You wouldn't buy a smartphone and only use it to make phone calls. Yet most people treat AI assistants the same way—starting every conversation from scratch, repeating the same context, and manually pasting the same instructions over and over.

If you are using ChatGPT, Claude, Manus, or OpenClaw out of the box, you are leaving an enormous amount of productivity on the table. The real power of these tools unlocks when you stop treating them as generic chat interfaces and start codifying your workflows into reusable "skills" or "custom instructions."

But there is a trap here. If you build all your custom instructions inside ChatGPT, what happens when Claude releases a better model? Or when you want to use Manus to automate a complex browser task? Your hard-won expertise is locked inside a single platform.

The solution is remarkably simple: treat your AI skills like software code. By writing your skills once and storing them in a central GitHub repository, you create a portable vault of expertise that can be instantly deployed to any AI tool you use today—or whatever new platform emerges tomorrow.

AI LESSON

How to write, store, and deploy AI skills across ChatGPT, Claude, Manus, and OpenClaw.

The strategy below solves the biggest problem with AI adoption: the friction of context-setting. By centralizing your instructions, you ensure that every AI tool you use executes tasks with your exact preferences, formatting, and business logic. It sounds technical, but it is entirely accessible to non-developers.

The reason a central vault is possible is the emergence of the Agent Skills open standard. This standard defines an AI skill as a simple text file, typically named SKILL.md.

This file contains two parts: a brief metadata section at the top (called YAML frontmatter) that tells the AI what the skill is called, and the actual markdown instructions that tell the AI what to do. Because these are just plain text files, they are universally readable. Claude Code, OpenClaw, and Manus all natively support this format. For ChatGPT, you simply copy the instruction text into your settings.

You do not need to write these instructions from scratch. The most efficient way to create a skill is to have an AI write it for you.

Step 1: Open your preferred AI (like Claude or ChatGPT) and explain the task you want to automate. For example: "I want to create a skill that analyzes financial reports. It should always extract the top three risks, format the output as a markdown table, and use a professional, objective tone."

Step 2: Ask the AI to format this as an Agent Skill. Say: "Please write this as a SKILL.md file following the Agent Skills open standard, including the YAML frontmatter with a name and description."

Step 3: Review the generated text. Ensure the instructions are clear, step-by-step, and leave no room for ambiguity.

Time: 5–10 minutes per skill.

GitHub is the perfect home for your skills. It provides version control (so you can see how a skill has evolved), acts as a secure backup, and makes it trivial to sync your skills across different machines.

Step 1: Create a free account at GitHub.com if you do not already have one.

Step 2: Create a new repository. Name it something like my-ai-skills. Set it to Private so your proprietary business logic remains confidential.

Step 3: Inside the repository, create a new folder for your skill (e.g., financial-analysis).

Step 4: Inside that folder, create a new file named SKILL.md and paste the text generated in the previous step. Commit the new file.

Time: 5 minutes for the initial setup.

Now that your skill is safely stored in GitHub, you can deploy it to whichever tool is best suited for the task at hand.

For ChatGPT: Open ChatGPT, navigate to Settings, and select Personalization. Click on Custom Instructions. Open your SKILL.md file in GitHub, copy the instruction text, and paste it into the "How would you like ChatGPT to respond?" field. If you use ChatGPT Projects (available on paid plans), you can paste these instructions directly into the Project settings to keep them scoped to a specific workspace.

For Claude Code and OpenClaw: Because these tools operate in your local environment, you simply clone your GitHub repository to your machine. For Claude Code, place the skills in the ~/.claude/skills/ directory. For OpenClaw, place them in your workspace/skills/ folder. Both tools will automatically detect the SKILL.md files and make them available via a slash command (e.g., /financial-analysis).

For Manus: Manus executes skills end-to-end in a secure cloud environment. You can upload your SKILL.md file directly into the Manus interface. When you trigger the skill, Manus reads the instructions and autonomously executes the workflow, leveraging its browser and code execution capabilities.

While this workflow provides excellent portability, it is not a perfect synchronization system. When you update a skill in GitHub, your local tools (Claude Code, OpenClaw) can pull the latest version automatically via Git. However, web-based interfaces like ChatGPT require you to manually copy and paste the updated text. Additionally, while the core instructions are portable, certain tool-specific capabilities (like Manus's native browser automation) may require slight tweaks to the instructions to function optimally across different platforms.

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