Using Skills

A Skill is a reusable workflow that enables ChatGPT to consistently perform a specific task. Instead of explaining the same prompts and templates every time, it applies a procedure defined once, again and again.

The basic structure has three parts. A name and description let it recognize the appropriate situation, SKILL.md contains step-by-step instructions, and resources such as templates, examples, brand guides, and schemas are attached alongside.

Skills are especially effective for tasks that involve multiple steps or where structure matters. For example:

• Consistency: Reduces missing formats and inconsistent tone.
• Best practices: Lightly embeds SME-approved procedures.
• Sharing: A team's standard playbook can be used directly within conversations.
• Reuse: A way of working built once can be applied across multiple chats and use cases.

SKILL.md is a plain-text Markdown file that serves as the skill's playbook. It contains what the skill does, what inputs are needed, in what order to process them, what the final output format is, and what checks to perform before completion. Because it is a portable format, it is easy to share and version, and it is described as an Open standard.

The way to create one is simple. Choose a task you do repeatedly, organize the inputs, outputs, and guardrails, then have ChatGPT draft the skill. Afterward, review it and install it, then either use it automatically within the workspace or invoke it explicitly with an @-mention. Depending on workspace settings, it can also be shared with others.

Skills, GPTs, and Projects each have different roles. Skills are reusable workflows that perform specific tasks, GPTs are customized versions of ChatGPT that extend a team's expertise, and Projects are spaces where a team works together with the same context, files, and conversations.

Skills can be applied across various departments, including marketing, sales, finance, engineering, operations, customer success, IT, legal, HR, and executive leadership. The key is not large end-to-end automation, but standardizing frequently used tasks by breaking them into small, clear building blocks.