Claude Skills vs Custom GPTs: differences and which one to choose

Short answer: choose a custom GPT when you want an experience inside ChatGPT that a non-technical team can configure, share and use quickly. Choose a Claude Skill when the main asset is a reusable procedure made of instructions, resources and, when necessary, scripts.

Do not choose based on a supposed universal privacy or capability advantage. A Skill does not keep data local merely because it uses files, and a GPT is not automatically unsuitable for business. The plan, connectors, actions, permissions and data matter more than the label.

What is a Claude Skill?

A Skill is a folder of instructions, scripts and resources that Claude loads when it decides they are relevant. Anthropic calls this progressive disclosure: Claude sees the description first and loads the detail needed for the task instead of putting every Skill into context.

Skills can apply brand guidance, create documents with a specific structure, analyse data through a defined procedure or execute a technical workflow. Anthropic makes Skills available in Claude, in Claude Code—currently beta according to its documentation—and through the API with the code-execution tool.

The format is published as the open Agent Skills standard. That improves instruction portability, but it does not guarantee that scripts or integrations behave identically in every runtime.

What is a custom GPT?

A GPT is a version of ChatGPT configured for a particular purpose. It can combine instructions, knowledge files and selected capabilities. It can also use apps or Actions to call external APIs; an Action requires authentication and an OpenAPI schema.

GPTs are created and edited inside ChatGPT. They can stay private, be shared with people or a workspace, be published by link or reach the GPT Store when the plan, workspace configuration and policies allow it.

OpenAI also defines an important boundary: a GPT is designed to be used inside ChatGPT. If you need to embed an assistant in a website or product, build it with the API.

Quick comparison

The key distinction: procedure or experience

A Skill captures how to perform a task. It can specify sources, order, validations and output format. It works particularly well when operational knowledge belongs next to files, scripts or a repository.

A GPT configures a specialised experience inside ChatGPT. It is convenient when a user needs to open it, ask a question, attach material and get a response without maintaining an automation folder.

The same need can be solved both ways. A proposal reviewer could be a GPT for a sales team or a Skill in the repository where proposals are generated. The decision depends on where the real user already works.

Privacy: claims to avoid

It is incorrect to say a Claude Skill automatically keeps data on the device. When Claude runs in the cloud, the conversation and required content are processed under the relevant Anthropic product and plan. A script may execute local work, but that does not make the whole workflow local.

It is also incorrect to treat every GPT as if it had the same data policy. OpenAI says Business, Enterprise and Edu data is not used for model training by default. Consumer-plan use depends on data controls. If a GPT calls an external app or API, relevant input may be sent to that third party.

Before either option handles personal or confidential data, document:

1. Which data enters and what can be removed.
2. Which product, plan and region process it.
3. Which connectors, Actions, scripts or third parties receive information.
4. Who can publish, modify and use the assistant.
5. Which logs, retention and deletion mechanisms exist.

For legal, health, financial or customer data, also read our guide to using AI without compromising sensitive information.

When to choose a custom GPT

A GPT is usually a better fit when:

• The team already works inside ChatGPT.
• The task is mostly conversational: reviewing, summarising, classifying or drafting.
• Non-technical people need to configure and test it.
• You want to share it in a workspace or publish it when eligible.
• An integration can be exposed through a controlled API.
• The asset does not need to deploy as part of a software repository.

Example: an internal assistant that reviews text against the brand guide, asks for the publication channel and returns observations before a person approves the piece.

When to choose a Claude Skill

A Skill is usually a better fit when:

• The value lies in a multi-step procedure and its validations.
• The procedure needs templates, references or scripts.
• The team wants to review changes through Git.
• Claude should load the procedure automatically when it recognises the task.
• The organisation wants to distribute a common way of working.
• The workflow sits close to code, documents or technical tools.

Example: a Skill that prepares a delivery, runs permitted checks, gathers results and produces a report. Credentials and destructive actions must remain controlled outside the instructions.

Maintenance and governance

The real cost is not only the subscription. It includes maintaining instructions, sources, permissions, evaluations and ownership.

For a GPT:

• Define an owner and reviewers.
• Restrict publishing and Action domains in the workspace.
• Keep a controlled copy of instructions and tests outside the editor.
• Repeat tests when models, files or integrations change.

For a Skill:

• Version instructions and scripts.
• Declare dependencies and permissions.
• Separate public, internal and secret information.
• Test correct activation and cases where it must not run.

For both, maintain a small set of expected examples and critical failures. A specialised assistant without evaluation eventually accumulates contradictory instructions.

Cost

Creating or editing GPTs requires a compatible paid plan; user access, publication and controls vary by plan and workspace. Skills are available across several Claude plans, while some uses require code execution to be enabled. Always consult official pricing before budgeting a deployment because plans change.

For a business comparison, add:

• Model licences or usage.
• Integration development and maintenance.
• Evaluation and human review.
• Infrastructure and storage.
• Migration cost when the process becomes platform-dependent.

Can they be combined?

Yes. A company can use GPTs for accessible conversational experiences and Skills for versioned procedures. Both can connect to a governed tool layer when the product allows it.

The Model Context Protocol helps standardise tool connections, but it does not make migration automatic: authentication, permissions, interfaces and model behaviour still require testing. Read more in our guide to MCP servers and company data.

Final recommendation

Do not start with “Claude or OpenAI?” Start with four questions:

1. Who runs the process and where do they work today?
2. Is the value in a conversation or a reproducible procedure?
3. Which data and actions are involved?
4. How will you test whether the result is correct?

If the answers point to an experience inside ChatGPT, pilot a custom GPT. If they point to reusable instructions, resources and scripts, pilot a Skill. If the process crosses several systems or sensitive decisions, you may need a custom automation or agent instead of forcing either format.

Navel Digital can map the workflow and build a measurable pilot without assuming which platform should win.

Official sources reviewed

• Anthropic: what are Skills
• Anthropic: use Skills in Claude
• OpenAI: GPTs in ChatGPT
• OpenAI: configuring Actions in GPTs
• OpenAI: ChatGPT Business pricing