Agent skill · Databases

bioservices

Primary Python tool for 40+ bioinformatics services. Preferred for multi-database workflows: UniProt, KEGG, ChEMBL, PubChem, Reactome, QuickGO. Unified API for queries, ID mapping, pathway analysis. For direct REST control, use individual database skills (uniprot-database, kegg-database).

FreedomIntelligencegithub.com/FreedomIntelligenceGitHub ↗
claude-codeships scripts
Install
npx skills add FreedomIntelligence/OpenClaw-Medical-Skills --skill bioservices --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 8
SKILL.md size: 10 KB
Bundled scripts: yes
Path: skills/bioservices/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 2,909
Language: Python
Read our review of the source →

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# BioServices ## Overview BioServices is a Python package providing programmatic access to approximately 40 bioinformatics web services and databases. Retrieve biological data, perform cross-database queries, map identifiers, analyze sequences, and integrate multiple biological resources in Python workflows. The package handles both REST and SOAP/WSDL protocols transparently. ## When to Use This Skill This skill should be used when: - Retrieving protein sequences, annotations, or structures from UniProt, PDB, Pfam - Analyzing metabolic pathways and gene functions via KEGG or Reactome - Searching compound databases (ChEBI, ChEMBL, PubChem) for chemical information - Converting identifiers between different biological databases (KEGG↔UniProt, compound IDs) - Running sequence similarity searches (BLAST, MUSCLE alignment) - Querying gene ontology terms (QuickGO, GO annotations) - Accessing protein-protein interaction data (PSICQUIC, IntactComplex) - Mining genomic data (BioMart, ArrayExpress, ENA) - Integrating data from multiple bioinformatics resources in a single workflow ## Core Capabilities ### 1. Protein Analysis Retrieve protein information, sequences, and functional annotations

What's inside
Steps it walks through
  1. Overview
  2. When to Use This Skill
  3. Core Capabilities
  4. 1. Protein Analysis
  5. 2. Pathway Discovery and Analysis
  6. 3. Compound Database Searches
  7. 4. Sequence Analysis
  8. 5. Identifier Mapping
  9. 6. Gene Ontology Queries
  10. 7. Protein-Protein Interactions
  11. Multi-Service Integration Workflows
  12. Complete Protein Analysis Pipeline
  13. Pathway Network Analysis
  14. Cross-Database Compound Search
Ships with 7 files
  • references/identifier_mapping.md
  • references/services_reference.md
  • references/workflow_patterns.md
  • scripts/batch_id_converter.py
  • scripts/compound_cross_reference.py
  • scripts/pathway_analysis.py
  • scripts/protein_analysis_workflow.py
Commands it runs
python scripts/protein_analysis_workflow.py ZAP70_HUMAN your.email@example.com
python scripts/pathway_analysis.py hsa output_directory/
python scripts/compound_cross_reference.py Geldanamycin
python scripts/batch_id_converter.py input_ids.txt --from UniProtKB_AC-ID --to KEGG
uv pip install bioservices
More from OpenClaw-Medical-Skills
All skills →
About this skill
What does the bioservices skill do?

Primary Python tool for 40+ bioinformatics services. Preferred for multi-database workflows: UniProt, KEGG, ChEMBL, PubChem, Reactome, QuickGO. Unified API for queries, ID mapping, pathway analysis. For direct REST control, use individual database skills (uniprot-database, kegg-database).

How do I install it?

Run `npx skills add FreedomIntelligence/OpenClaw-Medical-Skills --skill bioservices --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From FreedomIntelligence/OpenClaw-Medical-Skills, a repository with 2,909 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

Keep going