GPT-6 Astra skills are reusable workflow packages: a SKILL.md file explains when and how to perform a recurring task, while optional files can supply templates, examples, scripts, or reference material. Use a skill when reliable results depend on repeating steps, following a format, or applying a policy—not just because a task involves AI. How a skill is installed and made available depends on whether you use ChatGPT, Codex, the API, or a plugin.
How do GPT-6 Astra skills work?
A skill records a workflow so an AI can apply it when relevant instead of requiring you to paste the same instructions into every conversation. OpenAI describes Agent Skills as modular instructions for codifying processes and conventions, from company style guides to multi-step workflows. See the OpenAI API Skills guide and OpenAI Academy’s introduction to using skills.
A typical skill has a name and a short description that help identify its purpose and when it should be considered. Its SKILL.md file contains the workflow itself. More involved skills can include supporting files in the skill directory, such as a template to fill in, examples to follow, reference material, or scripts. The exact packaging and execution depend on the product surface.
What goes in a SKILL.md file?
Write the file as a usable playbook, not a general description of a topic. State what task the skill handles and provide the operational details needed to complete it. A well-bounded workflow can specify:
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- What inputs the user or agent should provide.
- The steps to follow and any decisions to make along the way.
- The required output format and checks for a finished result.
- What the model must not assume or infer.
- When to ask a question, stop, or hand off the task.
- Which supporting files to consult, when applicable.
Keep the trigger—the circumstances in which the skill is useful—in its description. Put the detailed procedure in the body, and link to supporting resources as needed. OpenAI’s plugin skills guidance also explains how a skill can make a repeatable workflow for combining tools from an MCP server; the server provides the tools and controlled actions, while the skill supplies the procedure and context.
When should you use a skill?
A skill is a good fit when a task recurs and its quality depends on a dependable process, consistent deliverable, or shared policy. Examples include preparing a particular report from recurring inputs, applying a team’s style rules, or following the same multi-step review each time. A skill can make those conventions reusable across relevant tasks and easier for a team to share.
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Use these questions to decide whether it is worth creating or adopting one:
- Repeatability: Does this task come up often enough that recording the workflow would save repeated explanation?
- Process dependence: Does a good result require several steps, a specific format, or consistent policy handling?
- Clear boundaries: Can you describe the expected inputs and outputs, along with when to ask, stop, or avoid making assumptions?
- Access: Does the product surface and account or workspace configuration support the way you intend to use the skill?
- Instruction load: Can the skill stay focused, without duplicating or conflicting with other instructions?
This is a practical decision framework, not an OpenAI scoring system or a formal minimum threshold. A one-off request that is already clear may not benefit from a saved workflow; nor may a task whose steps change substantially every time.
How should you design skills for GPT-6 Astra?
GPT-6 Astra follows more than one source of instructions: skills, AGENTS.md files, and task prompts all shape how a coding agent works. In guidance published September 11, 2026, OpenAI warns that long descriptions and too many skills can cause descriptions to be shortened in context, while conflicting instructions can make skill selection harder. Review accumulated instructions for bloat, ambiguity, duplication, and conflicts. Keep the skill description concise, state its trigger clearly, and define a focused workflow boundary. Read OpenAI’s GPT-6 Astra guidance on skills and prompts.
A focused skill should handle a coherent workflow rather than bundle unrelated tasks. Make clear what it expects, what it produces, which facts it must not infer, and what to do when an input is missing or a situation falls outside its scope. This makes it easier to tell when the skill applies and reduces the chance that its instructions pull a different task off course.
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Do skills work the same way in ChatGPT, Codex, the API, and plugins?
No single installation or invocation method should be assumed across these surfaces. The underlying idea—a reusable workflow with instructions and possibly supporting files—can be similar, but availability, packaging, and execution differ.
| Surface | What to expect |
|---|---|
| ChatGPT | Eligible users can create, install, and share skills through supported interfaces. ChatGPT may automatically use one or more installed skills when helpful, but availability depends on account eligibility, workspace settings, and product surface. See the ChatGPT Skills Help Center article. |
| Codex | Skills, AGENTS.md files, and task prompts can all shape agent behavior. Check the relevant environment’s instructions and skill availability rather than assuming that a skill installed elsewhere is present. |
| OpenAI API | The API documentation describes skills provided for local execution or made available in a hosted, container-based environment, using a directory that can include a SKILL.md manifest and supporting files. Consult the API Skills guide for the applicable setup. |
| Plugins | A skill can describe how ChatGPT or Codex should combine tools exposed by an MCP server in a repeatable workflow. The skill provides instructions; the server exposes the tools and controlled actions. See the plugin skills documentation. |
Because eligibility, workspace configuration, and product interfaces can change, check the documentation for the specific surface you use. Installing a skill does not mean it is enabled for every account or guaranteed to run in every conversation.
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