Remember the scene in The Matrix where Neo loads kung fu and five seconds later says, "I know kung fu"? Anthropic has just brought that moment to the world of real-world technology. The new Agent Skills system lets you "teach" Claude any specialization in seconds—from data analysis to writing code. This isn't science fiction; it's the future, and it's happening right now.
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"Uploading Skills" - Reality Instead of Film
In a famous scene from The Matrix, the protagonist, after uploading a martial arts program, opens his eyes and declares, "I know kung fu." It turns out that a similar concept is entering the world of AI. Anthropic has announced "Agent Skills" (or simply "Skills") for its Claude model—knowledge modules and tools that are activated "on demand" and delivered when a specific action requires them.
To put it simply: it's not that Claude has it all "in his head" all the time - instead, he can "load" the appropriate skill when a user or process needs it.
– In the movie: Neo uploads kung fu.
– In reality: Claude can load, for example, the ability to analyze an Excel sheet or create a PowerPoint presentation.
How the Skills mechanism works – from the technical side
The technology is designed in a modular and efficient manner to address a key limitation of LLM systems – the overwhelming amount of data that fills the context window. Below are the key elements:
Three levels of skill implementation
- Level 1 – List of available skills: Claude only sees the metadata of each skill – a short description, name – without the full content. (docs.claude.com)
- Level 2 – Loading Details: When Claude determines that a skill is relevant to the task, a SKILL.md file containing detailed instructions is loaded. (docs.claude.com)
- Level 3 – full file upload: If a skill requires additional resources (Python scripts, images, instructions, bash code), they are loaded only at the time of actual use. (anthropic.com)
Skill Format
– Skill is a folder containing: SKILL.md file (in Markdown + YAML frontmatter), potentially code (e.g. scripts), static resources.
– Skills may contain executable code – e.g., Python scripts or bash commands.
– Providing the ability to create your own skills by the user/organization: via API and console.
Context and Cost Window Effects
– Thanks to this approach, Claude does not need to see all the knowledge at once – it reduces the consumption of tokens, speeds up operation, and reduces costs.
– The company provides pre-built skills (e.g. PowerPoint, Excel, Word, PDF) and a path to creating skills dedicated to the organization.
Importance for business – what does this change in practice?
For organizations interested in AI implementations, the Skills feature opens up specific opportunities:
1. Faster implementations with lower entry barriers
Companies don't have to build AI agents from scratch; each task can be handled by the appropriate skill. This reduces implementation time and costs.
2. Better alignment with internal processes
An organization can package its own rules, industry knowledge, or regulations into a skill, and Claude then operates within that context. This is important for companies operating in regulated sectors (finance, energy, industry).
3. Increased scale and efficiency through modularity
Instead of a single "monolithic" model, we have a library of skills—you can have hundreds of them, loaded only when needed. This makes the system easier to manage and develop.
4. Potential savings
Fewer tokens in reserve, better resource utilization, lower risk of model overload – all this translates into economic benefits for enterprises.
Example of use in practice
Imagine a construction or industrial company using Claude in its reporting process. Instead of having to prepare a prompt with a complete knowledge dossier each time, the company can:
– Create a skill “Construction Report – EU Compliance” containing regulations, templates, guidelines.
– Create a skill “HVAC Failure Detection Data Analysis” containing a Python script for analyzing sensor data.
– When an employee asks, "Prepare my quarterly HVAC compliance report," Claude automatically identifies the appropriate skill and loads it. The model sees only what's needed and generates results faster and more precisely.
These types of applications reduce the need to involve the IT department every time and speed up the pace of operations.
Conclusions and Critical Remarks
Despite the attractiveness of the Skills function, it is also worth noting certain limitations and aspects that the company must consider.
Technical and operational
– Although Claude "only loads when needed," it still requires appropriate infrastructure—including skills library management, versioning, and validation processes. It's not entirely maintenance-free.
– Implementing your own skills requires at least basic competence in preparing files, scripts, and instructions – if the company does not have a project team, external support may be necessary.
Risk and management
– Skills must be well defined and tested – an incorrect script in a skill can lead to incorrect results.
– While modularization projects help with context control, there are still issues of security, regulatory compliance (including the EU AI Act), and confidential data management.
– In the long term, it is necessary to ensure that skills are updated – knowledge becomes outdated, processes change.
Strategic perspective on Anthropic Agent Skills
"The Skills feature aligns with the trend of "enterprise-ready AI agents," not just LLM models for experimentation. For companies, this represents a paradigm shift: from "we're testing AI, maybe something will come of it" to "we're implementing AI tailored to specific processes."
– The choice of supplier (in this case Anthropic) shows that the enterprise AI market is increasingly diversifying its offerings – modularity, customization, updates – these are no longer just performance benchmarks.
– In the long run, organizations that establish a skills library and onboarding process will gain a competitive advantage: faster processes, lower costs, better customization.
The Skills feature in Claude by Anthropic lets you "upload" specialized knowledge and tools exactly when you need them—much like Neo "uploading kung fu" in The Matrix. It's a practical solution, available now, and has the potential to deliver real benefits for businesses.
However, like any technology, it requires thoughtful implementation – it is not enough to count on "magic uploading" – processes, competences and management will be crucial.
For companies in the construction, industrial, technical services, and logistics sectors, this is another step towards accelerating AI transformation – this time with an emphasis not on large-scale experiments, but on specific skills, operational applications, and real effects.
If you wish, I can also prepare a "how-to" for implementing Skills in Polish regulatory conditions (EU/Poland) along with a checklist and potential pitfalls – should I prepare such material?
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FAQ – Anthropic Agent Skills: How does the “Matrix in Reality” work?
What are Anthropic Agent Skills?
Agent Skills is a new feature introduced by Anthropic for the Claude model. It allows specific skills—such as data analysis, coding, or report creation—to be "uploaded" to the AI exactly when they're needed. It's a modular knowledge system activated on demand.
What is the Agent Skills innovation?
Instead of loading all the knowledge at once (which slows down the model), Claude only sees a list of available skills and activates the one selected when the task requires it. As a result, it runs faster, cheaper, and more precisely—without context overload.
Does it really work like in the movie The Matrix?
In a sense, yes. In the Matrix, Neo uploaded combat skills; here, Claude "uploads" a file with instructions and code that instantly expands his abilities. The difference is that instead of fighting, the AI performs complex business tasks.
How can companies use Agent Skills?
Companies can create their own "skills"—for example, with compliance procedures, report templates, and code to automate analyses. Claude can then operate in compliance with industry regulations without requiring repeated training.
What does the process of creating a new Skill look like?
Just create a folder with the file
SKILL.md(in Markdown + YAML format), containing a description and resources. Anthropic has provided this Skill Creator in the Claude application, which automatically generates the necessary files and documentation.Can you create your own skills for the company?
Yes. Anthropic allows you to build and deploy private Skills via API. This means you can program skills unique to a specific organization—for example, financial analysis, ISO procedures, ESG audits, or construction reporting.
Are Agent Skills the beginning of the era of AI agents?
Absolutely. The Anthropic system represents the first real step toward intelligent enterprise agents that not only "understand" commands but can dynamically learn new tasks—just as humans learn new skills.
What are the risks and limitations?
The main challenges are skill library management, data security, and the quality of SKILL.md files. An incorrectly described skill can cause errors, so a validation and update process is necessary, especially in regulated environments.
Are Agent Skills available yet?
Yes. The feature works across Claude.ai, Claude Code, and the Anthropic API. Users can test Skills in beta today, and businesses can deploy their own skills through the Anthropic developer dashboard.
Why is this important for business?
Agent Skills is transforming the way companies use AI—from an experiment to a process tool. It's a step toward practical, modular AI implementation that can significantly reduce costs and increase work efficiency.
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