: ClawBio is a research and educational tool. It is not a medical device and does not provide clinical diagnoses. Consult a healthcare professional before making any medical decisions.
Integration with Bio Orchestrator
Triggers when: User mentions "galaxy", "usegalaxy", "tool shed", "run on galaxy", "NGS pipeline", or references a Galaxy tool ID.
Chaining partners:
pharmgx-reporter— Galaxy VEP annotates variants → PharmGx generates dosage reportclaw-metagenomics— Galaxy Kraken2 → ClawBio metagenomics profilingequity-scorer— Galaxy VCF processing → HEIM equity scoringvcf-annotator— Galaxy VEP/SnpSift ↔ ClawBio annotation
Citations
- Galaxy Project — Afgan et al. (2018) Nucleic Acids Research
- BioBlend — Sloggett et al. (2013) Bioinformatics
- usegalaxy.org — Main Galaxy public server
- Galaxy ToolShed — Community tool repository
© ClawBio, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 213 other files in skills/galaxy-bridge of ClawBio/ClawBio.
- SKILL.md
- demo/demo_reads.fq
- demo/fastqc_demo_output.html
- demo/reproducibility/commands.sh
- galaxy_bridge.py
- galaxy_catalog.json
- galaxy_skills/INDEX.md
- galaxy_skills/add-lofreq-alignment-quality-scores.md
- galaxy_skills/add-metadata.md
- galaxy_skills/align-sequences.md
- galaxy_skills/alleyoop.md
- galaxy_skills/augustus.md
- galaxy_skills/axtchain.md
- galaxy_skills/bakta.md
- galaxy_skills/bam-filter.md
- galaxy_skills/bamcompare.md
- galaxy_skills/bamleftalign.md
- galaxy_skills/bandage-image.md
- … and 196 more
Open the folder on GitHubat commit dece754
Used in 2 other repositories
We found 2 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 2 other GitHub owners. This page covers the copy in ClawBio/ClawBio, which our catalogue first saw on October 7, 2026.
Compare with similar skills
Galaxy Bridge 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.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Galaxy Bridge this skillClawBio/ClawBio | 1.2k | 2 repos | ~2.4k | Automated safety check: Pass | MIT | |
| Alphagenome Single Variant Analysisgoogle-deepmind/science-skills | 3.2k | 2 repos | ~3k | Automated safety check: Notes | Apache-2.0 | |
| 13C Metabolic Flux AnalysisK-Dense-AI/scientific-agent-skills | 48k | 1 repos | ~3.2k | Automated safety check: Pass | MIT | |
| Clinvar Databasegoogle-deepmind/science-skills | 3.2k | 2 repos | ~3.9k | Automated safety check: Notes | Apache-2.0 | |
| Metabolic Study Planneraiming-lab/AutoResearchClaw | 15k | — | ~1.9k | Automated safety check: Pass | MIT | |
| Dbsnp Databasegoogle-deepmind/science-skills | 3.2k | 2 repos | ~3.4k | Automated safety check: Notes | Apache-2.0 |
Similar skills
13C Metabolic Flux Analysis
K-Dense-AI/scientific-agent-skills
Estimates reaction fluxes inside cells from steady-state carbon-13 labeling data with a bundled mfapy-based solver, and reports which fluxes the data pin down.
Clinvar Database
google-deepmind/science-skills
A skill your agent uses when needing clinical significance, pathogenicity classifications (e.g., Pathogenic, Benign, VUS), clinical evidence rationales, or finding "hard positive" benchmark controls…
Metabolic Study Planner
aiming-lab/AutoResearchClaw
Turns a broad metabolic modelling topic into a concrete, paper-shaped plan with organism, model, perturbations, metrics and figures before any FBA code is written.
Dbsnp Database
google-deepmind/science-skills
A skill your agent uses when you want to look up, map, and search for short genetic variants (SNPs, indels) in NCBI's dbSNP database.
MFA Pipeline Orchestrator
aiming-lab/AutoResearchClaw
Runs a metabolic flux analysis from model loading to phenotype prediction and figures by handing work to four sub-agents in sequence.
More from ClawBio/ClawBio
All 104 skills in this repoEqtl Catalogue Region Fetch
ClawBio/ClawBio
Fetch a region of cis-eQTL summary statistics from EBI eQTL Catalogue v7+ via tabix-on-FTP.
Xena Tcga Gene Query
ClawBio/ClawBio
Query TCGA tumor biology through the ucscxenatoolspy API. An agent skill from ClawBio/ClawBio.
Gwas Catalog Region Fetch
ClawBio/ClawBio
Fetch a region of GWAS summary statistics from the NHGRI-EBI GWAS Catalog harmonised collection via tabix-on-FTP.
Dnasp
ClawBio/ClawBio
Population genetics of pre-aligned DNA sequences or multi-sample VCFs using selected DnaSP 6 methods.
Ld 1000g Region Compute
ClawBio/ClawBio
Compute pairwise r² between a lead variant and every variant in a window using the 1000 Genomes Phase 3 GRCh38 reference panel, ancestry-stratified.
Ncbi Datasets
ClawBio/ClawBio
Download genomes, genes, virus sequences, and taxonomy data from NCBI using the datasets and dataformat CLI tools.
Related
Categories
Questions about Galaxy Bridge
What does Galaxy Bridge do?
Galaxy tool discovery, intelligent recommendation, and execution — 8,000+ bioinformatics tools from usegalaxy.org with multi-signal scoring and workflow suggestions. Galaxy Bridge is an agent skill from ClawBio/ClawBio.
When should I use Galaxy Bridge?
Galaxy Bridge fits situations like: tasks that involve Bioinformatics.
How do I install Galaxy Bridge in Claude Code?
Run `npx skills add ClawBio/ClawBio --skill galaxy-bridge -a claude-code`. Or copy the skill folder (skills/galaxy-bridge in ClawBio/ClawBio) into .claude/skills/galaxy-bridge in your project. Claude Code loads it when a task matches its description.
How do I install Galaxy Bridge in Codex?
Run `npx skills add ClawBio/ClawBio --skill galaxy-bridge -a codex`. Or copy the skill folder (skills/galaxy-bridge in ClawBio/ClawBio) into .agents/skills/galaxy-bridge in your project. Codex loads it when a task matches its description.
Can I use Galaxy Bridge 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 ClawBio/ClawBio --skill galaxy-bridge -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/galaxy-bridge, .gemini/skills/galaxy-bridge, .github/skills/galaxy-bridge and .opencode/skills/galaxy-bridge in your project.
What does Galaxy Bridge need to run?
Going by SKILL.md and its folder, Galaxy Bridge needs a shell and Python for the scripts in its folder, the command-line tools its instructions call (python) and credentials named GALAXY_API_KEY. Our summary lists: Python 3; A Bash shell; A credential in GALAXY_API_KEY.
Does Galaxy Bridge access the network?
SKILL.md names 4 domains. In commands or code: usegalaxy.org; the agent is likely to contact it when it follows the instructions. As links in the text: galaxyproject.org, bioblend.readthedocs.io and toolshed.g2.bx.psu.edu. This is read from the text; nothing was executed.
Is Galaxy Bridge 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 Galaxy Bridge use?
Galaxy Bridge is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Galaxy Bridge use?
About 2.4k tokens (SKILL.md is roughly 9.8k 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 Galaxy Bridge?
Skills that share tags, products or a category with Galaxy Bridge: Alphagenome Single Variant Analysis (google-deepmind/science-skills, 3.2k stars), 13C Metabolic Flux Analysis (K-Dense-AI/scientific-agent-skills, 48k stars), Clinvar Database (google-deepmind/science-skills, 3.2k stars) and Metabolic Study Planner (aiming-lab/AutoResearchClaw, 15k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Galaxy Bridge?
ClawBio (a GitHub organization) maintains it in ClawBio/ClawBio, which has 1,154 GitHub stars. The repository holds 104 skills in this directory. The repository was last updated on October 8, 2026.
Source: ClawBio/ClawBio on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.