Brenda Database Agent Skill
BRENDA Enzyme DB SOAP/REST queries: kinetic parameters (Km, Vmax, kcat, Ki), EC classes, substrate specificity, inhibitors, cofactors, organism data. 80K+ enzymes, 7M+ values. Free academic registration. For metabolic modeling use cobrapy-metabolic-modeling; metabolites use hmdb-database.
Install
one command, takes just this skill from the repositorynpx skills add https://github.com/BioTender-max/awesome-bio-agent-skills --skill brenda-databaseOther skills for the same job
different authors, same section of the catalogue
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Direct REST API access to KEGG (academic use only). Pathway analysis, gene-pathway mapping, metabolic pathways, drug interactions, ID conversion. For Python workflows with multiple databases, prefer bioservices. Use this for direct HTTP/REST work or KEGG-specific control.
Direct REST API access to PubMed. Advanced Boolean/MeSH queries, E-utilities API, batch processing, citation management. For Python workflows, prefer biopython (Bio.Entrez). Use this for direct HTTP/REST work or custom API implementations.
Access USPTO APIs for patent/trademark searches, examination history (PEDS), assignments, citations, office actions, TSDR, for IP analysis and prior art searches.
How to use it
Take biotender-max/awesome-bio-agent-brenda-database from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.
The instructions reference pip.
Without those the skill loads but fails at the first command.