Skills
The open registry for AI agent skills — structured prompts and workflows with recommended models, example prompts, and compatible tools.
Skills
7
Categories
9
Compatible tools
5
Contributors
1
Showing 1–7 of 7 skills
Generates platform-tailored social media posts from a single idea or announcement. Adapts length, tone, hashtags, and formatting for X, LinkedIn, Instagram, and threads. Produces hook-first copy, variant options for A/B testing, and a suggested posting cadence while respecting each platform's conventions and character limits.
Reviews and rewrites resumes and CVs to be clear, achievement-focused, and ATS-friendly. Rewrites bullet points using strong action verbs and quantified impact, aligns wording to a target job description, flags gaps and red flags, and checks formatting for applicant tracking system compatibility.
Drafts long-form blog posts from a topic, outline, or set of notes. Handles title and hook generation, logical section structure, SEO-aware headings, tone matching, internal linking suggestions, and a clear call to action. Produces publish-ready Markdown with meta description and suggested tags.
Drafts email newsletters that get opened and read. Writes subject lines and preview text, structures the issue with a clear lead, scannable sections, and a single primary call to action, and adapts tone to the audience. Can turn a list of updates or links into a cohesive issue and suggest send-time and segmentation tips.
Turns merged pull requests, commits, and issue references into clear, audience-appropriate release notes. Groups changes into features, fixes, and breaking changes, translates technical detail into user-facing value, and produces both a concise highlights section and a complete changelog.
Rewrites vague or technical error messages into clear, actionable user-facing messages. Considers the audience (end-user vs developer), suggests error codes, and provides guidance on what the user can do to resolve the issue.
Drafts professional emails for various business contexts — follow-ups, introductions, requests, escalations, and announcements. Adapts tone from formal to friendly based on audience and relationship. Keeps messages concise and action-oriented.
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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