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Query the WHO Model List of Essential Medicines (23rd list, 2023). Use whenever the user asks about essential medicines, WHO-recommended drugs, dosage forms, therapeutic sections, or AWaRe antibiotic classification.
Codex または Claude でインストール この Prompt をコピーして Codex、Claude、または他のアシスタントに貼り付けると、Skill ページを確認してインストールできます。
SOC 職業分類に基づく
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 | WHO-EML-query |
| description | Query the WHO Model List of Essential Medicines (23rd list, 2023). Use whenever the user asks about essential medicines, WHO-recommended drugs, dosage forms, therapeutic sections, or AWaRe antibiotic classification. |
Search ~500 WHO essential medicines by name, section, or section number. Case-insensitive substring match.
| Input Example | Matches On |
|---|---|
amoxicillin | medicine name |
antimalarial | section hierarchy (full path) |
diabetes | section hierarchy |
6.2 | section_num prefix |
| Function | Input | Returns |
|---|---|---|
load_eml(cache_path) | JSON path | list[dict] |
build_cache(pdf_path, cache_path) | PDF + cache paths | list[dict] (parses PDF → JSON) |
search(data, entity) | single string | list[dict] |
search_batch(data, entities) | list of strings | dict[str, list[dict]] |
summarize(hits, entity) | list[dict] + label | compact text |
to_json(hits) | list[dict] | list[dict] |
| Field | Example |
|---|---|
medicine | amoxicillin |
section_num | 6.2.1 |
section_name | Anti-infective medicines > Antibacterials > Access group antibiotics |
dosage_forms | ["Capsule: 250 mg; 500 mg", "Oral liquid: 125 mg/5 mL"] |
See if __name__ == "__main__" block in 59_WHO_EML.py for runnable examples.
WHO EML 23rd List (2023).pdf in DATA_DIRwho_eml_23.json (auto-built on first run from PDF)pip install pypdf