I just tested Claude Skills, and it’s awesome. Anthropic is on a roll here with disruptive innovation. If you haven’t tried it yet, here’s a quick rundown of why it matters, and why it could reshape how we work with AI assistants.

What Claude Skills are

Skills are like snap-on capabilities for Claude. Instead of rewriting prompts or uploading instructions every time, you can package reusable logic, scripts, and guidelines into a small folder. Claude automatically detects when a skill is relevant and loads it as needed.

You could build a “content brief” skill that enforces your tone, structure, and formatting. Or a “status-report” skill that summarizes updates the same way every week. It’s lightweight, modular, and instantly reusable across chats and teams.

The brilliance is in the simplicity: Claude now behaves less like a memory-loss chatbot and more like a real system that remembers how your team works.

How it differs from MCP

The Model Context Protocol (MCP) enables Claude to connect to external tools and data sources, such as your CRM, documents, or APIs. It’s a connectivity layer.

Skills, by contrast, define what to do once that data is available. They’re workflow logic, not integrations. MCP gives Claude access; Skills give Claude purpose.

In practice, they complement each other: MCP fetches data, Skills tell Claude how to process and present it.

Seeing it through a product manager’s lens

As a product manager, I see Skills as a new layer of knowledge infrastructure. You can encode how your team thinks (tone, workflow, review criteria) directly into the assistant. It’s like turning your company’s playbook into callable micro-apps.

For many teams, that’s a bigger unlock than simple data connectivity. It moves AI from “help me write this” to “run this process the way we do it.” That’s the kind of leverage PMs and operations teams have been chasing for years.

Why some say it’s a bigger deal than MCP

Maybe it’s because Skills feel immediately useful. You don’t need engineering support or API keys to get value. Anyone can create a folder, drop in a Markdown file with clear instructions, and watch Claude follow it perfectly.

MCP, on the other hand, is powerful but technical. It shines when you want deep integrations, but most people start with workflows, not systems integration. Skills meet users where they already are.

One important thing I picked up: Skills are much more efficient. They only keep a smaller set of metadata about the skills in the context window and invoke the appropriate skill on demand.

Closing thought

Anthropic is quietly redefining how assistants evolve. From reactive tools to configurable, modular workers. Whether Skills outshine MCP in the long run doesn’t matter much right now. What matters is that we’re watching AI systems become more adaptable and more personal.

It’s exciting to be living in this era.