菜单
Query the DrugLib.com Drug Review Dataset (UCI #461). Use whenever the user asks about patient drug reviews, drug effectiveness ratings, side-effect profiles, or condition-specific treatment experiences from DrugLib.com.
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
基于 SOC 职业分类
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 | druglib-reviews |
| description | Query the DrugLib.com Drug Review Dataset (UCI #461). Use whenever the user asks about patient drug reviews, drug effectiveness ratings, side-effect profiles, or condition-specific treatment experiences from DrugLib.com. |
Search patient drug reviews by drug name or medical condition. Auto-detects entity type and routes to the appropriate field.
| Input Pattern | Detected As | Match Logic |
|---|---|---|
single/two-word term (e.g. lamictal) | drug name | substring on urlDrugName |
multi-word or medical keyword (e.g. bipolar disorder) | condition | substring on condition |
Condition keywords that trigger condition routing: disease, disorder, syndrome, infection, pain, cancer, diabetes, hypertension, depression, anxiety, asthma, arthritis, migraine, allergy, insomnia, nausea, obesity, acne, gerd, copd.
| Function | Input | Returns |
|---|---|---|
load_reviews() | — | list[dict] (cached) |
search(entity) | single entity string | list[dict] |
search_batch(entities) | list of entity strings | dict[str, list[dict]] |
summarize(hits, entity) | list[dict] + label | compact LLM-readable text |
to_json(hits) | list[dict] | list[dict] (JSON-serialisable) |
See if __name__ == "__main__" block in 16_DRUGLIB_REVIEWS.py for runnable
examples covering: drug name search, condition search, batch search, and JSON
output.
drugLibTrain_raw.tsv, drugLibTest_raw.tsv (TSV, merged at load)DATA_DIR variable in 16_DRUGLIB_REVIEWS.py| Column | Type | Description |
|---|---|---|
urlDrugName | str | Drug name (lowercase, URL-style) |
rating | int 0–9 | Overall patient satisfaction |
effectiveness | str | Highly / Considerably / Moderately / Marginally Effective, Ineffective |
sideEffects | str | No / Mild / Moderate / Severe / Extremely Severe Side Effects |
condition | str | Medical condition being treated |
benefitsReview | str | Free-text review of benefits |
sideEffectsReview | str | Free-text review of side effects |
commentsReview | str | Free-text general comments |