pharmkg-query
Query the PharmKG knowledge graph (180k entities, 39 relation types, >1M triples). Use whenever the user asks about biomedical relationships among genes, drugs/chemicals, and diseases — e.g. drug–gene interactions, drug–disease associations, gene–disease links, or drug–drug relationships derived from literature and curated databases.
npx skills add BioTender-max/awesome-bio-agent-skills --skill pharmkg --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# PharmKG Query Skill Search PharmKG triples by entity name. Matching is case-insensitive; exact match is tried first via a prebuilt index, with substring fallback. | Input Example | Matches On | |---|---| | `aspirin` | exact on Entity1\_name or Entity2\_name | | `BRCA1` | exact / substring on entity names | | `Alzheimer Disease` | substring on entity names | ## Entity & Relation Types **Entities** (~188 k): Drug/Chemical (DrugBank, ChEMBL), Gene/Protein (Entrez, UniProt), Disease (DO, MeSH). **Relations** (39 types): chemical–gene (inhibition, activation, binding …), chemical–disease (treatment, marker, risk factor), gene–disease (association, marker), chemical–chemical (similarity, interaction), and others. ## API | Function | Input | Returns | |---|---|---| | `load_pharmkg(path)` | CSV path | `list[dict]` of triples | | `_build_index(triples)` | triple list | `dict[str, list]` (entity→triples) | | `search(triples, entity, index=)` | entity string | `list[dict]` | | `search_batch(triples, entities, index=)` | list of strings | `dict[str, list]` | | `summarize(hits, entity)` | hits + label | compact text | | `to_json(hits)` | hits | JSON string | ## Usage See `if __name__ == "__ma
- Entity & Relation Types
- API
- Usage
- Data
What does the pharmkg-query skill do?
Query the PharmKG knowledge graph (180k entities, 39 relation types, >1M triples). Use whenever the user asks about biomedical relationships among genes, drugs/chemicals, and diseases — e.g. drug–gene interactions, drug–disease associations, gene–disease links, or drug–drug relationships derived from literature and curated databases.
How do I install it?
Run `npx skills add BioTender-max/awesome-bio-agent-skills --skill pharmkg --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 BioTender-max/awesome-bio-agent-skills, a repository with 135 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.