Neo4j Graph Data Scientist

Organization

neo4j-contrib

neo4j-graph-data-scientist

Use for graph realted tasks on Neo4j via GDS Agent and Cypher tools. Covers the workflow and a troubleshooting guide for errors.

Overview

Publisher	neo4j-contrib
Repository	`gds-agent`
Skill name	`neo4j-graph-data-scientist`
Stars	99
Forks	22
Bundled files	1
License	MIT
Links	Skill source Repository

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.
1 bundled files
Scripts, templates, and references the model can read while it works. Files are read-only and never executed.
Open source
Published by neo4j-contrib on GitHub. Read the source before you install it.

Installation

Install the Neo4j Graph Data Scientist 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/neo4j-contrib/gds-agent/tree/main/skills/neo4j-graph-data-scientist
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/neo4j-contrib/gds-agent.git /tmp/gds-agent
mkdir -p .claude/skills
cp -r /tmp/gds-agent/skills/neo4j-graph-data-scientist .claude/skills/neo4j-graph-data-scientist

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

Use it in TypingMind

Enable Neo4j Graph Data Scientist 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 Neo4j Graph Data Scientist 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 Neo4j Graph Data Scientist 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.

Workflow

Inspect the database schema first. Never guess labels, types, or property names.
Project a graph. Plugin and session mode have different projection syntax and parameters. Check the graph projection tool description and parameters. For session mode, you need to first create sessions to project graphs onto.
Clean up. drop_graph when a projection is no longer needed. delete_session when a session is no longer needed, and this will automatically drop all graphs projected to this session.
When you see errors, inspect the message and consult references/troubleshooting.md. Then make necessary corrections.
Independently verify key results. Verify the key results using a genuinely different method if the problem allows. If the two methods disagree, investigate the discrepancy and resolve it first if it can be resolved. Otherwise, say so explicitly in the answer. This step is not satisfied by sanity checking the logic mentally.

Best Practices

Large graphs. When the graph in the DB is large, you might want to consider projecting subgraphs at the start for analysis.
Long running tools. Certain algorithms (or Cypher queries) are long running. For exploratory work, consider trying them out on smaller projected graphs before executing them on a desirable large projected graph.
Follow general data science best practice. Understand if the task is transductive (over the fixed data) or inductive. For predictive tasks, ensure there is no data leakage. Formulate hypothesis and design metrics appropriately. Remember all the basic statistics best practices.
Perform additional analysis when needed. You do not need to use solely the Cypher and GDS tools. For complex data science task, feel free to use other tools or coding capabilities and write ad-hoc scripts that use other libraries, such as pytorch, scikit-learn, pandas, matplotlib, when necessary.

Bundled files

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

references/troubleshooting.md2 KB

Frequently asked questions

What does the Neo4j Graph Data Scientist AI skill do?

Use for graph realted tasks on Neo4j via GDS Agent and Cypher tools. Covers the workflow and a troubleshooting guide for errors.

Why use Neo4j Graph Data Scientist on TypingMind?

Because you install it once and use it with any model. Neo4j Graph Data Scientist 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 Neo4j Graph Data Scientist in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/neo4j-contrib/gds-agent/tree/main/skills/neo4j-graph-data-scientist. 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 Neo4j Graph Data Scientist?

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 Neo4j Graph Data Scientist?

As many as you like. As long as a model supports skills, you can use Neo4j Graph Data Scientist with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Neo4j Graph Data Scientist AI skill free?

Yes. It is published on GitHub by neo4j-contrib under the MIT license. 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

Workflow

Best Practices

Bundled files

Frequently asked questions

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