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.
Claude Skills aren't limited to natural language instructions; they can reference and execute Python scripts. This enables developers to enforce consistency for technical tasks like data cleaning or validation, preventing the variability that occurs when the LLM generates code on its own.
While Claude's built-in 'create skill' tool is clunky, its output reveals a highly structured template for effective prompts. It includes decision trees, clarifying questions for the user, and keywords for invocation, serving as an invaluable guide for building robust skills without starting from scratch.
You don't need a special command like 'invoke skill' to activate a Claude Skill. The AI agent automatically detects when a skill is relevant based on the context of the conversation. For example, simply pasting a changelog can trigger a 'changelog-to-newsletter' skill without any other instruction.
Instead of using Claude's slow and error-prone web UI to generate skills, a more effective workflow is to use an AI-native code editor like Cursor. By providing Cursor with the official documentation link, it can rapidly and reliably generate the entire skill folder structure, including markdown and validation scripts.
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.