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...
nginx-config-generator
by heldernoidGenerate production-ready nginx configuration files for reverse proxy, SSL, rate limiting, and caching setups. Use when you need an nginx config for a web application, API, static site, or reverse proxy. Triggers include "nginx config", "nginx configuration", "nginx setup", "reverse proxy config", "SSL nginx", "nginx rate limiting", or any request involving nginx web server configuration.
exercise-log
by heldernoidLog workouts with exercises, sets, reps, and weights. Automatically tracks personal records, monitors workout streaks, manages training goals, and exports data as CSV or PDF. Use when a user needs to log a workout, check personal records, review weekly volume, or track goal progress.
nutrient-analysis
by heldernoidInterpret soil test nutrient data, identify deficiencies, query trends, and generate comparison reports. Use when asked to identify which fields need lime, find all phosphorus-deficient fields, compare nutrient values between tests, generate a before/after amendment report, or explain what a nutrient status means for crop production. Triggers include "which fields are deficient", "nutrient trend", "before after comparison", "lime recommendation", "N P K status", "improvement report", or any analytical question about soil chemistry data.
livestock-tracker
by heldernoidTrack individual animals, record health events, vaccinations, weights, and breeding events. Use when asked to add an animal to the herd, log a vaccination, record body weight, track a treatment, set up a breeding event, check overdue vaccinations, or view the animal timeline. Triggers include "add animal", "record vaccination", "log weight", "track treatment", "breeding event", "overdue vaccines", "animal health history", "herd overview", or any task involving individual animal management.
progress-charts
by heldernoidRecharts-based WPM progress visualization for typing-trainer. Use when implementing or modifying the WPM over time chart, sessions per day bar chart, or any data visualization in the progress dashboard.
harvest-logger
by heldernoidLog crop harvests with yield quantity, quality grade, field, and storage destination. Use when asked to record a harvest, check total yield for a crop or field, filter harvest history by date or grade, view analytics charts, or export harvest data. Triggers include "log harvest", "record yield", "harvest entry", "crop yield", "grade breakdown", "field yield", "harvest history", or any task involving tracking what was picked and where it went.
jq-lite
by heldernoidPipe JSON into a query CLI with intuitive dot-notation syntax. Use when you need to extract fields from JSON, filter arrays, transform objects, or format JSON output. Triggers include "query JSON", "extract from JSON", "filter JSON array", "jq", "process JSON in shell", "parse API response", or any task involving JSON data manipulation in the terminal.
time-reports
by heldernoidGenerate time tracking reports from terminal-time-tracker data. Use when summarizing hours by project, comparing weeks, analyzing daily patterns, or exporting time data for invoicing. Triggers include "time report", "hours by project", "weekly summary", "time breakdown", "how long did I spend", "invoice export".
faker-templates
by heldernoidReference for Faker.js template helpers available in api-mock-server response body definitions. Use when building YAML config files for api-mock-server and you need to know which faker helpers are available, what they produce, or how to use dynamic values from request context.
api-mock
by heldernoidServe fake API responses from a YAML definition file with Faker.js data and configurable latency. Use when you need to develop a frontend without a backend, test error states, simulate slow APIs, or do contract-first API development. Triggers include "mock API", "fake backend", "stub API", "YAML mock server", "frontend without backend", "simulate API", "API contract testing".
qr-code-generator
by heldernoidGenerate QR codes via the web UI or REST API. Supports URL, WiFi, vCard, and plain text. Outputs SVG and PNG. Includes logo embedding and bulk CSV generation.
qr-api
by heldernoidREST API integration for qr-code-generator. TypeScript request helpers, batch pipeline patterns, and server-side code examples for embedding QR generation into other applications.
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.