How do I install the Mecddi Query skill?

Run npx skillmds@latest add gabrielmoreira/mecddi-query in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Mecddi Query safe to use?

This skill has not completed SkillMD's automated safety review yet. Independent scanners report: SkillSpector: PASS, Skill Scanner: PASS. Capability flags: executes scripts, makes network calls. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Mecddi Query?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Mecddi Query free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Mecddi Query?

gabrielmoreira (@gabrielmoreira) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Mecddi Query by gabrielmoreira — Agent Skill

Name: Mecddi Query
Rating: 4.666666666666667 (3 reviews)
Author: gabrielmoreira

Mecddi Query

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.

gabrielmoreira Updated Sep 9, 2026 17 repo stars

File contents

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_DIR variable in 19_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)

---name: mecddi-querydescription: 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.--- # 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_DIR` variable in `19_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: 1. **Single drug name** → `search(data, "Atropine")` 2. **Single drug ID** → `search(data, "D0123")` 3. **Batch query** → `search_batch(data, ["Meclizine", "Isocarboxazid", "D0853"])` 4. **JSON output** → `to_json(hits)` 5. **LLM-friendly summary** → `summarize(hits, entity)`

Frequently asked questions