Mecddi
Skill BioTender-max/awesome-bio-agent-skills/skills/drugclaw/mecddi
Query the MecDDI mechanism-based drug-drug interaction database. Use whenever the user asks about drug-drug interactions, DDI mechanisms (PK/PD), enzyme or transporter-mediated interactions, or wants to look up interacting drug pairs by drug name or MecDDI drug ID. Trigger on keywords like DDI, drug interaction, MecDDI, mechanism-based interaction, pharmacokinetic interaction, pharmacodynamic interaction, or any query involving two drugs that may interact.From its SKILL.md
npx -y skills add BioTender-max/awesome-bio-agent-skills --skill mecddiAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
One thing to look at
- no licenseNo license file was found in the repository. Code published without one is not open source by default, so using it at work is a question for whoever answers licensing questions where you are.
SKILL.md
2.2 KB, 528 tokens by cl100k_base, as published. Nobody here has run it
MecDDI Query Skill
Search MecDDI drug-drug interaction records by drug name or drug ID. Auto-detects input type:
| Input Pattern | Detected As | Match Logic |
|---|---|---|
D0123 | MecDDI Drug ID | exact on A_Drug_ID / B_Drug_ID |
| anything else | free text | substring on A_Drug_Name / B_Drug_Name |
Mechanism Categories (7 files)
| Category | Type |
|---|---|
| Affected Gastrointestinal Absorption | PK |
| Affected Cellular Transport | PK |
| Affected Organization Distribution | PK |
| Affected Intra/Extra-Hepatic Metabolism | PK |
| Affected Excretion Pathways | PK |
| Pharmacodynamic Additive Effects | PD |
| Pharmacodynamic Antagonistic Effects | PD |
API
| Function | Input | Returns |
|---|---|---|
load_mecddi(data_dir) | directory path | list[dict] (all records) |
search(records, entity) | single entity string | list[dict] |
search_batch(records, entities) | list of strings | dict[str, list[dict]] |
summarize(hits, entity) | hits + label | compact text for LLM |
to_json(hits) | list[dict] | JSON string |
Data
- Source: 7 TSV files downloaded from https://mecddi.idrblab.net/download
- Path:
DATA_DIRvariable in19_MecDDI.py(default:resources_metadata/ddi/MecDDI) - Columns:
A_Drug_ID,A_Drug_Name,B_Drug_ID,B_Drug_Name,Mechanism_Category
Usage
See if __name__ == "__main__" block in 19_MecDDI.py for runnable examples covering:
- Single drug name →
search(data, "Atropine") - Single drug ID →
search(data, "D0123") - Batch query →
search_batch(data, ["Meclizine", "Isocarboxazid", "D0853"]) - JSON output →
to_json(hits) - LLM-friendly summary →
summarize(hits, entity)
What ships with it: 5 files
9.2 KB alongside SKILL.md, 4 of them executable
- example.pyruns4.1 KB
- __init__.pyruns130 B
- mecddi_skill.pyruns3.1 KB
- README.md1.1 KB
- retrieve.pyruns793 B