TL;DR: Anthropic’s recent push into "Skills" has confused many. Is it just another word for "Agents"? No. The difference is fundamental economics. Agents are like hiring expensive contractors: they carry their own baggage (context) and bill you by the hour (token burn). Skills are like handing a smart employee a library of SOPs: they only open the book when they need to. Here is why the future of AI workflows is about Dynamic Loading, not Static Staffing.
James here, CEO of Mercury Technology Solutions. Taipei - December 23, 2025
When Anthropic introduced the "Skills" capability, my first reaction was skepticism. "Wait, don't we already have Agents? Isn't this just rebranding?"
After digging into the architecture, I realized I was wrong. These are two completely different philosophies of AI orchestration. One mimics Staffing; the other mimics Knowledge Management.
1. The "Agent" Trap: The Problem with Digital Staffing
We are all familiar with the Agent concept. It is the idea of "Multiple Personas." You set up a digital assembly line:
- Agent A: The Senior Engineer (Writes code).
- Agent B: The QA Lead (Reviews code).
- Agent C: The Tech Writer (Documents code).
On paper, this looks like a perfect organization. In practice, it is often a Token Furnace.
The Hidden Costs:
- Context Fragmentation: Each Agent lives in its own silo. Agent B doesn't inherently know what Agent A was thinking unless you pass the entire history (expensive) or summarize it (lossy).
- Idle Resource Burn: When you spin up an Agent swarm, you are essentially "hiring" them all at once. They occupy memory and context windows even when they aren't working.
- Coordination Friction: Just like real humans, AI Agents suffer from "information asymmetry." If the QA Agent lacks the context of the Engineer Agent, the output is unstable.
It’s like hiring five freelancers who sit in separate rooms and refuse to talk to each other without a formal meeting. The maintenance overhead often outweighs the productivity.
2. The "Skill" Solution: The Just-in-Time Protocol
"Skills" flips the model. Instead of "hiring more people," you simply give your best employee a better manual.
A "Skill" isn't a persona; it's a directory structure. It typically looks like this:
- SKILL.md: The Master SOP (Standard Operating Procedure).
- workflows/: The specific steps to execute.
- context/: The reference data.
The Magic of Dynamic Loading: The genius of Skills lies in Token Economics. When you start a session, Claude doesn't read every single manual. It only reads the Index (Table of Contents).
- Claude sees it has a skill called "Data Migration."
- It does not load the content yet.
- Only when you ask, "Help me move this SQL database," does Claude dynamically load the SKILL.md into the context window.
- Once the task is done, it releases that context.
The Strategic Difference: "Always On" vs. "On Demand"
The distinction comes down to Load Time and Resource Usage.
Agents = "Formal Employment"
When you activate an Agent, you are loading its entire persona, rules, and history into the Context Window immediately. It’s like a full-time employee sitting at their desk. Whether they are working or not, they are burning electricity (and your API credits).
Skills = "The Library Strategy"
When you use Skills, you are operating a Just-in-Time (JIT) system. Claude acts as a single, highly intelligent worker with access to a massive library. It grabs the "Python Manual" when coding, puts it back, and grabs the "Marketing Manual" when writing copy.
It never holds both manuals in its hand at the same time unless absolutely necessary.
Conclusion: One Genius > Five Interns
The analogy I tell my team is this:
- Agents are like hiring five mediocre employees, each with one specific job description.
- Skills are like hiring one genius and giving them a shelf full of perfect SOPs.
For complex, multi-modal tasks, you don't need a crowded room of Agents bumping into each other. You need a single, coherent intelligence that knows exactly which book to pull off the shelf.
Mercury Technology Solutions: Accelerate Digitality.
