Skills

A skill is packaged know-how for doing one kind of task well — a procedure, a house style, a checklist, the gotchas of a recurring job. You write it once, and the model loads it on demand when a task calls for it, then follows it. Think of skills as expertise the model can reach for, rather than instructions you paste in every time.

Open Skills from the sidebar to manage your own and browse the Public library shared across the workspace.

Why skills instead of just prompting

The difference is when the guidance applies:

• A prompt and your memory are always on for the conversations they apply to.
• A skill is loaded only when it’s relevant. That means you can have many specialized skills available without every one of them crowding the model’s attention on unrelated questions.

So skills are how you give the model deep competence in lots of narrow areas at once — formatting a particular report, running a specific kind of analysis, following your team’s review process — and trust it to pull in the right one at the right moment.

What makes a good skill

A clear trigger

Describe when to use it (“when asked to write a release note…”) so the model knows when to reach for it.

Concrete steps

The actual procedure — the steps, the format, the rules, the common mistakes to avoid.

Self-contained

Everything needed to do the task well, so loading the skill is enough — no extra context required.

One job

Scoped to a single kind of task. Several focused skills beat one sprawling one.

Creating, importing, and sharing

1. Add a skill — give it a name, a description of when it should be used, and the instructions themselves.

2. Import an existing skill to bring one in rather than writing from scratch.

3. Share it — browse and publish to the Public tab so skills can be reused across the workspace. My Skills holds yours; Public holds the shared library.

Skills in the wild: how Catalyst builds workflows

Here’s the best proof that skills are powerful — Catalyst uses one to build a core feature of itself. The public workflow-author skill is what teaches the model to turn a conversation into a real, runnable workflow. It’s a normal skill, sitting right in the Public library, that you can open and read:

When you ask Catalyst to “make this into a workflow”, the model loads this skill, follows its instructions on which node types exist and how to wire them, and emits a valid workflow artifact — exactly the mechanism behind Promote a chat to a workflow.

Read that again: a headline product feature is just a skill. Nothing about it is special-cased or hard-coded — it’s the same authoring surface, the same load-on-demand mechanism, the same Public library you have. Anything you can teach the model to do well, you can package the same way.

Tip

Open workflow-author in the Public tab to see what a substantial, real-world skill looks like — the trigger conditions, the step-by-step instructions, and a worked example. It’s a great template for writing your own.

Skills vs. prompts vs. memory

A quick way to choose:

• Skills — task-specific know-how, loaded only when needed. (“How we write release notes.”)
• Prompts — a reusable setup you select for a conversation: instruction, documents, data, and tools.
• Memory — what the model knows about you, recalled automatically everywhere.

Used together, they let Catalyst behave like it already knows your work: who you are (memory), how this conversation should go (prompt), and how to do the task in front of it (skill).