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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chip-diagram-generator
by zhaixin244-wqUse when generating chip module diagrams (block diagrams, timing diagrams, FSM diagrams). Triggers on '框图', '时序图', '状态机图', 'diagram', '架构图', '画图', '画一个'. Generates module block diagrams, timing diagrams and state machine diagrams. Primary format: D2→PNG for block/FSM diagrams, Wavedrom→PNG for timing diagrams.
chip-png-interface-gen
by zhaixin244-wqUse when generating interface port PNG diagrams from Verilog module declarations. Triggers on '接口图', '端口图', 'interface gen', 'port diagram', '接口PNG', 'module snapshot'. Generates module_snapshot style port PNGs with inputs on left, outputs on right, signal names with width and direction arrows.
bom
by mattpainter701BOM management, sourcing, pricing, export, and fabrication preparation. Load the canonical Circuit Weaver skill from `skills/bom/SKILL.md`.
kicad-validate
by mattpainter701Cross-reference design audit -- validates consistency across spec, schematics, BOM, pin maps, and PCB layout. Catches disagreements before fabrication. Run after any significant design change.
eda-pcb
by majiayu000PCB layout and routing. Component placement, trace routing, copper pours, design rule configuration, and layout optimization for manufacturability.
eda-schematics
by majiayu000Schematic capture and wiring. Create schematic sheets, place symbols, add wires and net labels, organize hierarchical designs.
kicad-pcb
by Demerzels-labAutomate PCB design with KiCad. Create schematics, design boards, export Gerbers, order from PCBWay. Full design-to-manufacturing pipeline.
extract-circuit-graph-edge-features
by gabrielmoreiraExtracts and formats edge features from a bipartite circuit netlist graph, ensuring device-to-net ordering and detecting parallel connections based on specific terminal color mappings.
altium-mcp
by flaco-sourceUses the altium-mcp Model Context Protocol server to read and edit PCB/schematic data from Altium Designer via a DelphiScript bridge on Windows. Apply when the user enables the altium-mcp MCP server, mentions Altium Designer, X2.EXE, PCB layers/rules/nets, schematic components, designators, schematic edits, workspace projects, or MCP tools get_server_status, altium_ping, get_schematic_data, edit_schematic, get_pcb_*, get_all_designators, get_component_pins.
pcbschemagen-constraint-guided-schematic-design
by ndpvt-webGenerate PCB schematics from natural language using constraint-guided LLM code generation with knowledge-graph verification. Use when the user says 'generate a PCB schematic', 'design a circuit board', 'create a KiCad schematic from description', 'convert circuit requirements to netlist', 'automate schematic design', or 'generate SKiDL code for a circuit'.
kicad-cli
by o2scaleKiCad command-line interface expertise. Complete reference for schematic/PCB exports, DRC/ERC validation, manufacturing outputs, and automation.
wiring-edit-skill
by Designer-Awei基于当前画布 JSON 与连线意图生成仅含连线的增删计划（add_connection/remove_connection）；可选应用到画布。不增删元件、不移动元件。
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.