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Query the Precision Medicine Knowledge Graph (PrimeKG) for multiscale biological data including genes, drugs, diseases, phenotypes, and more.
Passed 15 of 19 test cases with the skill, and 3 of 19 without it.
and 12 more in the full report
14 fixed3 passed either way4 still failing1 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 14 test cases the skill fixed. Same model, same prompt, with and without the skill.
When looking up clinical signs and symptoms for a rare disease ID in the knowledge graph, what exact relation_type filter should be supplied to get_neighbors?
| Checked | Without skill | With skill |
|---|---|---|
| Identifies disease_phenotype as the relation_type parameter value | Missed | Passed |
The instructions your model reads when the skill loads.
PrimeKG is a precision medicine knowledge graph that integrates over 20 primary databases and high-quality scientific literature into a single resource. It contains over 100,000 nodes and 4 million edges across 29 relationship types, including drug-target, disease-gene, and phenotype-disease associations.
Key capabilities:
Data access: Programmatic access via query_primekg.py. Data is stored at C:\Users\eamon\Documents\Data\PrimeKG\kg.csv.
This skill should be used when:
Find identifiers for genes, drugs, or diseases.
from scripts.query_primekg import search_nodes
# Search for Alzheimer's disease nodes
results = search_nodes("Alzheimer", node_type="disease")
# Returns: [{"id": "EFO_0000249", "type": "disease", "name": "Alzheimer's disease", ...}]
test cases passed, vs 3 / 19 without
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