Molecular Targets Query

Community

QSong-github

molecular-targets-query

Query the NCI CCDI Molecular Targets Platform (pediatric oncology) for targets (genes), diseases, drugs, and target-disease associations via its public GraphQL API. Auto-detects entity type from input string.

Overview

Publisher	QSong-github
Repository	`DrugClaw`
Skill name	`molecular-targets-query`
Stars	118
Forks	3
Bundled files	4
Links	Skill source Repository Homepage

Markdown instructions
A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.
Works with any LLM
AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.
4 bundled files
Scripts, templates, and references the model can read while it works. Files are read-only and never executed.
Open source
Published by QSong-github on GitHub. Read the source before you install it.

Installation

Install the Molecular Targets Query AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/QSong-github/DrugClaw/tree/main/skills/dti/molecular_targets
Enable the skill in any chat where you want it available.

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills

git clone --depth 1 https://github.com/QSong-github/DrugClaw.git /tmp/DrugClaw
mkdir -p .claude/skills
cp -r /tmp/DrugClaw/skills/dti/molecular_targets .claude/skills/molecular-targets-query

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Molecular Targets Query in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Molecular Targets Query on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Molecular Targets Query is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

Loaded only when it is needed
The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.
Switch models mid-chat
Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Molecular Targets Platform Query Skill

Search the CCDI Molecular Targets Platform — an NCI-supported Open Targets instance focused on preclinical pediatric oncology data. Includes FDA Pediatric Molecular Target Lists and additional pediatric cancer datasets.

Entity Auto-Detection

Input Pattern	Detected As	Query Used
`ENSG00000141510`	Target (Ensembl gene)	`target(ensemblId)`
`EFO_\d+`, `MONDO_\d+`, `Orphanet_\d+`, `HP_\d+`, `DOID_\d+`	Disease / Phenotype	`disease(efoId)`
`CHEMBL\d+`	Drug / molecule	`drug(chemblId)`
anything else	Free text	`search(queryString)`

API

Function	Input	Returns
`search(entity, size=10)`	single entity string	`dict` (GraphQL data) or `None`
`search_batch(entities)`	list of strings	`dict[str, dict\|None]` — uses batch GraphQL where possible
`get_associations(entity, size=10)`	Ensembl ID or EFO/MONDO ID	associated diseases (for target) or targets (for disease)
`summarize(data, entity)`	result dict + label	compact LLM-readable text
`to_json(data)`	result dict	`list[dict]` for pipeline output

Helper

Function	Purpose
`detect_entity_type(entity)`	returns `'target'`, `'disease'`, `'drug'`, or `'search'`

Usage

See if __name__ == "__main__" block in 16_MolecularTargets.py for runnable examples covering:

Free-text search ("neuroblastoma")
Target lookup by Ensembl ID ("ENSG00000141510" → TP53)
Disease lookup by ontology ID ("MONDO_0005072")
Drug lookup by ChEMBL ID ("CHEMBL941" → imatinib)
Target → disease associations
Disease → target associations
Batch search (mixed entity types)
JSON pipeline output

Data Source

Platform: NCI CCDI Molecular Targets Platform
URL: https://moleculartargets.ccdi.cancer.gov
API endpoint: https://moleculartargets.ccdi.cancer.gov/api/v4/graphql
Method: HTTP POST, Content-Type: application/json, no auth required
Upstream schema: Open Targets Platform GraphQL v4
Focus: Pediatric oncology — FDA Pediatric Molecular Target Lists, preclinical data

Notes

The API is optimised for single-entity queries. For bulk analyses consider Open Targets data downloads.
Batch functions (search_batch) use the plural GraphQL fields (targets, diseases, drugs) to reduce round-trips where possible; free-text queries fall back to one-at-a-time.
get_associations() returns scored target↔disease links ranked by overall evidence score (0–1). Use size to control how many rows are returned.
Returns None / [] on HTTP errors — callers handle no-results gracefully.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Molecular Targets Query AI skill do?

Why use Molecular Targets Query on TypingMind?

Because you install it once and use it with any model. Molecular Targets Query is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Molecular Targets Query in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/QSong-github/DrugClaw/tree/main/skills/dti/molecular_targets. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Molecular Targets Query?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Molecular Targets Query?

As many as you like. As long as a model supports skills, you can use Molecular Targets Query with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Molecular Targets Query AI skill free?

It is published on GitHub by QSong-github. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Molecular Targets Platform Query Skill

Entity Auto-Detection

API

Helper

Usage

Data Source

Notes

Bundled files

Frequently asked questions

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