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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interproscan-pipeline
by AGI4SciPredict protein domain families and functional annotation using InterProScan. Input a protein sequence and receive domain architecture, Gene Ontology (GO) terms, pathway annotations, and cross-references to protein databases including Pfam, SMART, PANTHER, and CDD.
pediatric-drug-safety
by AGI4SciPediatric Drug Safety Review - Evaluate pediatric drug safety: pediatric use information from FDA, child safety, dosage forms, and overdose information. Use this skill for pediatric pharmacology tasks involving get pediatric use info by drug name get child safety info by drug name get dosage forms and specs by drug name get overdose info by drug name. Combines 4 tools from 1 SCP server(s).
cancer-therapy-design
by AGI4SciDesign personalized cancer therapeutic strategies by integrating multi-omics data including genomics, transcriptomics, and proteomics for target identification, drug selection, and biomarker discovery.
enetic-counseling-report
by AGI4SciGenetic Counseling Report - Generate genetic counseling reports: variant interpretation, inheritance patterns, recurrence risks, and clinical recommendations. Use this skill for clinical genetics tasks involving interpret variants determine inheritance calculate recurrence recommend clinically. Combines 4 tools from 2 SCP server(s).
go-term-analysis
by AGI4SciPerform Gene Ontology enrichment analysis and functional annotation. Supports GO Slim mapping, pathway enrichment, and gene set analysis for genomics datasets.
phenotype-by-hpo-id
by AGI4SciRetrieve clinical phenotypes and associated genes using Human Phenotype Ontology (HPO) IDs.
epigenetics-drug
by AGI4SciEpigenetics Drug Analysis - Analyze epigenetic drugs: histone modification targeting, DNA methylation patterns, epigenetic enzyme inhibition, and chromatin remodeling. Use this skill for epigenomics tasks involving get histone targets get methylation patterns get enzyme inhibition get chromatin analysis. Combines 4 tools from 2 SCP server(s).
tcga-gene-expression
by AGI4SciQuery and analyze tumor gene expression profiles from The Cancer Genome Atlas (TCGA). Supports cohort-level expression lookup, tumor-versus-normal comparison, subtype stratification, and candidate biomarker exploration across cancer types.
molecular-visualization-suite
by AGI4SciMolecular Visualization Suite - Visualize molecules: SMILES to formats, molecular visualization, protein visualization, complex visualization. Use this skill for chemistry visualization tasks involving smiles to format visualize molecule visualize protein visualize complex. Combines 4 tools from 1 SCP server(s).
infectious-disease-analysis
by AGI4SciInfectious Disease Analysis - Analyze infectious diseases: pathogen identification, transmission tracking, antimicrobial resistance, and outbreak prediction. Use this skill for infectious disease tasks involving identify pathogens track transmission monitor resistance predict outbreaks. Combines 4 tools from 2 SCP server(s).
one-health-analysis
by AGI4SciOne Health Pathogen Analysis - One Health analysis: pathogen genomes, cross-species gene comparisons, antimicrobial drugs, and environmental context. Use this skill for one health tasks involving get genomic dataset report by taxonomy get homology symbol by drug name get mechanism of action get quick search get taxonomy. Combines 5 tools from 4 SCP server(s).
pandemic-preparedness
by AGI4SciPandemic Preparedness Analysis - Analyze pandemic preparedness: pathogen surveillance, transmission modeling, therapeutic development, and public health interventions. Use this skill for public health tasks involving monitor pathogens model transmission develop therapeutics plan interventions. Combines 4 tools from 2 SCP server(s).
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.