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...
huawei-cloud-cce-cluster-management
by huaweicloudHuawei Cloud CCE (Cloud Container Engine) cluster lifecycle management skill using Python SDK v3. Use this skill when the user wants to: (1) create, delete, hibernate, or awake CCE clusters, (2) list clusters and query cluster/node/nodepool/addon information, (3) manage node pools (create, delete, resize), (4) manage nodes (create, delete, cordon, uncordon, drain), (5) manage addons (install, uninstall, update), (6) bind/unbind cluster EIP for public access, (7) get cluster kubeconfig. Trigger: user mentions "CCE cluster", "create cluster", "delete cluster", "node pool", "node management", "hibernate cluster", "awake cluster", "addon", "kubeconfig", "EIP binding", "CCE 集群", "创建集群", "删除集群", "节点池", "节点管理", "休眠集群", "唤醒集群", "插件", "kubeconfig", "EIP 绑定"
huawei-cloud-msmodelslim-model-adapt
by huaweicloudCreate basic Transformers model adapters for msModelSlim. Implements required interfaces and completes a four-step verification workflow: generate test model -> full fallback quantization -> weight verification -> quantization description validation. Use this skill when the user wants to: (1) create msModelSlim adapters for decoder-only LLM, (2) adapt understanding VLM text backbones for quantization, (3) implement W8A8/W4A16 quantization workflow for new models. Trigger: user mentions "msModelSlim", "adapter", "model adapter","quantization", "W8A8","W4A16", "transformers", "LLM", "VLM", "adapter creation", "适配器","模型适配", "量化", "模型适配器", "LLM量化"
huawei-cloud-flexus-l-server-hermes-deployment
by huaweicloudOne-click deployment tool for Hermes on Huawei Cloud Flexus L instances. Supports one-click deployment, ModelArts large model configuration, and robot channel configuration. This skill provides a complete workflow for deploying and configuring Hermes AI Agent platform. Trigger words: "Deploy Hermes", "Install Hermes", "Configure Model", "Configure Channel", "部署Hermes", "安装Hermes", "配置大模型", "配置机器人通道"
huawei-cloud-flexus-l-deploy-jiuwenswarm
by huaweicloudOne-click deployment of JiuwenSwarm multi-Agent collaboration platform on Huawei Cloud Flexus L instances. Usage scenarios: When users need to quickly deploy JiuwenSwarm/JiuwenClaw on Huawei Cloud Flexus L instances, when they need to automatically create cloud instances and deploy AI Agent platforms, when they need to configure model APIs and message channels (Xiaoyi/Feishu/DingTalk). Automatically create instances, deploy applications via COC, configure models and message channels. Trigger keywords: JiuwenSwarm deployment, JiuwenClaw deployment, 九问Swarm部署, 九问Claw部署, 一键部署JiuwenSwarm, AI智能体平台部署, 部署九问Swarm, 部署九问Claw,云服务器部署AI平台.
huawei-cloud-flexus-l-server-manage
by huaweicloudManages Huawei Cloud Flexus L server lifecycle: create, renew, and unsubscribe instances. Use this skill when the user mentions "Flexus L", "Huawei Cloud lightweight server", "purchase server", "renew", "unsubscribe". (中文触发词："购买/创建L实例", "L实例续费", "L实例退订")
huawei-cloud-flexus-l-server-openclaw-deployment
by huaweicloudCreate Huawei Cloud Flexus L Instance (Lightweight Server), deploy OpenClaw application platform on it, and support installation and configuration of models and channels for deployed OpenClaw instances. Web UI access needs to be manually enabled in Huawei Cloud console. Trigger words: "Deploy OpenClaw", "Deploy Flexus L Instance", "Deploy Huawei Cloud Lightweight Server", "Model setting", "Channel Setting", "部署OpenClaw", "部署Flexus L实例", "部署华为云轻量服务器", "设置模型", "设置通道"
huawei-cloud-flexus-l-server-ops
by huaweicloudBased on Huawei Cloud Flexus L API for instance management and operations. Supports querying instance list and details, querying traffic packages, batch start/stop/reboot instances, resetting passwords, and modifying instance information. Suitable for daily operations, lifecycle management, configuration changes, traffic monitoring, and other scenarios for Flexus L instances. Triggers: Flexus L, Huawei Cloud ops, query instance, start, stop, reboot, reset password, modify info, check traffic, traffic package (中文触发词: L实例运维，查询L实例，L实例开机，L实例关机，L实例重启，L实例重置密码，查询L实例流量包).
huawei-cloud-flexus-l-server-scripts-excute
by huaweicloudBased on Huawei Cloud COC (Cloud Operations Center) APIs for script management and remote execution. Supports creating custom scripts (Shell, Python, Bat) and batch execution on target host instances via UniAgent. Applicable to cloud operations automation and batch script deployment scenarios. Trigger keywords: L-instance, COC script, script management, script execution, cloud operations, custom script, batch execution; COC, script management, script execution, cloud operations (中文触发词：L实例执行脚本).
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.