Explore AI Agent Skills & Claude Prompts
Discover open-source agent skills for Claude Code, Codex, ChatGPT, and any tool that uses SKILL.md.
Enter through keywords, occupations, creators, and GitHub sources to see what kinds of skills are emerging across domains.
Use the same catalog through the API
Connect 381,784 public skills to your own search, analytics, or agent workflow with the REST API.
Querying local SQLite index...
running-effective-1-1s
by oldwinterRun effective 1:1s and skip-levels as a manager/leader and produce a 1:1 Operating System Pack (cadence plan, agendas, shared doc templates, coaching prompts, career conversation plan, and quality gates). Use for 1:1, one-on-one, 1-on-1, manager check-ins, coaching, career conversations, and skip levels. Category: Leadership.
onboarding-new-hires
by oldwinterDesign a high-signal onboarding experience and produce a New Hire Onboarding Pack (preboarding checklist, first-week plan, buddy/first-pair plan, listening tour kit, working agreement, 30/60/90 + 1y/2y success plan, 30-day state-of-the-union memo). Use for onboarding, first 90 days, new hire ramp, manager onboarding plan, and joining plans. Category: Hiring & Teams.
fundraising
by oldwinterPlan and run an early-stage fundraising process and produce a Fundraising Pack (raise decision memo, round design brief, pitch narrative + deck outline, investor pipeline + tracker, outreach/follow-up scripts, diligence checklist). Use for fundraising, raising capital, venture capital, pitch deck, investor outreach, pre-seed, seed. Category: Career.
managing-imposter-syndrome
by oldwinterManage imposter syndrome at work and produce an Imposter Syndrome Management Pack (trigger & pattern map, reframes, evidence bank, experiment plan, support scripts, maintenance routine). Use for self-doubt, feeling like a fraud, new role anxiety, stretch assignments. Category: Career.
sales-compensation
by oldwinterDesign a sales compensation plan (OTE & pay mix, quotas & ramp, commission mechanics, and retention-aligned incentives) and produce a Sales Comp Plan Pack. Use for AE/SDR/AM comp plans, early sales hires, and GTM scaling. Category: Sales & GTM.
building-a-promotion-case
by oldwinterBuild a promotion case and produce a Promotion Case Pack (target role + timeline, ladder mapping, evidence log, impact narrative, manager alignment plan, sponsor/visibility map, submission-ready promo doc). Use for promotion packet, getting promoted, leveling up, career ladder, promotion committee. Category: Career.
career-transitions
by oldwinterPlan and execute a career transition and produce a Career Transition Pack (progress metric + push/pull map, target archetypes, option scorecard, opportunity pipeline + outreach scripts, skills plan, 4–12 week experiment plan). Use for career change, career pivot, career transition, switching roles. Category: Career.
finding-mentors-and-sponsors
by oldwinterBuild a mentor and sponsor network with targeted outreach and follow-up cadence.
finding-mentors-sponsors
by oldwinterBuild a Mentor & Sponsor Plan Pack (mentor portfolio, sponsor strategy, target list, outreach scripts, meeting agenda, tracking + cadence). Use for finding a mentor, finding a sponsor, mentorship, sponsorship, career advisor, career coaching, networking outreach. Category: Career.
building-team-culture
by oldwinterBuild or refresh a team culture and produce a Team Culture Operating System Pack (culture snapshot, culture code, norms, rituals, rollout + measurement plan). Use for team culture, culture code, team values, team norms, psychological safety, and coaching culture. Category: Hiring & Teams.
delegating-work
by oldwinterCreate a Delegation Pack (delegation brief, decision rights, context handoff, check-in cadence, review plan, debrief). Use for delegation, letting go, empowering reports, and avoiding micromanagement.
having-difficult-conversations
by oldwinterPrepare and lead difficult conversations as a manager/leader and produce a Difficult Conversation Pack (conversation brief, talk track/script, objection+emotion handling plan, follow-up note, and quality gates). Use for difficult conversation, hard conversation, tough feedback, performance conversation, promotion denial, layoff conversation, termination conversation, firing. Category: Leadership.
Browse Agent Skills by Occupation
23 major groups · 867 SOC occupations
Browse by Category
Explore agent skills organized by their primary use case
Explore the agent skills ecosystem by occupation and creator
SkillMD is not just a keyword search box. It is an open map that organizes public skills by occupation, creator, and repository, helping you see which workflows, judgment criteria, and domain habits people are writing for AI agents.
Then follow creators and GitHub repositories back to the source: compare the skills a team maintains, whether the repo is active, and how the README frames the work before you open, install, or reuse anything.
Use it three ways: learn an unfamiliar field by occupation, study how creators organize skills, then use source context to decide what is worth opening or reusing.
01 Map a field
Browse 23 occupation groups and 867 SOC roles to learn what skills exist in adjacent domains and how they break down real work.
02 Follow creators
Use creator and repository pages to inspect maintained skill collections, recent updates, and source context before trusting a result.
03 Search with sources
Search 1.7M+ collected skills, then use occupation tags, creators, and GitHub source context to decide what is worth opening.
Start with the occupation map, then follow creators and repositories back to real code. SkillMD helps explain why a skill is worth opening, not only what it is named.
Standardizing Agent Capabilities with SKILL.md and Model Context Protocol (MCP)
In the rapidly evolving landscape of artificial intelligence, LLM agents (Large Language Model agents) have transitioned from simple text predictors to autonomous problem solvers. To orchestrate complex, multi-step agentic workflows, developers require a standardized format to specify agent capabilities, prompt instructions, system rules, and database bindings. This is where SKILL.md and the Model Context Protocol (MCP) have emerged as standard developer paradigms. SkillMD serves as the central directory for indexing, exploring, and sharing these critical agent configurations.
Our open-source registry currently tracks over 1.7 million collected SKILL.md configurations and system prompts. By compiling agent configurations from active developers on GitHub, we bridge the gap between prompt engineering research and production execution. Whether you are building agents with Anthropic's Claude Code, OpenAI's GPT-4, Google's Gemini, or local models using Ollama and LlamaIndex, standardized skill definitions ensure your agents behave predictably across different runtime environments.
What is the Model Context Protocol (MCP)?
The Model Context Protocol (MCP) is an open-source standard designed to connect LLMs to data sources, developer tools, and external environments. MCP establishes a bidirectional communication channel between client applications (like Cursor, Claude Desktop, or custom agent systems) and servers hosting data or capabilities. Standardizing instructions via SKILL.md enables LLMs to query databases, read local files, execute terminal commands, and integrate third-party APIs. SkillMD allows you to find ready-to-run MCP servers and prompt instructions for various occupations and technical tasks.
The Structure of a Professional SKILL.md File
A valid SKILL.md configuration is designed to be easily read by humans and parsed by LLMs. It contains precise system instructions, trigger conditions, required parameters, and execution examples. Below is the typical architectural blueprint of a professional agent skill:
- Metadata & Core Scope: Declares the name of the skill, author details, target models, and a description of the capability.
- Triggers & Intent Detection: Details semantic triggers that help the agent decide when to invoke this skill.
- System Prompts: Explicit system-level instructions that direct the agent's behavior, personality, safety guardrails, and formatting preferences.
- Capabilities & Tools: Lists the files, databases, or APIs the agent must access to complete the tasks.
- Few-Shot Examples: Demonstrates real inputs and outputs, helping the model generalize behavior through in-context learning.
Optimizing Agent Workflows for Modern LLMs
Writing effective agent skills requires deep knowledge of prompt engineering. With the release of advanced reasoning models like Claude 3.5 Sonnet, ChatGPT o1, and DeepSeek-V3, prompt templates must focus on structured thinking. Developers are encouraged to use XML tags (e.g., <thought>, <context>, and <rules>) to isolate execution boundaries. Standardized prompts prevent agents from suffering from context drift, ensuring that long-running tasks remain aligned with the initial system parameters.
Exploring by SOC Occupations and Creator Profiles
What makes SkillMD unique is its taxonomy. Instead of simple text search, we parse and organize files according to the Standard Occupational Classification (SOC) system. This means you can discover skills written for Computer and Mathematical roles, Business and Financial operations, Legal, Design, and and Educational Instruction fields. By tracking creator profiles, developers can study how different teams organize their custom instructions, compare version updates, and fork public configs for specialized enterprise use cases.
SkillMD operates as a high-performance index running on a fast Go backend and a highly responsive Astro SSR frontend. All search queries execute in milliseconds, featuring smart debouncing to prevent multiple API requests while keeping user data secure. Join our community of developers to standardize your AI agent instructions and optimize your LLM prompting workflows today.
Frequently Asked Questions
A practical guide to agent skills: what they are, how to inspect them, and how SkillMD helps you explore the ecosystem.