381,784 Collected SKILL.md files

Explore AI Agent Skills & Claude Prompts

Discover open-source agent skills for Claude Code, Codex, ChatGPT, and any tool that uses SKILL.md.

search
expand_more
Active:
finsilabs
Showing 12 of 73 skills
finsilabs

subscription-billing

by finsilabs
star 29

Sell recurring subscriptions with automated billing, dunning emails for failed payments, plan upgrade/downgrade prorations, and self-serve cancellation

navigation main article SKILL.md
schedule Updated 3 months ago
finsilabs

accounts-receivable-automation

by finsilabs
star 29

Automate B2B accounts receivable with invoice generation, payment tracking, dunning sequences for past-due invoices, and aging analysis dashboards

navigation main article SKILL.md
schedule Updated 3 months ago
finsilabs

woocommerce-performance

by finsilabs
star 29

Fix slow WooCommerce stores by optimizing database queries, clearing transients, enabling Redis object caching, and configuring page caching

navigation main article SKILL.md
schedule Updated 3 months ago
finsilabs

woocommerce-subscriptions

by finsilabs
star 29

Add subscription products to WooCommerce with automatic recurring billing, renewal notifications, and subscriber self-service management

navigation main article SKILL.md
schedule Updated 3 months ago
finsilabs

woocommerce-rest-api

by finsilabs
star 29

Integrate or build headless frontends on WooCommerce using its REST API for products, orders, customers, and coupons with key authentication

navigation main article SKILL.md
schedule Updated 3 months ago
finsilabs

woocommerce-plugin-development

by finsilabs
star 29

Create custom WooCommerce plugins using action/filter hooks, the Settings API, and REST API extensions to add features without modifying core

navigation main article SKILL.md
schedule Updated 3 months ago
finsilabs

woocommerce-blocks

by finsilabs
star 29

Customize WooCommerce checkout and cart pages using Gutenberg blocks with server-side rendering, slot-fills, and extensibility hooks

navigation main article SKILL.md
schedule Updated 3 months ago
finsilabs

gift-cards

by finsilabs
star 29

Sell and accept gift cards with secure code generation, real-time balance tracking, partial redemption support, and expiration enforcement

navigation main article SKILL.md
schedule Updated 3 months ago
finsilabs

win-back-reactivation

by finsilabs
star 29

Re-engage lapsed customers with automated win-back campaigns using personalized comeback offers based on purchase history and inactivity windows

navigation main article SKILL.md
schedule Updated 3 months ago
finsilabs

erp-integration

by finsilabs
star 29

Sync orders, inventory, and customer data between your store and ERP systems like SAP, NetSuite, or Odoo using middleware and async queues

navigation main article SKILL.md
schedule Updated 3 months ago
finsilabs

guest-checkout

by finsilabs
star 29

Allow shoppers to buy without creating an account, then invite them to save their details post-purchase to reduce checkout friction and increase conversion

navigation main article SKILL.md
schedule Updated 3 months ago
finsilabs

ugc-campaign-management

by finsilabs
star 29

Source, curate, and display user-generated content at scale with rights management, brand safety moderation, and trust-building social proof galleries

navigation main article SKILL.md
schedule Updated 3 months ago
Page 1 of 7

Browse Agent Skills by Occupation

23 major groups · 867 SOC occupations

Browse by Category

Explore agent skills organized by their primary use case

SKILLMD / CREATORS AND OCCUPATION CATEGORIES

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.

SEO KNOWLEDGE HUB & TECHNICAL OVERVIEW

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.

8 QUESTIONS

Frequently Asked Questions

A practical guide to agent skills: what they are, how to inspect them, and how SkillMD helps you explore the ecosystem.