Agent skill · Databases

16_DGIdb

Query the DGIdb (Drug-Gene Interaction Database) for drug-gene interactions, gene druggability categories, and drug target information. Use whenever the user asks about drug targets, druggable genes, gene-drug interactions, or wants to look up any entity (gene name, drug name, druggability category) in DGIdb.

BioTender-maxgithub.com/BioTender-maxGitHub ↗
claude-codeships scriptsNOASSERTION
Install
npx skills add BioTender-max/awesome-bio-agent-skills --skill dgidb --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 6
SKILL.md size: 2 KB
Bundled scripts: yes
Path: skills/drugclaw/dgidb/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 135
Language: Python

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# DGIdb Query Skill Search DGIdb records by any entity. Auto-detects type by naming convention: | Input Pattern | Detected As | Example | |---|---|---| | ALL-CAPS ≤15 chars | Gene | `EGFR`, `BRAF`, `TP53` | | Known category keyword | Druggability category | `clinically actionable`, `kinase` | | Anything else | Drug | `imatinib`, `erlotinib` | Supported category keywords: `clinically actionable`, `drug resistance`, `druggable genome`, `tumor suppressor`, `transcription factor`, `kinase`, `g protein coupled receptor`, `hormone activity`, `ion channel`, `protease`, `dna repair`. ## API | Function | Input | Returns | |---|---|---| | `search(entity)` | single entity string | `list[dict]` | | `search_batch(entities)` | list of entity strings | `dict[str, list[dict]]` | | `summarize(results, entity)` | result list + label | compact text for LLM | | `to_json(results)` | result list | `list[dict]` (passthrough) | ## Key Fields **Gene result**: `name`, `long_name`, `categories`, `interaction_count`, `interactions[]` (each with `drug`, `drug_concept_id`, `score`, `types`, `directionality`, `attributes`, `pmids`, `sources`). **Drug result**: `name`, `concept_id`, `approval_ratings`, `interacti

What's inside
Steps it walks through
  1. API
  2. Key Fields
  3. Usage
  4. Data Source
Ships with 5 files
  • README.md
  • __init__.py
  • dgidb_skill.py
  • example.py
  • retrieve.py
More from awesome-bio-agent-skills
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About this skill
What does the 16_DGIdb skill do?

Query the DGIdb (Drug-Gene Interaction Database) for drug-gene interactions, gene druggability categories, and drug target information. Use whenever the user asks about drug targets, druggable genes, gene-drug interactions, or wants to look up any entity (gene name, drug name, druggability category) in DGIdb.

How do I install it?

Run `npx skills add BioTender-max/awesome-bio-agent-skills --skill dgidb --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From BioTender-max/awesome-bio-agent-skills, a repository with 135 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

Keep going