Agent skills, and how to actually run them
A skill teaches your AI how to do a job. When that job means running code, reading a database, searching the live web, or committing to a repo, the work needs a safe place to run. That is what UniversalBench is: one hosted MCP server your skills can call, with safety built in. Works with Claude, ChatGPT, Gemini, Cursor, and any MCP-compatible AI.
Skills are the recipe. The work still has to run somewhere.
A skill is a folder with a SKILL.md file: instructions, and often a few small scripts, that teach your AI how to do a job the same way every time. That is the recipe, and a recipe is not a kitchen. The moment a skill needs to run code, read a database, call the live web, or commit to a repo, that work has to execute somewhere, and you want it to run safely. MCP is how your AI reaches those tools. UniversalBench is the hosted place the work actually runs. The skill is the recipe, MCP is the wire, and UniversalBench is the kitchen.
See it in action
Skills run code, so the runtime matters
Anthropic is blunt about this in its own guidance: a skill can direct your AI to run code or call tools in ways that do not match its stated purpose, so you should only run skills you trust. When a skill’s steps run on UniversalBench, three checks are always on. Code is validated and confirmed to load before it is ever committed. Every model call is cost estimated and capped before it runs. No request can reach a private or internal network address. The work gets done without handing a skill the keys to everything.
Connect UniversalBench
Add the server
Connect your UniversalBench MCP URL in whichever client runs your skills.
Keep your skills where they are
Your SKILL.md folders do not change. They just gain a place to run the heavy steps.
Save your secrets once
Put any token or database URL in your secret vault and the matching capability unlocks.
Let the skill call it
When a step needs code, data, the web, or a repo, the skill calls UniversalBench and the work runs safely.
Credentials live in an encrypted secret vault
When a skill’s step needs a credential, a GitHub token, a database URL, an API key, you save it once in your secret vault. You enter the secret name on the left and the secret value on the right, then save. Your AI never sees the value, it is never shown in the chat, and the matching capability unlocks automatically.
A skill alone versus a skill with an execution layer
| Skill on its own | Skill plus UniversalBench | |
|---|---|---|
| What it gives the AI | Instructions and small scripts | Instructions plus real execution |
| Run code, query a database, hit the web | Only if the host provides it | One hosted URL covers all of it |
| Reach your tools | Depends on the surface | GitHub, Postgres, Slack, Sheets, and more |
| Safety on the work | Up to you to audit | Validated code, capped spend, no internal network |
| Credentials | In files or prompts | Encrypted vault, never shown |
Frequently asked questions
Do agent skills need UniversalBench?
No. Skills run in whatever execution environment the host gives them, and many tasks run fine there. UniversalBench is for when a skill needs to reach your database, the live web, your repos, or any model, or when you want validated code, capped spend, and no internal network access on the work.
Is this an official Anthropic product?
No. Agent skills are an open standard from Anthropic, published at agentskills.io. UniversalBench is an independent hosted MCP server you pair with your skills. It works with Claude, ChatGPT, Gemini, Cursor, and any MCP-compatible AI.
What is a skill, exactly?
A folder with a SKILL.md file: a name, a description, instructions, and often a few scripts. Your AI preloads the description and reads the full instructions only when a task matches.
How does it stay safe?
Code is confirmed to load before it commits, every model call is cost capped before it runs, and no request can reach a private or internal address.
