What AI Agent Skills Are and How They Work
Description
Watch: full video.This IBM Technology explainer introduces Agent Skills as a way to give AI agents procedural knowledge: not just facts to retrieve, but repeatable instructions for how to perform work. The useful distinction is that RAG supplies reference knowledge, MCP supplies tool access, and skills package workflows, rules, scripts, and examples the agent can load when needed. For knowledge workers, the practical point is that more reliable agents depend on reusable operating know-how, not prompts alone.
Official video embed
Martin Keen / IBM Technology, YouTube · 2026-04-20
Martin Keen / IBM Technology, YouTube · 2026-04-20
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Open original sourceKey Takeaways
- AI agent skills are best understood as procedural knowledge: they teach an agent how to perform a task, not merely what facts to use.
- A skill file turns a workflow into reusable instructions, usually with a name, description, body instructions, and optional scripts or reference materials.
- The practical distinction is that MCP connects an agent to external tools, RAG supplies relevant information, and skills guide the agent through the steps of doing the work.
- The trust issue is control: once skills can run tools or scripts, they need clear boundaries, testing, and review so automation does not become invisible or unsafe.