How to Build Reusable AI Skills Across GitHub Copilot, Claude, and LangChain

Major AI platforms including GitHub Copilot, Claude, and LangChain all support custom callable skills that extend an AI assistant's capabilities, though each uses different terminology such as Extensions, Tools, or Functions. Despite the naming differences, the underlying architecture is consistent: a schema defines what the skill does, an implementation executes the logic, and a registration mechanism exposes it to the AI model. A practical example — a deployment status checker that retrieves service health, version, and incident data — is used to demonstrate how the concept translates across three platforms. The AI model itself decides when to invoke a skill based on the user's request, extracts structured arguments from natural language, and incorporates the result into its response. Developers can use this cross-platform understanding to choose the most suitable integration path depending on their toolchain and use case.