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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dc-power-flow
by benchflow-aiDC power flow analysis for power systems. Use when computing power flows using DC approximation, building susceptance matrices, calculating line flows and loading percentages, or performing sensitivity analysis on transmission networks.
capacitance-calculation
by SpectrAI-InitiativeCalculate electrical capacitance from geometric parameters and dielectric properties for circuit design.
electrical-circuit-analysis
by SpectrAI-InitiativeElectrical Circuit Analysis - Analyze electrical circuit: compute capacitance, convert resistance units, calculate total charge, and duty cycle. Use this skill for electrical engineering tasks involving convert resistance kOhm to Ohm calculate geometric term calculate absolute error. Combines 3 tools from 3 SCP server(s).
electromagnetic-analysis
by InternScienceElectromagnetic Field Analysis - Analyze EM fields: vacuum permittivity, total charge, radiation pressure, and photon calculations. Use this skill for electromagnetics tasks involving calculate vacuum permittivity calculate total charge calculate radiation pressure calculate total power. Combines 4 tools from 2 SCP server(s).
energy-systems
by omer-metinPower systems engineering covering grid modeling, power flow analysis, energy storage dispatch, demand response, and electricity market economics. Spans transmission/distribution planning to real-time operations. Use when "power flow|load flow|grid model, energy storage|battery dispatch|ESS, demand response|load management|peak shaving, electricity market|LMP|locational marginal price, grid stability|frequency|voltage, capacity planning|resource adequacy, unit commitment|economic dispatch, transmission|distribution|power system, " mentioned.
motor-control
by omer-metinPatterns for electric motor control including Field Oriented Control (FOC), stepper motor control, encoder interfaces, current sensing, and power electronics. Covers BLDC, PMSM, DC brushed, and stepper motor applications. Use when ", " mentioned.
pie-power-systems
by TibsfoxElectrical power distribution design for infrastructure: load calculations (NEC 220), conductor sizing (NEC 310.16), transformer/UPS/PDU selection, redundancy architectures (N through 2N+1), DC distribution, and voltage classes 120V-480V. Activates for electrical load calculations, conductor sizing, power equipment selection, data center power design, and redundancy architecture planning.
repairing-signal-tower
by ComeOnOliver信号塔修复 - Stella尝试修复或建造信号发射装置,希望联系地球或发送求救信号
contingency-mitigation
by Power-AgentSenior power-engineer playbook for contingency violations. Use whenever N-1 or N-2 studies reveal voltage or thermal problems, binding contingencies, or post-outage islanding — including escalations from a tool skill's contingency run. Triggers on "N-1 violation", "worst contingency", "preventive vs corrective action", or "do we need a RAS". Moves from ranking contingencies to identifying preventive and corrective actions that cover a family of outages.
dynamic-stability-mitigation
by Power-AgentSenior power-engineer playbook for dynamic stability problems. Use whenever eigenvalue or time-domain studies show poor damping, transient angle instability, weak voltage recovery, or sustained oscillations in tools such as ANDES or PSS/E — including escalations from a tool skill's dynamic run. Triggers on "low damping", "unstable after the fault", "tune the PSS", or "voltage recovery too slow". Gives an ordered fix sequence across dispatch, controls, protection, and special schemes.
frequency-response-mitigation
by Power-AgentSenior power-engineer playbook for frequency-performance problems. Use whenever studies or operations show low system inertia, poor frequency nadir, high RoCoF, weak primary frequency response, UFLS encroachment, or reserve shortfall after loss of the largest unit or HVDC import. Triggers on "frequency nadir", "RoCoF too high", "inertia too low", "UFLS risk", "primary frequency response", or "loss of largest unit". Distinct from dynamic-stability-mitigation, which handles damping and angle stability rather than frequency containment.
interconnection-impact-mitigation
by Power-AgentSenior power-engineer playbook for screening and mitigating the grid impact of a new generator, storage, or large-load interconnection. Use whenever the question is whether X MW can connect at a point of interconnection and what upgrades it needs. Triggers on "interconnection study", "system impact study", "POI", "can we connect this plant at bus Y", "short-circuit ratio", or "weak grid". Walks from steady-state screens through weak-grid and reactive checks to the binding constraint and its mitigation set.
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.