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Agent skill

Open Targets DB

by aipoch in aipoch/medical-research-skills

Query the Open Targets Platform to retrieve targets, diseases, or evidence records when you need target-disease association data and evidence-based scores for therapeutic discovery.

MITAuto-check passedResearch & Science

Install Open Targets DB

skills CLI
$ npx skills add aipoch/medical-research-skills --skill open-targets-db -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install aipoch/medical-research-skills open-targets-db --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/aipoch/medical-research-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/'scientific-skills/Evidence Insight/open-targets-db' .claude/skills/open-targets-db && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
open-targets-db
GitHub stars
2k
Token cost
~1.6k tokens
SKILL.md length
719 words
Files
4 (incl. scripts, references)
Skills in repo
578
Repo updated
First seen
Licence
MIT

At a glance

Query the Open Targets Platform to retrieve targets, diseases, or evidence records when you need target-disease association data and evidence-based scores for therapeutic discovery.

  • Works in 4 steps: Validate the request against the skill… → Select the documented execution path and… → Produce the expected output using the… → …
  • Research & Science work in your project
  • SKILL.md covers When to Use, Key Features, Dependencies and Example Usage, plus 11 more sections
  • Runs Python scripts from its folder; calls python

What it does

Open Targets DB is an agent skill from aipoch/medical-research-skills. Query the Open Targets Platform to retrieve targets, diseases, or evidence records when you need target-disease association data and evidence-based scores for therapeutic discovery.

Its SKILL.md is about 1.6k tokens, which your agent loads only when the skill is triggered. The skill folder holds 5 other files, including scripts and reference files (for example `open-targets-db_audit_result_v2.json`, `references/api_reference.md` and `scripts/query_opentargets.py`).

It sits in Research & Science. It works with Ensembl. The repository describes itself as: Hundreds of agent skills for medical research, including protocol design, data analysis, evidence insights, and academic writing. The licence is MIT.

When your agent uses it

  • Research & Science work in your project

Example prompts

  • “/open-targets-db”

Requirements

  • Python 3

Workflow steps

4 steps, taken from the first numbered list in SKILL.md.

  1. Validate the request against the skill boundary and confirm all required inputs are present.
  2. Select the documented execution path and prefer the simplest supported command or procedure.
  3. Produce the expected output using the documented file format, schema, or narrative structure.
  4. Run a final validation pass for completeness, consistency, and safety before returning the result.

What it can do on your machine

Read from SKILL.md and the folder at commit 686e09d. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 1 file in scripts/ (Python), which the agent can run.

    Shell commands in SKILL.md call:

    • python

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Open Targets DB loads about 1.6k tokens when it runs, and up to ~1.7k if it reads all its reference files. Until then it costs about 49 tokens; SKILL.md has 719 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~49
When it runs · the whole SKILL.md, loaded when a task matches
~1.6k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~1.7k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from aipoch/medical-research-skills at commit 686e09d, republished under its MIT licence (© aipoch). 719 words, ~1,551 tokens.

Download SKILL.mdSave it as .claude/skills/open-targets-db/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.
name
open-targets-db
description
Query the Open Targets Platform to retrieve targets, diseases, or evidence records when you need target-disease association data and evidence-based scores for therapeutic discovery.
license
MIT
author
AIPOCH

Source: https://github.com/aipoch/medical-research-skills

When to Use

  • You have a disease (e.g., an EFO ID) and want to discover and prioritize candidate therapeutic targets.
  • You have a target (e.g., an Ensembl gene ID) and need to review associated diseases and supporting evidence.
  • You need evidence-level details (e.g., GWAS, ClinVar, ChEMBL) to justify or audit a target-disease association.
  • You want to compare association strength across targets/diseases using Open Targets evidence scoring.
  • You are building a pipeline that programmatically fetches curated target-disease associations from Open Targets.

Key Features

  • Entity querying by type: target, disease, or evidence.
  • Target discovery for diseases using Open Targets associations.
  • Association scoring based on Open Targets evidence aggregation (harmonic-sum style aggregation across evidence sources).
  • Evidence retrieval from integrated sources such as GWAS, ClinVar, ChEMBL, pathways, and other curated datasets.
  • Field selection to request only specific fields (optional) for smaller payloads.

Dependencies

  • Python >=3.8
  • requests >=2.25

Example Usage

Run a target query by Ensembl ID (example: BRAF ENSG00000157764):

bash
python scripts/query_opentargets.py --id "ENSG00000157764" --type target

Optional: request specific fields (if supported by your script/API wrapper):

bash
python scripts/query_opentargets.py \
  --id "ENSG00000157764" \
  --type target \
  --fields "approvedSymbol,biotype,tractability"

Implementation Details

  • Inputs

    • query_type (required, string): Entity type to query. Supported values: target, disease, evidence.
    • id (required, string): Entity identifier (e.g., Ensembl ID for targets, EFO ID for diseases).
    • fields (optional, array): A list of fields to retrieve to limit the response payload.

  • Outputs

    • data (json): The parsed response returned by the Open Targets API for the requested entity.

  • Scoring model (conceptual)

    • Open Targets aggregates evidence across multiple evidence sources (genetics, drugs/chemistry, pathways, literature/curation, etc.).
    • Association scores are computed by combining evidence contributions; the platform commonly uses harmonic-sum style aggregation to prevent any single evidence type from dominating while still rewarding multiple independent evidence lines.

  • Reference

    • See references/api_reference.md for API details, available fields, and entity schemas.

When Not to Use

  • Do not use this skill when the required source data, identifiers, files, or credentials are missing.
  • Do not use this skill when the user asks for fabricated results, unsupported claims, or out-of-scope conclusions.
  • Do not use this skill when a simpler direct answer is more appropriate than the documented workflow.

Required Inputs

  • A clearly specified task goal aligned with the documented scope.
  • All required files, identifiers, parameters, or environment variables before execution.
  • Any domain constraints, formatting requirements, and expected output destination if applicable.
  1. Validate the request against the skill boundary and confirm all required inputs are present.
  2. Select the documented execution path and prefer the simplest supported command or procedure.
  3. Produce the expected output using the documented file format, schema, or narrative structure.
  4. Run a final validation pass for completeness, consistency, and safety before returning the result.
Show full SKILL.md (289 more words)Show less

Deterministic Output Rules

  • Use the same section order for every supported request of this skill.
  • Keep output field names stable and do not rename documented keys across examples.
  • If a value is unavailable, emit an explicit placeholder instead of omitting the field.

Output Contract

  • Return a structured deliverable that is directly usable without reformatting.
  • If a file is produced, prefer a deterministic output name such as open_targets_db_result.md unless the skill documentation defines a better convention.
  • Include a short validation summary describing what was checked, what assumptions were made, and any remaining limitations.

Validation and Safety Rules

  • Validate required inputs before execution and stop early when mandatory fields or files are missing.
  • Do not fabricate measurements, references, findings, or conclusions that are not supported by the provided source material.
  • Emit a clear warning when credentials, privacy constraints, safety boundaries, or unsupported requests affect the result.
  • Keep the output safe, reproducible, and within the documented scope at all times.

Failure Handling

  • If validation fails, explain the exact missing field, file, or parameter and show the minimum fix required.
  • If an external dependency or script fails, surface the command path, likely cause, and the next recovery step.
  • If partial output is returned, label it clearly and identify which checks could not be completed.

Completion Checklist

  • Confirm all required inputs were present and valid.
  • Confirm the supported execution path completed without unresolved errors.
  • Confirm the final deliverable matches the documented format exactly.
  • Confirm assumptions, limitations, and warnings are surfaced explicitly.

Quick Validation

Run this minimal verification path before full execution when possible:

bash
python scripts/query_opentargets.py --help

Expected output format:

text
Result file: open_targets_db_result.md
Validation summary: PASS/FAIL with brief notes
Assumptions: explicit list if any

Scope Reminder

  • Core purpose: Query the Open Targets Platform to retrieve targets, diseases, or evidence records when you need target-disease association data and evidence-based scores for therapeutic discovery.

© aipoch, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 3 other files (scripts, references) in scientific-skills/Evidence Insight/open-targets-db of aipoch/medical-research-skills.

  • SKILL.md
  • open-targets-db_audit_result_v2.json
  • references/api_reference.md
  • scripts/query_opentargets.py

Open the folder on GitHubat commit 686e09d

Compare with similar skills

Open Targets DB next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Open Targets DB compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Open Targets DB this skillaipoch/medical-research-skills2k—~1.6kAutomated safety check: PassMIT
Human Protein Atlas Databasegoogle-deepmind/science-skills3.2k2 repos~1.6kAutomated safety check: PassApache-2.0
External API ChangeGuyTeichman/RNAlysis139—~1.8kAutomated safety check: PassMIT
Ensembl Databasedavila7/claude-code-templates32k10 repos~2.1kAutomated safety check: PassMIT
Bio DB ToolsDrugClaw/DrugClaw125—~1.4kAutomated safety check: PassApache-2.0
Annotating Variantsmaziyarpanahi/openmed5.5k—~2.1kAutomated safety check: PassApache-2.0

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Works with

Categories

Questions about Open Targets DB

What does Open Targets DB do?

Query the Open Targets Platform to retrieve targets, diseases, or evidence records when you need target-disease association data and evidence-based scores for therapeutic discovery. Open Targets DB is an agent skill from aipoch/medical-research-skills. Query the Open Targets Platform to retrieve targets, diseases, or evidence records when you need target-disease association data and evidence-based scores for therapeutic discovery.

When should I use Open Targets DB?

Open Targets DB fits situations like: research & Science work in your project.

How do I install Open Targets DB in Claude Code?

Run `npx skills add aipoch/medical-research-skills --skill open-targets-db -a claude-code`. Or copy the skill folder (scientific-skills/Evidence Insight/open-targets-db in aipoch/medical-research-skills) into .claude/skills/open-targets-db in your project. Claude Code loads it when a task matches its description.

How do I install Open Targets DB in Codex?

Run `npx skills add aipoch/medical-research-skills --skill open-targets-db -a codex`. Or copy the skill folder (scientific-skills/Evidence Insight/open-targets-db in aipoch/medical-research-skills) into .agents/skills/open-targets-db in your project. Codex loads it when a task matches its description.

Can I use Open Targets DB in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add aipoch/medical-research-skills --skill open-targets-db -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/open-targets-db, .gemini/skills/open-targets-db, .github/skills/open-targets-db and .opencode/skills/open-targets-db in your project.

What does Open Targets DB need to run?

Going by SKILL.md and its folder, Open Targets DB needs Python for the scripts in its folder and the command-line tools its instructions call (python). Our summary lists: Python 3.

Does Open Targets DB access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Open Targets DB safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Open Targets DB use?

Open Targets DB is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Open Targets DB use?

About 1.6k tokens (SKILL.md is roughly 6.2k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 169 tokens, read only when the agent opens those files.

What are the alternatives to Open Targets DB?

Skills that share tags, products or a category with Open Targets DB: Human Protein Atlas Database (google-deepmind/science-skills, 3.2k stars), External API Change (GuyTeichman/RNAlysis, 139 stars), Ensembl Database (davila7/claude-code-templates, 32k stars) and Bio DB Tools (DrugClaw/DrugClaw, 125 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Open Targets DB?

aipoch (a GitHub organization) maintains it in aipoch/medical-research-skills, which has 1,978 GitHub stars. The repository holds 578 skills in this directory. The repository was last updated on September 17, 2026.

Source: aipoch/medical-research-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.