Claude Skills: The AI Feature That Actually Solves a Real Problem

Yesterday, Anthropic quietly released what might be the most practical AI feature of 2025. It’s not flashier models or better benchmarks. It’s something simpler: a way to teach Claude your specific workflows without writing a single line of code.

They call it Skills. And this might be a bigger deal than the Model Context Protocol that had everyone buzzing last year.

What Are Skills, Really?

Skills are remarkably straightforward: folders containing instructions, scripts, and resources that Claude loads when it recognizes a relevant task. Think of them as custom training manuals. You’re building a financial model? Claude grabs your Excel expertise. Creating a presentation? Your brand guidelines and templates load automatically. Writing code? Your team’s coding standards kick in. The elegant part? You’re not micromanaging any of this. Claude scans available skills, identifies what’s relevant, and pulls in exactly what it needs. Nothing more.

Here’s what makes them different:

Composable: Skills stack together without you coordinating them. Portable: Build once, use everywhere. The same skill works in Claude’s web interface, API, and Claude Code. Efficient: Each skill only consumes a few dozen tokens until Claude needs it. Then it loads the full details. Powerful: Skills can include executable Python scripts for tasks where traditional code beats token generation.

Claude Skills. Source: Anthropic

Under the Hood: How Skills Actually Work

The technical implementation reveals why Skills matter. At the start of a session, Claude scans all available skill files and reads a short explanation from the YAML in each Markdown file. This is remarkably token-efficient — each skill takes up maybe 30–50 tokens until needed.

When you request something like “create a sales presentation following our brand guidelines,” Claude recognizes two relevant skills: presentation creation and your brand standards. It loads both, coordinates their use, and gets to work.

Those document creation abilities Claude launched in September? Turns out they were Skills all along.

A Real Example: The PPT Creation

In this example I use the theme-factory. This is a: toolkit for styling artifacts with a theme. These artifacts can be slides, docs, reportings, HTML landing pages, etc. There are 10 pre-set themes with colors/fonts that you can apply to any artifact

I believe that this one is very useful. I can see that you could create power points templates that are used in your company and create quickly the presnetations following the right format. All you need to do is to upload excel file with the data and the rest is done by Claude. You can have multiple formats saved and use them whenever needed.

2nd Example: Canvas-Design Skill

The canvas-desing is use to “create beautiful visual art in .png and .pdf documents using design philosophy. You should use this skill when the user asks to create a poster, piece of art, design, or other static piece.”

The Coding Environment Requirement

Skills depend entirely on Claude having access to a filesystem and the ability to execute code. This isn’t new — ChatGPT’s Code Interpreter pioneered this pattern back in early 2023, and local tools like Cursor and Claude Code extended it to your machine.

But this requirement is what separates Skills from previous attempts to expand LLM capabilities, like MCP or ChatGPT Plugins.

The trade-off is clear: you need secure sandboxing to limit damage from potential prompt injection attacks. But once you have that environment, the possibilities expand dramatically.

Claude as a General Agent (Not Just a Coding Tool)

Here’s where things get interesting. Claude Code is misleadingly named. It’s not purely for coding. It’s a tool for general computer automation. Anything you can accomplish by typing commands into a terminal is something Claude Code can now automate.

Skills vs. MCP: A Better Approach?

The Model Context Protocol launched last November to enormous buzz. Every company building an “AI strategy” rushed to announce MCP implementations.

But limitations emerged. GitHub’s official MCP alone consumes tens of thousands of tokens. Add a few more MCPs and there’s barely any context left for actual work.

Skills have the same advantage, but better. You don’t even need to implement a CLI tool. Drop in a Markdown file describing how to do the task. Add scripts only if they make things more reliable or efficient. The token efficiency is stark. MCPs front-load thousands of tokens describing every possible capability. Skills load a 30-token description and only pull the full details when needed.

Building Your First Skill

Creating skills is straightforward. Anthropic even built a “skill-creator” skill that interviews you about your workflow and generates the folder structure for you. The basic structure:

my-skill/ ├── SKILL.md # Main instructions ├── core/ # Helper scripts (optional) │ └── utilities.py └── examples/ # Sample files (optional) └── template.json

The SKILL.md file contains frontmatter with a brief description, followed by detailed instructions for Claude:

— -  name: brand-guidelines description: Company brand standards for presentations and documents  — -

Brand Guidelines Skill

When creating presentations or documents, follow these standards:

1. Colors - Primary: #0066CC - Secondary: #FF6B35 - Background: #F8F9FA

1. Typography - Headings: Montserrat Bold - Body: Open Sans Regular

1. Logo Usage Load the logo from `/examples/logo.svg`. Always position in top-right…

That’s it. No API integrations. No authentication flows. Just instructions.

Real-World Applications

For Teams:

Onboarding documentation that Claude references automatically
Code review standards that apply when examining pull requests
Brand guidelines that enforce consistency across all documents

For Developers:

API integration patterns specific to your stack
Testing strategies that match your team’s approach
Deployment procedures that follow your exact workflow

For Analysts:

Data cleaning procedures for common sources
Visualization standards and templates
Report structures that match stakeholder expectations

For Content Creators:

SEO optimization guidelines
Publishing workflows for different platforms
Brand voice and tone standards

What Comes Next The barrier to creating and sharing skills is so low that we’ll likely see:

Industry-specific skill libraries (legal, medical, financial)
Company-wide skill repositories that standardize operations
Community-contributed skills for common tools and frameworks
Educational skills that teach domain expertise

The most interesting aspect? Nothing prevents these skills from working with other models. You can use a Claude skill folder with Codex CLI or Gemini CLI today. Read the SKILL.md file and go. This isn’t vendor lock-in. It’s a shared format that could become a standard.

The Bottom Line

Skills represent a shift from “prompt engineering” to “expertise packaging.” You’re not trying to phrase your request perfectly. You’re teaching the assistant your domain once, and it remembers.

The implications extend beyond individual productivity. Organizations can codify institutional knowledge. Teams can standardize approaches without rigid processes. Specialists can share expertise at scale. And unlike most AI features announced with fanfare and forgotten by next quarter, Skills solve an actual problem: the gap between what AI can theoretically do and what it practically understands about your specific work.

That’s worth paying attention to.

Read the full article here: https://medium.com/@meshuggah22/claude-skills-the-ai-feature-that-actually-solves-a-real-problem-c149b54b0846