Agent skill

open-targets-platform

Query the Open Targets Platform for drug-target-disease associations. Use whenever the user asks about drug targets, gene-disease associations, drug indications, clinical trial phases, or wants to look up any entity (Ensembl gene ID, ChEMBL drug ID, or free-text gene/drug name) in Open Targets. Also trigger when the user mentions Open Targets, ENSG IDs, CHEMBL IDs, or asks about target prioritization for diseases.

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

# Open Targets Platform Query Skill Query the Open Targets GraphQL API for drug, target, and disease association data. No API key required. ## Entity Auto-Detection | Input Pattern | Detected As | Example | |---|---|---| | `ENSG00000...` | Target (Ensembl gene ID) | `ENSG00000146648` (EGFR) | | `CHEMBL...` | Drug (ChEMBL ID) | `CHEMBL941` (Imatinib) | | anything else | Free-text search | `BRCA1`, `aspirin` | ## API | Function | Input | Returns | |---|---|---| | `query(entity)` | single entity string | dict with type, name, associations | | `query_batch(entities)` | list of entity strings | list[dict] | | `summarize(result)` | query result dict | compact one-line text | | `get_target_info(ensembl_id)` | Ensembl ID string | raw GraphQL response | | `get_drug_info(chembl_id)` | ChEMBL ID string | raw GraphQL response | | `search_entities(term)` | free-text string | raw GraphQL response | ## Return Format **Target result:** ```json {"entity": "ENSG00000146648", "type": "target", "found": true, "symbol": "EGFR", "name": "epidermal growth factor receptor", "biotype": "protein_coding", "top_diseases": [{"disease": "lung carcinoma", "score": 0.78}]} ``` **Drug result:** ```json {"entity":

What's inside
Steps it walks through
  1. Entity Auto-Detection
  2. API
  3. Return Format
  4. Usage
  5. Source
Ships with 5 files
  • README.md
  • __init__.py
  • example.py
  • open_targets_skill.py
  • retrieve.py
More from awesome-bio-agent-skills
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About this skill
What does the open-targets-platform skill do?

Query the Open Targets Platform for drug-target-disease associations. Use whenever the user asks about drug targets, gene-disease associations, drug indications, clinical trial phases, or wants to look up any entity (Ensembl gene ID, ChEMBL drug ID, or free-text gene/drug name) in Open Targets. Also trigger when the user mentions Open Targets, ENSG IDs, CHEMBL IDs, or asks about target prioritization for diseases.

How do I install it?

Run `npx skills add BioTender-max/awesome-bio-agent-skills --skill open_targets --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.

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