A GPT-6 Astra skill is a reusable workflow package: a short description helps identify when it applies, while a SKILL.md file explains how to do the work. Optional examples, templates, scripts, or references can support the instructions. Use one when a task recurs and dependable steps, output conventions, or policy handling matter—not simply because a request is complicated.
How do GPT-6 Astra skills work?
OpenAI describes Agent Skills as modular instructions for codifying processes and conventions, from style guides to multi-step workflows. A skill is meant to be available for use when relevant, instead of requiring you to paste the same playbook into every conversation. Its description helps the model recognize the intended use; the workflow itself belongs in the instructions.
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The parts of a skill
- Description: States the kind of work the skill covers and the conditions that should trigger it.
SKILL.md: The playbook. It can specify required inputs, steps, output format, checks, and boundaries.- Supporting files: Optional examples, templates, references, scripts, or assets that the workflow needs.
The skill supplies procedure and context; it is not itself a guarantee that every instruction will run or that every action is available. In a plugin workflow, for example, the skill can explain how to combine tools, while an MCP server exposes the tools and controlled actions. See OpenAI’s API Skills guide and Plugins Skills documentation for those distinct contexts.
What should go in a SKILL.md file?
Write the actual procedure, not a long sales pitch for the skill. A useful file makes the workflow executable and bounded: what information it expects, what to do with it, what a successful result looks like, and what not to assume.
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- List the inputs the workflow needs and how to handle missing information.
- Give the steps in the order they should happen, including checks that catch common mistakes.
- Specify the required output format or conventions.
- State limits: facts the model must not infer, conditions for asking a question, and when to stop.
- Point to supporting resources only when they are useful, rather than copying large references into the main instructions.
Keep the description concise and use it to define the trigger; put detailed instructions in the body. OpenAI’s skill-building guidance recommends defining the workflow boundary and keeping a skill focused on a coherent process.
When should you use a skill?
A skill is worth creating or adopting when the same work comes up repeatedly and quality depends on following a consistent process. Examples include preparing a recurring report with required sections, applying a team style guide, or completing a multi-step task with a standard output. A shared playbook can reduce the need to restate those expectations and help different users follow the same conventions.
Use these questions to decide whether a skill fits. They are a practical framework, not an official OpenAI scoring system or threshold.
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| Question | A skill is a stronger fit when… |
|---|---|
| Repeatability | The task recurs often enough that recording the process saves repeated explanation. |
| Process dependence | A good result depends on multiple steps, a required format, or a policy. |
| Boundary clarity | You can state the expected inputs and outputs, plus when to ask or stop. |
| Surface and access | The product or environment where it will run supports that form of skill. |
| Instruction load | The workflow can be expressed without adding redundant or conflicting guidance. |
For a one-off request that is already clear, a skill may add little. It may also be a poor fit if the steps change substantially each time. Those are practical judgments about the value of reusable workflows, not product restrictions.
What is different about skills for GPT-6 Astra?
OpenAI’s September 11, 2026 guidance says skills, AGENTS.md files, and task prompts all shape how a coding agent works. It cautions that long descriptions and too many skills can cause descriptions to be shortened in context, while conflicting instructions can make selection harder. The useful response is to review accumulated instructions for bloat, ambiguity, and conflict—not to assume that adding more guidance always improves results. Read OpenAI’s GPT-6 Astra guidance.
Make the trigger and boundary explicit
Say plainly what situation should call for the skill, and what work is outside its scope. Keep the trigger in the description and the detailed workflow in SKILL.md. Prefer one focused skill for a coherent workflow to a broad package bundling unrelated tasks.
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Do skills work the same way in ChatGPT, Codex, the API, and plugins?
No. The underlying idea—reusable instructions with optional resources—can carry across environments, but the way a skill is provided, made available, or used depends on the product surface.
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- API: Skills may be supplied for local execution or made available in a hosted container-based environment. The API documentation describes a skill directory containing a
SKILL.mdmanifest and supporting files. - Plugins: A skill can provide repeatable instructions for combining plugin tools; the MCP server provides the tools and controlled actions.
- Codex: Skills sit alongside files such as
AGENTS.mdand task prompts as sources of instructions. Check the relevant Codex environment’s own availability and setup rather than assuming ChatGPT installation steps apply.
OpenAI’s ChatGPT Skills help article describes automatic use after creation and installation, but that does not mean a skill is enabled for every account or guaranteed to run for every request. Plan eligibility, workspace settings, syncing, and product surface can affect availability.
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