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Query a locally downloaded DrugBank database. Use whenever the user asks about drug information, drug targets, drug-drug interactions, drug categories, or wants to look up any entity (DrugBank ID, drug name, CAS number, synonym) in DrugBank.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
SOC 직업 분류 기준
Query the DrugComb drug combination database for cancer cell-line synergy and sensitivity data. Use whenever the user asks about drug combinations, synergy scores (ZIP/Bliss/Loewe/HSA), combination sensitivity (CSS), or wants to look up how two drugs interact in a specific cancer cell line.
Query canonical DrugCombDB combination records. Use when the user asks about drug pairs, synergy values, or cell-line-specific combination evidence.
Query or inspect the FDA Orange Book - FDA-Approved Drug Products Listing resource for drug-centric tasks with emphasis on drug knowledgebase Use whenever Codex needs the calling pattern, downloadable entrypoint, or example query flow from this skill example script.
Query the RepurposeDrugs single-agent drug repurposing database. Use whenever the user asks about drug-disease repurposing associations, clinical trial phases for repurposed drugs, or wants to look up any entity (drug name, disease name, NCT ID) in RepurposeDrugs.
Query the Gene-Drug Knowledge Database (GDKD) for variant-specific gene–drug associations in oncology. Use when the user asks about cancer genomic biomarkers, drug sensitivity/resistance by gene or variant, targetable mutations, or clinical evidence for cancer therapeutics.
Query canonical TarKG drug-target triplets. Use when the user asks about drug-target interactions, relation labels, disease/pathway context, or quick lookups for drugs/targets in TarKG.
| name | drugbank-query |
| description | Query a locally downloaded DrugBank database. Use whenever the user asks about drug information, drug targets, drug-drug interactions, drug categories, or wants to look up any entity (DrugBank ID, drug name, CAS number, synonym) in DrugBank. |
Search local DrugBank data by any entity. Auto-detects query type:
| Input Pattern | Detected As | Match Logic |
|---|---|---|
DB00945 | DrugBank ID | exact on drugbank_id |
| anything else | free text | substring on name, synonyms, cas_number |
resources_metadata/drug_knowledgebase/DrugBank/full database.xml — rich fields: description, targets, interactions, categories, synonyms, groupsdrugbank vocabulary.csv — lightweight: DrugBank ID, name, CAS, synonyms| Function | Input | Returns |
|---|---|---|
load(path) | file path (XML or TSV/CSV, auto-detected) | list[dict] |
search(data, entity) | single entity string | list[dict] |
search_batch(data, entities) | list or comma-separated string | dict[str, list[dict]] |
summarize(hits, entity) | hit list + label | compact text |
to_json(hits) | hit list | JSON string |
from 07_DrugBank import load, search, search_batch, summarize, to_json
data = load() # auto-selects XML or CSV
# single query
hits = search(data, "aspirin")
print(summarize(hits, "aspirin"))
# batch query
results = search_batch(data, ["metformin", "DB00316", "ibuprofen"])
for entity, hits in results.items():
print(summarize(hits, entity))
# JSON output
print(to_json(hits[:1]))
See if __name__ == "__main__" block in 07_DrugBank.py for runnable examples.