Agent skills, beyond one vendor

Convergent Skills

Agent skills are becoming a shared way to package procedural knowledge for AI agents: a SKILL.md file, optional scripts, optional references, and a loading model that keeps most context out of the model until it is useful.

Free tools

Build the first draft.

The thesis

Skills are capability memory.

A skill is not just a prompt, and it is not the same thing as a tool. It is a portable packaging pattern for capability: what the agent should know, how it should decide that the knowledge applies, which files or scripts support the workflow, and how to validate the result. The format matters because capable agents increasingly need repeatable craft, not another copy-pasted instruction block.

The useful mental model is a three-part split. Skills package task knowledge. Tools execute actions. MCP standardizes how hosts connect to external systems that expose tools, resources, and prompts. These pieces overlap in practice, but they solve different problems.

This site is intentionally cross-ecosystem. For Claude-only browsing, examples, and directory-style discovery, see Claude Has Skills. Convergent Skills focuses on the broader pattern: how reusable skills move across Claude, Codex, GitHub Copilot, MCP development workflows, and whatever agent runtimes adopt the same basic contract next.

If you are ready to make one, start with the Skill Scaffold Generator, check the description in the Description Linter, or use the Skill vs MCP Decider when the architecture is unclear.

Map

Read the system.

Source-backed facts