What Are AI Skills and How Do You Use Them?
By Sravanth Thota
If you use AI often, you probably have a few instructions you keep repeating. You may tell the AI to keep answers simple, avoid changing too much code, write in your tone, or follow a certain review process. After a while, repeating the same setup becomes boring, and it also makes the output less consistent.
An AI Skill is a reusable set of instructions for that kind of repeated work. Instead of explaining your preference from scratch every time, you save it once and bring it back when the task needs it. This is one of the simplest ways to create AI continuity across chats and tools.
What is an AI Skill?
An AI Skill is a small guide that tells an AI how to handle a specific type of work. It can be as simple as a writing preference, or it can be a detailed workflow for coding, research, support replies, documentation, or planning.
Think of it like a playbook. The AI still does the task, but the skill gives it the rules, examples, and limits it should follow. That can be enough to change the quality of the result, especially when the task is something you do often.
An AI Skill is not the same as a user profile. A skill focuses on how the AI should handle a specific type of work, covering the rules, steps and limits for that task. A profile is more about who you are and how you prefer to work in general and can also include rules that apply across all sessions.
For example, a writing skill may say:
Write in simple English. Avoid buzzwords. Use short paragraphs. Do not make the result sound too polished.
A coding skill may say:
Make minimal changes. Preserve existing behavior. Read the existing code before editing. Run checks before saying the task is complete.
These are not one-time prompts. They are instructions you expect to reuse across many chats, tools, and tasks.
Why AI Skills are useful
AI works better when it understands how you want the work done. The problem is that most chats start with too little context, so the first few messages often become setup: explain the project, explain your style, explain what not to do, then finally start the real work.
Skills reduce that setup. They keep the important instructions ready so you do not have to remember every detail each time. They also reduce mistakes caused by missing context, like an AI writing in the wrong tone or changing code that should have been left alone.
In a broader AI workflow, skills become part of your reusable context. They help you carry the way you work from one session to another, instead of rebuilding the same context in every chat. And when your context is smaller and more precise, you spend fewer tokens on background that no longer needs explaining.
Skills are not only for developers
The word "skill" can sound technical, but the idea is simple. A skill is just a saved way of doing work, and it is useful for everyday AI use too.
If you write emails often, you can create a skill for short and natural replies. If you study with AI, you can create a skill for beginner-friendly explanations. If you use AI for business planning, you can create a skill that asks for risks, tradeoffs, and next steps before giving a recommendation.
Common examples include blog editing, customer support replies, study tutoring, code review, product planning, and meeting summaries. The best skills are not fancy. They are clear, practical, and tied to work you actually repeat.
How SKILL.md, AGENTS.md, and CLAUDE.md fit in
In AI coding tools, skills often live as Markdown files inside a project. Common examples are `SKILL.md`, `AGENTS.md`, and `CLAUDE.md`.
They may include coding standards, testing rules, security expectations, commands to run, files to avoid, and how to communicate changes. For example, an `AGENTS.md` file may tell an AI assistant to use minimal changes, avoid unrelated refactors, run focused tests, and never commit unless asked.
A `CLAUDE.md` file may contain similar guidance for Claude Code. A `SKILL.md` file may describe a reusable workflow, such as how to review documents, test APIs, or work with a specific framework. These files are useful because they give AI tools a stable source of instructions, and the AI does not have to guess how the project should be handled.
How to use skills while working with AI
The simplest way to use a skill is to paste it into the chat before asking for work. That works, but it becomes tiring if the file is long or if you switch between different AI tools.
A better habit is to keep skills somewhere you can reuse them. Then you can ask the AI to apply the right skill when needed, instead of pasting a long instruction file every time.
Example prompts:
Use my coding review skill before reviewing this change.
Apply my writing style skill and rewrite this email.
Read the project instructions before editing any files.
You can also create smaller skills for specific tasks. One skill can guide code reviews, another can guide release notes, and another can guide customer-facing writing.
What makes a good skill?
A good skill is specific enough to be followed. It should tell the AI what to do, what to avoid, and when to ask before taking action. If the instruction is too vague, the AI still has to guess.
It does not need to be long. In many cases, a short skill is better because the AI can follow it quickly without getting lost in too many rules. For coding, a good skill may include project structure, commands, and safety rules. For writing, it may include tone, audience, length, examples, and words to avoid.
How Memside can help
Memside gives you a single place to store AI Skills outside of any one chat or tool. You can keep the original instruction file, write a shorter version for everyday use, and pull the same skill back into any AI tool when the task needs it. That matters when your work moves across ChatGPT, Claude, coding assistants, and other tools, because useful instructions do not always travel with you unless you have somewhere to keep them.
When a skill is stored in Memside, your AI tool can load it through MCP without you having to paste anything manually. The skill becomes part of your reusable context and stays consistent no matter which tool you are working with that day. Over time, storing skills this way also reduces the token overhead of repeating the same setup instructions at the start of every session.
If you want to see how this fits into a real AI workflow, including checkpoints, decisions, and project handoffs, read - How to Use Memside to Resume Work Across AI Chats
The simple way to start
Start with one skill you actually need. A large library on day one is not the goal, and it usually becomes harder to maintain than it is worth. Pick one area where you find yourself giving the AI the same instructions repeatedly, write it down once as a skill, and use it for a few real tasks.
A good first skill is usually your writing style, coding rules, code review checklist, or project setup instructions. Refine it when you notice what works and what creates confusion, and add more skills only when a clear need shows up.