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.
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long-context-1m
by latestaiagentsUse Claude's 1M-token context window effectively — when to use it, how to structure inputs for recall, how to price it, and how to combine with prompt caching to keep it affordable. Use this skill when building apps that feed large codebases, long documents, or entire conversation histories to Claude, or when weighing 1M context vs RAG. Activate when: 1M context, long context, big context window, context vs RAG, Claude 1 million tokens, context-beta header.
policy-document-writer
by latestaiagentsCreate clear, compliant HR policies and employee handbook content. Use this skill when writing company policies, updating handbooks, or ensuring compliance. Activate when: HR policy, company policy, employee handbook, workplace policy, PTO policy, remote work policy.
compensation-analysis
by latestaiagentsAnalyze compensation data, create salary bands, and ensure pay equity. Use this skill when benchmarking salaries, building compensation structures, or analyzing pay equity. Activate when: compensation, salary, pay equity, salary bands, compensation analysis, total rewards, salary benchmark.
agent-cost-budgeting
by latestaiagentsUse this skill when managing AI agent costs. Activate when the user needs to control token usage, implement cost limits for agents, optimize LLM spending, track agent costs, or prevent runaway API bills in agent systems.
eval-dataset-design
by latestaiagentsDesign eval datasets that actually measure model quality — coverage, difficulty distribution, labeling consistency, and avoiding contamination. Covers sourcing, stratification, label quality, and when to generate vs curate. Use this skill when building a new eval set, realizing your current evals don't catch regressions, or labeling is inconsistent. Activate when: eval dataset, benchmark, test set, eval coverage, label quality, synthetic eval, dataset design.
sensitive-data-protection
by latestaiagentsOWASP A03 - Sensitive Data Exposure Prevention. Use this skill when handling PII, passwords, credit cards, API keys, or any sensitive information. Activate when: encryption, PII, personal data, credit card, SSN, password storage, HTTPS, TLS, data at rest, data in transit, GDPR, compliance, data masking.
agent-handoff-protocols
by latestaiagentsUse this skill when designing task handoffs between agents. Activate when the user needs to pass work between agents, transfer context between agents, implement agent-to-agent communication, or design protocols for agents to collaborate on sequential tasks.
cost-quality-tradeoff
by latestaiagentsMeasure and optimize the cost/quality curve — which model, prompt, and settings give the best quality per dollar. Covers Pareto analysis, break-even thresholds, and when to spend more vs less. Use this skill when optimizing LLM spend, picking a default model for a feature, or deciding whether a premium model is worth it. Activate when: cost vs quality, model selection, eval cost, Pareto frontier, cheaper model, premium model tradeoff.
commit-message-crafter
by latestaiagentsUse this skill when writing Git commit messages. Activate when the user asks about commit message format, conventional commits, how to write good commit messages, commit message best practices, or when they're about to commit changes and need help crafting the message.
xxe-prevention
by latestaiagentsOWASP A04 - XML External Entity (XXE) Prevention. Use this skill when parsing XML, processing SOAP requests, handling SVG uploads, or working with XML-based formats. Activate when: XML parsing, SOAP, SVG upload, XML input, DOCTYPE, DTD, external entity, XML bomb, billion laughs, XSLT.
onboarding-checklist
by latestaiagentsCreate comprehensive onboarding plans that set new hires up for success. Use this skill when preparing for new employee arrivals, improving onboarding processes, or building role-specific onboarding. Activate when: onboarding, new hire, first day, new employee, orientation, employee onboarding, 30-60-90.
performance-review-assistant
by latestaiagentsWrite constructive, specific performance reviews that drive growth and development. Use this skill when writing performance reviews, giving feedback, or preparing for review conversations. Activate when: performance review, employee review, feedback, annual review, quarterly review, evaluation.
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.