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AI agent skills: reusable workflows that do one job well

A useful skill is more than a long prompt. It should define the task, expected inputs, allowed tools, output shape, quality checks, and what the agent should do when information is missing.

Last reviewed: 2026-09-18

Start here

Use these as a shortlist, then verify current limits, permissions, and pricing on the provider site.

What belongs inside a skill

Package the repeatable parts of a task so the agent does not need to rediscover your preferred process every time.

  • Goal, inputs, assumptions, and constraints.
  • Tools or data sources the workflow is allowed to use.
  • Ordered steps and decision points.
  • Output format, examples, and validation checks.
  • Fallback behavior when evidence or permissions are missing.

Start narrow, then compose

A small reliable skill such as 'review a pull request for migration risk' is easier to test than a broad 'be my senior engineer' prompt. Compose several narrow skills into a larger workflow after each one is dependable.

Version skills like code

Store the instructions, examples, and acceptance criteria in version control or another reviewable system. When an output regresses, you need to know what changed.

Frequently asked questions

Is an AI agent skill just a prompt?+

A prompt can be part of a skill, but a reusable skill usually also defines inputs, tools, ordered steps, output format, validation, and fallback behavior.

How small should an agent skill be?+

Small enough to test with repeatable examples. Narrow skills are easier to debug, review, reuse, and combine into larger workflows.

How do I know an agent skill is reliable?+

Run it against representative tasks, define acceptance checks, review failures, and version changes so regressions are visible.