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
5
Contributors
1
Showing 1–5 of 5 skills
Turns customer results into a persuasive, credible case study. Structures the story as challenge, solution, and measurable results, weaves in quotes and concrete metrics, keeps claims verifiable, and ends with a clear call to action. Produces a publish-ready draft plus a one-paragraph summary and pull-quote suggestions.
Assists with internationalization (i18n) and localization (l10n) of applications and content. Extracts translatable strings, generates resource bundles, translates copy while preserving placeholders and ICU plural/gender rules, and flags layout, date, number, and currency formatting concerns for target locales.
Optimizes web content for search engines and readers. Performs keyword analysis and intent mapping, improves titles, meta descriptions, headings, and internal linking, and generates structured data (JSON-LD) while keeping copy natural and useful. Outputs an actionable, prioritized list of on-page SEO improvements.
Transforms complex technical concepts into clear, well-structured documentation for different audiences. Produces README files, architecture decision records (ADRs), runbooks, onboarding guides, and technical blog posts. Follows documentation best practices with consistent tone, proper formatting, and useful examples.
Generates comprehensive documentation from code including API references, README files, architecture decision records (ADRs), inline comments, and user guides. Adapts tone and detail level to the target audience (developers, end-users, stakeholders).
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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