Understanding Claude Skills: Differences from Projects and MCP and Their Impact on AI Collaboration

Claude Skills are definition files that record how a user wants Claude to work, making the AI remember a set of instructions that can be saved, reused, and refined—effectively turning personal usage habits into a persistent asset.

Previously, Claude suffered from “forgetfulness”: each new task required repeating the same tone, logic, or format instructions. Skills solve this by encapsulating those requirements into a single document, such as a “WeChat public‑account writing Skill” that specifies tone and structure, or a “learning‑notes Skill” that defines how to extract key points and produce summaries.

Unlike one‑off custom prompts, Skills are systematic files that can be stored locally, called repeatedly, combined, and continuously optimized. Users can edit a Skill, invoke it in any Claude conversation, and even let Claude’s built‑in meta‑Skill automatically update the file.

The relationship among Claude’s components is hierarchical: Claude is the “brain”, Skills are the recorded methods, MCP (Model‑Controlled Plugins) are the tools Claude can use, and Projects represent the specific context of a task. When these pieces work together, Claude moves beyond answering questions to planning, executing, and iterating on tasks.

Key benefits highlighted include: one‑click local saving without complex cloud setup, on‑the‑fly modifications per task, and iterative improvement through continuous review. This transforms AI interaction from a temporary Q&A into a long‑term collaborative workflow, making AI more personalized and human‑centric.