Nathaniel Whittemore

Cloud agents can then draw from these skills when they become relevant to the task at hand.

Essentially, skills are little barrels or buckets of context that Claude can draw on when it makes sense.

They're in a standard format that can be used across Claude apps, Claude code and the API, meaning you only have to build them once.

Said anthropic staffer Mahesh Murag, skills are based on our belief and vision that as model intelligence continues to improve, we'll continue moving towards general purpose agents that often have access to their own file system and computing environment.

The agent is initially made aware only of the names and descriptions of each available skill and can choose to load more information about a particular skill when relevant to the task at hand.

Now, part of the benefit here is that this makes the method token efficient.

Cloud agents can initially use very basic tools to figure out which skills they need for a given task and only spend significant tokens once it knows which ones to load.

They also function sort of like custom agentic scaffolding, but in a much more modular and user-friendly package.

A user doesn't need to know any programming language to create a custom skill that's fit for their purpose, which of course dramatically lowers the barrier to entry for advanced agent design.

You can also prompt Claude to design its own skills with the example that they give, saying, help me create an image editor skill.

Claude can also help them refine human design skills or monitor common failure points and then build skills to mitigate them.

Basically, Claude can be leveraged to collaborate on its own agentic design.

skills are also stackable.

So by way of example, Anthropic discussed an agentic workflow for building a quarterly investor deck where the agent would be able to tap into the company's brand guideline skill, a financial reporting skill, and a presentation formatting skill, coordinating all three without the need for manual intervention.

People very quickly picked up that this is sneakily a big deal.

Daniel Meisler wrote, Something I want to stress today.

MCP changed everything, but not because of a model improvement.

And today, skills change everything, but not because of a model improvement.

AI systems are the thing to watch, not just the intelligence of the models.

People are useful in jobs because they connect dots and can do many different things.