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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jfrog-package-safety-and-download
by jfrogCheck JFrog Public Catalog and stored packages for a version, interpret catalog security signals, and download through Artifactory (JFrog Platform locations, remote cache, curation-aware package managers, or repo proxy). Use when the user asks whether a package is safe, allowed, curated, or wants to download npm, Maven, PyPI, Go, or similar packages via JFrog. Do NOT use for pure CVE or vulnerability lookups (e.g. "details on CVE-2021-23337") — those are handled by the jfrog skill's Public security domain queries without this workflow.
jfrog
by jfrogInteract with the JFrog Platform via the JFrog CLI, JFrog MCP server and REST/GraphQL APIs. Use this skill when the user wants to manage Artifactory repositories, upload or download artifacts, manage builds, configure permissions, manage users and groups, work with access tokens, configure JFrog CLI servers, search artifacts, manage properties, set up replication, manage JFrog Projects, run security audits or scans, look up CVE details, query exposures scan results from JFrog Advanced Security, manage release bundles and lifecycle operations, aggregate or export platform data, or perform any JFrog Platform administration task. Also use when the user mentions jf, jfrog, artifactory, xray, distribution, evidence, apptrust, onemodel, graphql, workers, mission control, curation, advanced security, exposures, or any JFrog product name.
orders-helper
by jfrogLook up customer orders through the orders_db MCP server. Use whenever the user asks about an order, a tracking number, a delivery, or a customer's purchase history.
processing-watch
by jfrogIdentify and surface every order currently in the `processing` state, so the operator can chase down stalled fulfilment. Use whenever the user asks about stalled orders, processing backlog, things stuck in processing, or orders that haven't shipped yet.
inventory-audit
by jfrogIdentify Folio books with low on-hand stock so the operator can replenish before the title goes out of stock. Use whenever the user asks about books running low, low stock, restock list, what's almost gone, stock audit, or which titles need reordering.
bookstore-assistant
by jfrogCustomer support and order operations for the Folio bookstore. Use whenever the user asks about a book, an order, a refund, a return, store credit, or anything else customer-facing. All canonical data lives behind the `folio` MCP server - never invent prices, stock counts, customer details, or order history.
jfrog-curation
by jfrogUse when working with JFrog Curation -- managing package curation policies, auditing blocked packages, configuring curated repositories, or managing waivers. Triggers on mentions of curation, package firewall, blocked package, curated repository, waiver, or supply chain policy.
jfrog-distribution
by jfrogUse when working with JFrog Distribution and Release Lifecycle Management -- creating release bundles, promoting through environments, distributing to edge nodes, or managing evidence. Triggers on mentions of distribution, release bundle, promote, environment, edge node, release lifecycle, or evidence.
jfrog-mission-control
by jfrogUse when working with JFrog Mission Control -- managing JFrog Platform Deployments (JPDs), checking deployment health, auditing licenses, or listing proxies. Triggers on mentions of mission control, JPD, platform deployment, license, proxy, or deployment health.
jfrog-onemodel
by jfrogQuery any entity on the JFrog Platform using OneModel GraphQL — applications, release bundles, artifacts, builds, evidence, packages, and catalog data through a single unified API. Use this skill when the user wants to query, search, or list anything from the JFrog Platform using GraphQL, including applications, application versions, release bundles, artifacts, evidence, packages, catalog information, or build traceability. Also use when the user asks "what do I have" or "list my..." for JFrog Platform entities. Triggers on mentions of "onemodel", "graphql", "release bundle info", "evidence query", "search evidence", "release bundle artifacts", "build traceability", "graphql query jfrog", "run a graphql query against jfrog", "list applications", "my applications", "search packages", or "catalog info".
jfrog-patterns
by jfrogUse when helping users set up JFrog Platform architectures, best practices, or workflows. Covers 22 recommended patterns across CI integration, repositories, security, release lifecycle, multi-site, and AppTrust. Also covers 5 user journeys (Modernize Delivery, Secure SDLC, Accelerate Productivity, Enterprise Complexity, Trusted AI). Triggers on mentions of pattern, best practice, architecture, get started, CI integration, multi-site, release lifecycle, AppTrust, or how to set up JFrog.
jfrog-runtime
by jfrogUse when working with JFrog Runtime -- monitoring runtime clusters, checking node health, or listing running container images with vulnerability info. Triggers on mentions of runtime, runtime cluster, running images, runtime sensor, runtime controller, container monitoring, or node health.
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.