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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nx-gradle-plugin-version-bump
by nrwlBump the dev.nx.gradle.project-graph plugin version. Use when updating the Gradle project graph plugin version across the codebase, creating the migration files, and updating migrations.json.
nx-docs-style-check
by nrwlCheck modified Nx documentation pages against the astro-docs style guide. Auto-trigger after writing or editing docs content in the nx repo. Also trigger on "check style", "style guide", "docs review", "validate docs". Should run as a final step whenever docs files are modified. IMPORTANT: anytime astro-docs/**/*.mdoc files are modified, this should always run automatically without being asked.
ci-monitor
by nrwlMonitor Nx Cloud CI pipeline and handle self-healing fixes automatically. Checks for Nx Cloud connection before starting.
dist-build-migration
by nrwlMigrate an Nx package to build to a local dist/ directory with nodenext module resolution, exports map, and @nx/nx-source condition.
nx-generate
by nrwlGenerate code using nx generators. USE WHEN scaffolding code or transforming existing code - for example creating libraries or applications, or anything else that is boilerplate code or automates repetitive tasks. ALWAYS use this first when generating code with Nx instead of calling MCP tools or running nx generate immediately.
run-nx-generator
by nrwlRun Nx generators with prioritization for workspace-plugin generators. Use this when generating code, scaffolding new features, or automating repetitive tasks in the monorepo.
multi-version-compliance
by nrwlApply or review multi-version support compliance for first-party Nx plugins. Primary entry point: a Linear task ID (NXC-XXXX) from the "Multi-version supported across plugins" milestone — the task carries the resolved support window, findings, and "Needs human decision" items. Falls back to self-discovery when no task exists. Use when asked to "fix multi-version compliance for @nx/X", "do NXC-XXXX", "review this compliance PR", or when working on a branch / PR titled "multi-version support compliance for @nx/X". Covers the canonical shape (assertSupportedPackageVersion, all-generators-enforce-floor.spec.ts, peer dep alignment, requires-gate auditing, user-pin preservation, executor / inferred-plugin feature gating).
nx-workspace
by nrwlExplore and understand Nx workspaces. USE WHEN answering any questions about the nx workspace, the projects in it or tasks to run. EXAMPLES: 'What projects are in this workspace?', 'How is project X configured?', 'What targets can I run?', 'What's affected by my changes?', 'Which projects depend on library Y?', or any questions about Nx workspace structure, project configuration, or available tasks.
diagnose-sandbox-report
by nrwlDiagnose Nx sandbox violations from a sandbox report. Use when asked to "diagnose sandbox", "analyze sandbox report", "investigate sandbox violations", "check violations", when given a sandbox report JSON file or URL to investigate, or when the user pastes a staging.nx.app sandbox-report URL. Also trigger when discussing unexpected reads/writes in Nx task execution. Guides structured investigation of why tasks read/write undeclared files, determines root causes, and recommends fixes.
nx-multi-repo-migrate
by nrwlMigrate several repos to a target nx version (e.g. 23.0.0-beta.25) in one coordinated pass — delegates `nx migrate` + migrations to a Polygraph child agent per repo, then pushes branches and opens linked draft PRs. Use when asked to upgrade/migrate multiple repos to a specific nx version, or when working a Polygraph session whose goal is an nx version bump across repos.
diagnose-sandbox-report
by nrwlDiagnose Nx sandbox violations from a sandbox report. Use when asked to "diagnose sandbox", "analyze sandbox report", "investigate sandbox violations", "check violations", when given a sandbox report JSON file or URL to investigate, or when the user pastes a staging.nx.app sandbox-report URL. Also trigger when discussing unexpected reads/writes in Nx task execution. Guides structured investigation of why tasks read/write undeclared files, determines root causes, and recommends fixes.
nx-plugins
by nrwlFind and add Nx plugins. USE WHEN user wants to discover available plugins, install a new plugin, or add support for a specific framework or technology to the workspace.
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.