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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mulesoft-flow
by Mrsavage92MuleSoft flow construction expert. Covers flow structure (flow vs sub-flow vs private flow), triggers (Scheduler, Listener, Object Store watermark), processors (Transform, Logger, Choice, Scatter-Gather), error handling (On Error Propagate vs Continue, retry, DLQ), batch jobs, idempotency, and watermarking patterns. Use when building any integration flow, debugging flow behaviour, or adding error handling to existing flows.
mulesoft-dataweave
by Mrsavage92DataWeave 2.0 transformation expert for MuleSoft. Covers syntax (types, variables, functions), common patterns (object map, filter, reduce, groupBy), format handling (JSON/XML/CSV/Java/Form), field mapping between systems (NS ↔ SF ↔ DB), watermark logic, date/time manipulation, and error-safe defaults. Use when writing any ee:transform, debugging a DataWeave script, or mapping fields between source and target systems.
mulesoft-connector
by Mrsavage92MuleSoft connector configuration expert for Salesforce, NetSuite, HTTP, Database, JMS, FTP/SFTP, and File connectors. Covers authentication patterns (OAuth Username-Password, OAuth JWT Bearer, OAuth Client Credentials, TBA, Basic Auth), global config structure, property-file integration, environment promotion, and Secrets Manager references. Use when setting up a new connection, debugging a connection test failure, or upgrading auth from dev to production.
mulesoft-bdr
by Mrsavage92BDR Group MuleSoft integration project tracker. Reads the Implementation Playbook, tracks phase progress (0A→0B→0C→1A→1B→1C), flags blockers by owner (Ben/Anil/Dave/Julie/Ryan/Nikith), maintains credential state, generates stakeholder status updates. Use whenever Adam asks about BDR MuleSoft status, blockers, next steps, or phase gates. NOT for generic MuleSoft work — use /mulesoft or subskills for that.
mulesoft
by Mrsavage92MuleSoft integration suite orchestrator. Routes MuleSoft work to the right specialist subskill — connector config, flow construction, DataWeave transforms, platform ops, or BDR project tracking. Use as entry point when a MuleSoft request spans multiple areas or when not sure which subskill fits. NOT for a single narrow task — use the specific subskill directly.
mulesoft-platform
by Mrsavage92Anypoint Platform operations expert. Covers Runtime Manager (deploying, monitoring, alerts), Secrets Manager, Exchange (assets, templates), environment promotion (Design → Sandbox → Production), Access Management (roles, permissions), vCore allocation, Object Store, Runtime Fabric, and CI/CD via Maven. Use for any platform admin task, deployment, monitoring setup, or governance configuration.
techaudit-speed
by Mrsavage92Deep page speed analysis mapping render-blocking resources, unoptimised assets, and third-party script impact. Produces a prioritised optimisation plan with estimated load time improvements.
techaudit-speed
by Mrsavage92Deep page speed analysis mapping render-blocking resources, unoptimised assets, and third-party script impact. Produces a prioritised optimisation plan with estimated load time improvements.
audithq-convert
by Mrsavage92AuditHQ inbound conversion — the Day 0/3/7/14 email drip after free-scan email capture, free-to-paid upgrade nudges anchored on the visible 3-suite→9-suite gap, and result-page CRO. Owns the AuditHQ funnel logic; delegates email copy to market-emails, page copy to market-copy, and layout CRO to page-cro. Triggers: 'convert free scan visitors', 'drip email sequence', 'Day 0 email', 'Day 3 email', 'email capture on result page', 'free to paid upgrade', 'upgrade nudge', 'result page CRO', 'nurture the free scan leads', 'inbound email sequence', 'how do I convert the quick scan users'. NOT for: finding and contacting new prospects (use audithq-outbound); activating the n8n send pipeline (use audithq-pipeline); generic email sequences unrelated to AuditHQ (use market-emails).
research-summarizer
by Mrsavage92Structured research summarization agent skill for non-dev users. Handles academic papers, web articles, reports, and documentation. Extracts key findings, generates comparative analyses, and produces properly formatted citations. Use when: user wants to summarize a research paper, compare multiple sources, extract citations from documents, or create structured research briefs. Plugin for Claude Code, Codex, Gemini CLI, and OpenClaw.
agent-workflow-designer
by Mrsavage92Design multi-agent AI systems, task decomposition trees, and LLM coordination patterns. Use when architecting agent pipelines, planning multi-step AI workflows, or deciding how subagents should collaborate on a complex task.
overdrive
by Mrsavage92Pushes interfaces past conventional limits with technically ambitious implementations — shaders, spring physics, scroll-driven reveals, 60fps animations. Use when the user wants to wow, impress, go all-out, or make something that feels extraordinary.
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.