Skills
The open registry for AI agent skills — structured prompts and workflows with recommended models, example prompts, and compatible tools.
Skills
5
Categories
9
Compatible tools
4
Contributors
1
Showing 1–5 of 5 skills
Generates candidate names for products, features, projects, or companies against a clear brief. Explores naming styles (descriptive, evocative, coined, compound), checks each for pronounceability and unwanted meanings, and suggests domain and handle patterns to verify. Returns a shortlist with rationale rather than an undifferentiated list.
Creates accessible color palettes for brands and UIs from a brief or a seed color. Produces primary, secondary, and neutral scales with hex values, suggests semantic tokens (success, warning, error, info), and checks foreground/background pairings against WCAG contrast ratios. Outputs ready-to-use CSS variables or design tokens.
Writes conversion-focused ad copy for search, social, and display. Crafts headlines and descriptions within platform character limits, leads with a clear benefit and hook, matches message to audience and funnel stage, and produces multiple variants for A/B testing. Keeps claims honest and includes a strong, specific call to action.
Develops a distinctive, consistent brand voice and tone system. Defines voice attributes, do/don't guidance, vocabulary and grammar rules, tone shifts by context (marketing, support, errors), and worked before/after examples. Produces a practical style guide teams and AI assistants can apply across every touchpoint.
Facilitates structured brainstorming sessions using proven ideation frameworks — SCAMPER, Six Thinking Hats, How Might We, Crazy Eights, and more. Generates diverse ideas, challenges assumptions, and helps converge on the strongest concepts.
Skills vs MCP servers
what's the difference?Skillsthe “what to do”
A skillA reusable, structured prompt/workflow with recommended models, an example prompt, and compatible tools. packages know-how — instructions, an example promptA ready-to-use prompt template that demonstrates how to invoke the skill., and recommended models — so an agent performs a task consistently. Skills add knowledge, not new connections.
MCP serversthe “how to connect”
An MCP serverModel Context Protocol server — a standard way to expose tools, resources, and prompts to AI agents and IDEs. gives an agent new capabilities by connecting it to real systems (databases, APIs, files) over a transportHow the client talks to the server: stdio (local process), SSE, or HTTP streaming.. MCP adds connections and actions, not task instructions.
Rule of thumb: reach for a skill when you need the model to do a task well, and an MCP server when you need it to reach a tool or system. They compose — a skill can rely on tools an MCP server provides.
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