Claude's New Standard Skill System: The Dawn of AI's Division of Labor

I noticed something: our way of using artificial intelligence is in the midst of a profound transformation. In the past, when you wanted an AI to write a weekly report, you had to repeatedly input the same lengthy instructions each time. The format, tables, references—all had to be manually explained. The result? AI could still make mistakes with numbers or mix up formats.

Now, Claude's new Skill system is emerging, and this inefficient era is officially over. The standard skill package instantly turns AI into a domain expert. Instead of sentence-by-sentence instructions, it becomes a true intelligent folder.

What's inside this folder? Usually three core components: First, a detailed user guide (explains every detail in Markdown format). Second, standard templates—Word, Excel files are stored directly in the folder. AI no longer guesses; it uses these standard files directly. Third, automated scenarios. If complex calculations are needed, Python scripts run automatically, producing 100% accurate results.

The result: Just tell Claude "Prepare the weekly report." It automatically reviews the manual, pulls data, applies the standard template, and delivers a professional document perfectly aligned with your expectations. This standard skill approach fundamentally changes how AI works.

This system is cleverly designed to solve two problems. First, AI's context scope is costly. Standard skills enable "incremental loading"—AI remembers skill names daily and only opens the folder when needed. Faster response, lower cost. Second, this system can be used across multiple platforms. You can transfer your "Report Expert" skill from the web version directly to Claude Code on your computer.

The future gets even more interesting. As skills become widespread, AI's working model will radically change. You’ll be able to combine different skills like Lego blocks. For example, you combine a "Data Analysis" skill with a "German Translation" skill. AI first processes the data, then translates the result into German. Agents (Agents) will be the brains behind these skills. You’ll be able to download different skill packages into your general AI assistant—sometimes a legal advisor, sometimes a coding expert.

In the final stage, when your personal AI assistant detects it’s lacking in a task, it will automatically find other agents in the market. Intelligence will flow freely among agents, like water and electricity.

Why is Web3 inevitable for this market? If a single large model neuron exists, then standard skills are the synapses. Neurons themselves have potential, but true intelligence emerges when connected through skills. Web3 introduces the value capture mechanism.

Look, many people think these skills are just copyable snippets of code. But it’s different. When dozens of standard skills—like (tax auditing, on-chain strategies)—come together for specific industries, a high barrier to competition forms. Web3 provides access control—companies can encapsulate critical business logic in private skills. Global "Intelligence Micro-Payments" become possible. When one agent calls another’s skill, there’s no need for complex international banking systems; it’s as simple as breathing.

Security is critical. As intelligence begins to generate high value, protection becomes essential. Web3 offers a three-layer system: Hash fingerprint (digital stamp for each skill), blockchain ledger (immutable), and local security tools (anomaly detection). If any issue arises, the system immediately shuts down.

In conclusion: Skills have transformed AI from a chatbot into a work specialist. The Web3 market aims to scale this value from 1 to 100. Each packaged expertise will be verified by fingerprint, priced via Web3, and open to secure global collaboration. It’s worth following these developments at Gate.