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An AI skill is a reusable workflow for a recurring task. A prompt tells an AI what to do in a particular interaction; an agent can manage and carry out a task across multiple steps, often by using tools. They are different layers, not competing alternatives: a prompt can set the goal, a skill can supply the playbook, and an agent can execute it.
This is a practical distinction drawn from OpenAI’s descriptions, not a universal taxonomy shared by every AI product.
What is an AI skill?
An AI skill packages instructions for doing a particular kind of work repeatedly. It can help make a multi-step task, a required format, or a set of working rules easier to apply consistently. OpenAI Academy describes skills as reusable workflows and explains how to build them in its Using skills guide.
A skill is typically centered on a SKILL.md file. That file can describe the task, provide step-by-step guidance, specify required inputs and outputs, and set guardrails. The package may also include useful resources such as templates, examples, references, scripts, or other assets. The exact contents depend on the workflow.
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For example, a report-writing skill might specify which information to gather, the order in which to analyze it, the report sections and tone to use, and the final checks to perform. That is an illustrative example of the format, not a claim that a particular report skill has been tested.
How are AI skills different from prompts and agents?
The simplest distinction is what each one does: a prompt states the current request, a skill describes a repeatable process, and an agent runs a task that may involve planning and action across steps. The comparison below synthesizes OpenAI’s descriptions; it is not an exhaustive formal definition, and “prompt” can mean different things across products and research contexts.
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| Aspect | Prompt | Skill | Agent |
|---|---|---|---|
| Main role | Gives instructions or a request for the current task | Provides reusable instructions for a recurring kind of work | Manages and executes a task, potentially across multiple steps |
| Reuse | Often written for the current interaction, though it can be saved and reused | Designed for reuse, typically as a packaged workflow with metadata | The runtime or application can be used for different tasks |
| Autonomy | Does not by itself imply continuing execution | Guides how work should be done; does not itself imply independent execution | Can plan, choose available tools, act, and continue within its configured limits |
| Tools and resources | May mention tools, but the prompt alone does not provide access to them | May refer to supporting resources or tools; whether they are available depends on the host product | Often connects to tools or external systems |
| Best fit | A one-off request or instruction | Repeated work where process, format, or guardrails matter | Multi-step work that calls for decisions or tool-based actions |
OpenAI’s developer documentation describes agents in terms of planning and tool use. Its A practical guide to building agents states: “Agents are systems that independently accomplish tasks on your behalf.” In this context, an agent is the task runner; a skill is guidance it may use. A skill does not, by itself, create an agent, provide a runtime, or grant tool access.
What is a SKILL.md file?
SKILL.md is the instruction file at the center of a skill package. It can explain what the skill is for, how to carry out the workflow, what information it needs, what output to produce, and which constraints or checks to follow. The package can include additional files when the workflow needs them.
OpenAI’s Skills documentation describes staged discovery: a system may first see a skill’s name and description, then read its full instructions and supporting files when they are relevant. This progressive disclosure means detailed directions need not all be loaded before the skill applies. OpenAI’s September 11, 2026 developer blog, Rethinking skills and prompts for GPT-6 Astra, likewise discusses skills as Markdown prompts that can include resources and scripts, and emphasizes clear descriptions and progressive disclosure.
When should you use an AI skill instead of a prompt?
- Use a prompt when the job is a single request and you can explain it clearly without preserving a detailed process for future use.
- Create or use a skill when the work recurs and depends on the same steps, required inputs, output format, conventions, or checks. Start with a process you already perform often, then document its expected inputs, outputs, and guardrails.
- Use or build an agent when the system needs to manage a sequence of actions, make decisions as the work unfolds, or select tools and interact with external systems.
- Combine them when it helps: the prompt can state the current goal, the skill can supply a reusable playbook, and the agent can execute the multi-step work using tools it has been given.
OpenAI’s Agents documentation and its practical guide distinguish workflow execution by an agent from a single-turn language-model application. The combination above is a useful conceptual model, not a requirement imposed by every product.
Are skills and agents the same thing?
No. A skill describes a way to do work; an agent is a system that can manage and carry out work. They can be used together, but they are not interchangeable. Adding a skill does not automatically make software an agent, and an agent does not necessarily need a skill for every task.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Can you use the same AI skill in different products?
Not automatically. OpenAI says its skills are compatible with the open Agent Skills standard, which can support portability between tools that support the format. But format compatibility does not guarantee identical discovery, installation, available tools, or behavior in every product.
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OpenAI Academy’s Skills page describes downloading a skill from one product for installation in another supporting tool, while noting that OpenAI skills do not currently sync across products. Check the destination product’s support and setup requirements rather than assuming a skill will transfer unchanged.
What the evidence does—and does not—show
OpenAI’s published materials describe how skills and agents are structured and used; they are product guidance, technical documentation, and an implementation guide, not a statistical study. They do not establish a general adoption, productivity, or effectiveness figure for AI skills. Claims that a skill improves consistency are a description of its intended use, not a measured outcome here.
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