# 2025-10-16 Claude Skills are awesome, maybe a bigger deal than MCP

**Claude Skills are awesome, maybe a bigger deal than MCP**\
<https://simonwillison.net/2025/Oct/16/claude-skills>

Simon Willison’s article introduces **Claude Skills**, a new Anthropic feature that significantly enhances LLM capability by enabling specialized, modular task execution. Skills are **folders** containing a Markdown file with instructions, optional scripts, and resources that the model can load **only when relevant**, making them **token-efficient** and highly flexible.

Key points:

* **What Skills Are:**
  * Markdown-based instructions with optional YAML frontmatter.
  * May include scripts or resources to handle specialized tasks (e.g., Excel, PDFs, Slack GIFs).
  * Loaded only when needed, conserving token usage.
* **How They Work:**
  * Claude scans available skills on session start, reading short YAML summaries.
  * Full skill details are used only if a related task arises.
  * Require a coding environment with filesystem and script execution.
* **Comparison to MCP (Model Context Protocol):**
  * **MCP** is heavy, token-expensive, and protocol-driven.
  * **Skills** are lightweight, simple to create, and integrate seamlessly into coding agents.
  * MCP implementations often limit LLM performance due to context size.
* **Applications & Potential:**
  * Can create domain-specific “agents” (e.g., data journalism pipelines).
  * Easily shareable, simple to adapt, and not model-locked.
  * Expected to trigger a “Cambrian explosion” of community-made skills, overshadowing MCP adoption.
* **Security & Safety:**
  * Depends on sandboxed coding environments to prevent abuse and prompt injection risks.

#### Mermaid Diagram of Claude Skills vs MCP

{% @mermaid/diagram content="flowchart TD
A\[Claude LLM] --> B{Task Requested?}
B -->|General Task| C\[Baseline Claude]
B -->|Specialized Task| D\[Check Available Skills]
D --> E\[Load Relevant Skill]
E --> F\[Execute Skill Scripts/Instructions]
F --> G\[Task Completed Efficiently]

```
subgraph MCP Approach
    H[LLM] --> I[Load MCP]
    I --> J[Consume Large Token Context]
    J --> K[Perform Task]
end

G --> L[Less Token Usage]
K --> M[High Token Usage]

style A fill:#ffd700
style D fill:#90ee90
style H fill:#87ceeb" %}
```

This illustrates how **Skills offer a lightweight, modular, and token-efficient alternative** to MCP for enhancing LLM capabilities.


---

# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://docs.tuannvm.com/blog/reading/2025-10-16-claude-skills-are-awesome-maybe-a-bigger-deal-than-mcp.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.