Skills vs Agents in Claude Code: The Difference Explained Simply

If you're exploring Claude Code, you'll quickly run into two concepts: Skills and Agents.

Most people mix them up. Here's the simplest way I can explain it.

First: understand the jar

Every conversation with Claude has a limited memory. Think of it as a jar.

Everything goes into that jar: your instructions, your questions, Claude's answers, the data it reads, the tools it uses. All of it.

When the jar fills up, Claude starts summarizing older stuff to make room. That means it slowly forgets what you talked about earlier.

This is why structure matters. And it's the key difference between skills and agents.

Skills = a recipe (same jar)

A skill is a single, focused task. You tell Claude exactly what to do, step by step.

Type /search-term-analysis and Claude follows the steps. Pull the data, clean it, analyze it, give you the output.

Like a recipe. Specific steps, specific result. Done.

The important thing: a skill runs inside your conversation. It uses the same jar.

That means it fills up your jar faster. But the upside is huge: you can ask follow-up questions because everything stays in the same conversation. Claude remembers what the skill just did.

"Show me only the irrelevant terms." "Now create negative keyword lists from those." "Which ad groups are most affected?"

All of that works because the skill output is right there in the jar with you.

Agents = helpers (own jar)

An agent is different. Claude Code spins up a small helper focused on a specific task — and that helper gets its own jar. A completely separate one.

Think of it like delegating to a colleague. You say "go analyze this data" and they go off, do the work in their own space, and come back with a summary.

When the agent is done, it sends a short summary back into your main jar. Your main conversation stays clean.

This is why agents are better for heavy analysis. They can read thousands of lines of data, run complex logic, and crunch numbers — all without filling up your conversation.

Real example from my PPC setup

I have a skill called /gads-context. It pulls campaign data from Google Ads into your conversation. Specific steps, specific result. You can immediately ask follow-up questions about the data because it's right there in your jar.

Then I have /qs-analyze. This is an agent. It reads all your keyword data, diagnoses which Quality Score component is broken (ad relevance, expected CTR, or landing page experience), and decides what to fix first.

That's a lot of data and a lot of thinking. If all of that happened in your main jar, you'd run out of space fast. Your conversation would degrade before you got to the useful part.

So it runs in its own jar. Comes back with just the diagnosis and the recommended next step. Your main conversation stays sharp.

When to use which

Use a skill when:

• The task is focused and sequential
• You want to ask follow-up questions about the output
• The data volume is manageable (won't fill your jar)
• You need the output to inform your next prompt

Use an agent when:

• The task involves large amounts of data
• The analysis is complex and multi-step
• You only need the conclusion, not the raw work
• You want to keep your main conversation clean

The simple rule

Skill pulls data. Agent does the heavy analysis. Your jar stays clean.

Start with skills. They're easier to understand and build. Once you hit the limits of your jar — Claude starts forgetting things mid-conversation, or your analysis gets cut short — you'll instantly understand why agents exist.

That moment when Claude summarizes away your data mid-analysis? That's when you rebuild it as an agent.