Instead of complex SDKs or custom code, users can extend tools like Cowork by writing simple Markdown files called "Skills." These files guide the AI's behavior, making customization accessible to a broader audience and proving highly effective with powerful models.
OpenAI has quietly launched "skills" for its models, following the same open standard as Anthropic's Claude. This suggests a future where AI agent capabilities are reusable and interoperable across different platforms, making them significantly more powerful and easier to develop for.
Users can now upload instructional files to teach Claude AI specific abilities. This allows the AI to perform complex, branded tasks like creating presentations or designing posters according to a company's unique style guide, effectively turning it into a personalized expert assistant.
Beyond using pre-made skills, users can simply prompt Claude to create a new skill for itself. The AI understands the required format and can generate the instructional text for a new capability, such as crafting marketing hooks that create FOMO. This democratizes the process of AI customization.
The process of building AI tools is becoming automated. Claude features a 'Skill Creator,' a skill that builds other skills from natural language prompts. This meta-capability allows users to generate custom AI workflows without writing code, essentially asking the AI to build the exact tool they need for a task.
The concept of "Skills" was born when the team found that telling Claude *how* to query a data source and follow design guidelines produced better, more flexible dashboards than building rigid, parameterized tools. This discovery highlighted the power of instruction over hard-coding.
Unlike Claude Projects where the LLM decides how to use tools, Skills execute predefined scripts. This gives users precise control over data analysis and repeatable tasks, ensuring consistent, accurate results and overcoming the common issue of non-deterministic AI outputs.
The implementation of custom skills in Claude has a specific, non-obvious technical workflow. Users must generate the skill, download the file, rename it precisely to 'skill.md', compress it into a zip archive, and then upload it. This exact process is crucial for the feature to function correctly.
The surprising success of Dia's custom "Skills" feature revealed a huge user demand for personalized tools. This suggests a key value of AI is enabling non-technical users to build "handmade software" for their specific, just-in-time needs, moving beyond one-size-fits-all applications.
The tangible asset for a Claude Skill is surprisingly low-tech: a folder containing a 'skills.md' file and other optional resources. This folder is either referenced by Claude in a local directory or zipped and uploaded to the web UI, demystifying the creation process for non-engineers.
Unlike Claude Projects or OpenAI's Custom GPTs which apply a general context to all chats, Claude Skills are task-specific instruction sets that can be dynamically called upon within any conversation. This allows for reusable, on-demand workflows without being locked into a specific project's context.