# How Claude Solved AI's Biggest Problem

Source: https://www.youtube.com/watch?v=Z9glbip8pZc
Recap page: https://rapidrecap.app/video/Z9glbip8pZc
Generated: 2025-11-12T01:19:09.729+00:00

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## Quick Overview

Claude Skills solve AI's biggest problem of limited context window by dynamically loading necessary instructions, scripts, and resources only when relevant, allowing the model to handle complex tasks like building custom tools (like the Figma MCP server or an SEO skill) without exhausting context on unnecessary data, offering a significant advantage over traditional Model Context Protocols (MCP) that expose all tool definitions simultaneously.

**Key Points:**
- Claude Skills overcome context window limitations by only loading skill documentation and resources when they are relevant to the current task, unlike MCPs which expose all tool definitions at once (2:49).
- The custom PDF Extractor skill demonstrated the capability to extract text and tables from PDFs, which was necessary for building the Figma MCP server (0:26).
- The developer used the Skill Creator skill to build a new SEO optimization skill, which involved researching requirements and generating necessary files (7:28).
- The demonstration showed that Claude Skills can execute complex, multi-step projects, such as creating a production-ready Figma MCP server using external documentation retrieved via web search (2:04).
- Skills are stored locally within the project structure in a .claude/skills folder, and the model automatically recognizes them, including the skill-creator skill used to build others (0:43, 7:25).
- A key limitation of Skills is that they run in a restricted environment with no network access or runtime package installation, meaning external API calls or internet access are blocked (5:59).

![Screenshot at 2:49: Comparison diagram illustrating that Claude Skills selectively load only the name and description of required skills \(Skill 1, Skill 2\) into the context window, whereas MCP exposes all tool definitions \(MCP1, MCP2\) simultaneously, consuming more context.](https://ss.rapidrecap.app/screens/Z9glbip8pZc/00-02-49.png)

**Context:** This video explains Anthropic's solution to the context window constraints faced by large language models (LLMs) when dealing with numerous external tools or complex knowledge domains, a problem often addressed by Model Context Protocols (MCPs). The video introduces 'Claude Skills' as Anthropic's method for providing AI models with specialized, on-demand capabilities, contrasting this selective loading approach against the static nature of traditional MCP tool exposure.

## Detailed Analysis

The video argues that Claude Skills solve a major AI limitation: managing the context window effectively when many tools are available. Unlike MCPs, which load all tool definitions into the context window upfront (2:49), Claude Skills only load the necessary instructions, scripts, and resources when they are relevant to the user's prompt. This selective loading preserves context for crucial conversation history and complex reasoning. The presenter demonstrated this by first showing the structure of a custom PDF Extractor skill (0:57) and then using the Skill Creator skill to build a new SEO optimization skill (7:28). A major demonstration involved creating a comprehensive Figma MCP server, requiring Claude to use web search tools to find necessary Figma API documentation and then utilize the MCP builder skill to construct the server files, showing the model's ability to execute complex, multi-tool workflows (2:04). Crucially, the video highlights the runtime constraints for Skills: they cannot access the network or install new packages, meaning they are fully contained and rely only on pre-configured dependencies (5:59). The overall benefit is that Skills allow for specialized, repeatable tasks without bloating the context window unnecessarily, making the AI more efficient for complex, domain-specific work.

### Claude Skills vs. MCP

- Skills selectively load only name/description into context window, unlike MCPs which expose all tool definitions
- Skills are stored locally in .claude/skills folder
- MCP exposes all tool descriptions directly to the model (2:49, 4:46)

### Skill Creation Demonstration

- Skill Creator skill was used to build a new SEO skill after researching requirements for a React/Vite website
- The model created an SEO skill covering meta tags, structured data, performance, accessibility, and sitemap generation (7:33)

### Advanced Skill Execution

- The process included using the PDF Extractor skill to process brand guidelines, the MCP Builder skill to set up a Figma MCP server, and the Design Enhancer skill to improve a fashion website's design score from 86.3/100 to 94/100 (2:04, 7:55)

### Skill Limitations

- Skills run in a restricted code execution container
- Key limitations include no network access (no external API calls/internet) and no runtime package installation; only pre-configured dependencies are available (5:59)

![Screenshot at 0:00: Initial view of the terminal showing MCP tools and memory files, setting the context for agent workflows.](https://ss.rapidrecap.app/screens/Z9glbip8pZc/00-00-00.png)
![Screenshot at 0:04: Anthropic blog post highlighting the introduction of Agent Skills.](https://ss.rapidrecap.app/screens/Z9glbip8pZc/00-00-04.png)
![Screenshot at 0:26: Detail of the PDF Extractor skill structure, showing references, scripts, and the main SKILL.md file.](https://ss.rapidrecap.app/screens/Z9glbip8pZc/00-00-26.png)
![Screenshot at 2:49: Diagram comparing MCP context window \(all tools exposed\) versus Claude Skills context window \(only necessary skill descriptions loaded\), illustrating context efficiency.](https://ss.rapidrecap.app/screens/Z9glbip8pZc/00-02-49.png)
![Screenshot at 4:05: ScaleKit dashboard showcasing multi-tenant architecture and org-first approach to enterprise identity management.](https://ss.rapidrecap.app/screens/Z9glbip8pZc/00-04-05.png)
![Screenshot at 6:25: Terminal output showing the successful setup of a Figma MCP server with two configuration options \(Desktop Server vs. Remote Server\).](https://ss.rapidrecap.app/screens/Z9glbip8pZc/00-06-25.png)
![Screenshot at 7:33: The newly created SEO optimization skill's capabilities listed, including meta tags, structured data, performance, and accessibility optimization.](https://ss.rapidrecap.app/screens/Z9glbip8pZc/00-07-33.png)
![Screenshot at 7:55: Terminal output displaying the results of the Design Enhancer skill, showing component score increases and an overall project score jump from 86.3/100 to 94/100.](https://ss.rapidrecap.app/screens/Z9glbip8pZc/00-07-55.png)