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...
coding-tutor
by AojdevStudioPersonalized coding tutorials that build on your existing knowledge and use your actual codebase for examples. Creates a persistent learning trail that compounds over time using the power of AI, spaced repetition and quizes.
opentui
by AojdevStudioComprehensive OpenTUI skill for building terminal user interfaces. Covers the core imperative API, React reconciler, and Solid reconciler. Use for any TUI development task including components, layout, keyboard handling, animations, and testing.
fin-guru-compliance-review
by AojdevStudioExecute comprehensive compliance reviews for Finance Guru deliverables. Validates disclaimers, data handling, risk disclosures, and regulatory positioning.
fin-guru-quant-analysis
by AojdevStudioPerform quantitative analysis of returns, correlations, risk factors, and portfolio optimization. Statistical modeling with institutional-grade rigor.
montecarlo
by AojdevStudioRun Monte Carlo simulations for Finance Guru portfolio strategy. USE WHEN user mentions monte carlo OR run simulation OR stress test portfolio OR probability analysis OR income projections OR margin safety analysis. Supports 4-layer portfolio (Growth, Income, Hedge, GOOGL) with auto-detection of current values from Fidelity CSV.
dividend-tracking
by AojdevStudioSync dividend data from Fidelity CSV to Dividends sheet. Reads dividend.csv from notebooks/updates/, calculates actual dividends received (shares × amount per share), writes to input area (rows 2-46), then clicks Add Dividend button to process. Triggers on sync dividends, update dividends, dividend tracker, layer 2 income, or monthly dividend analysis.
fin-core
by AojdevStudioFinance Guru™ Core Context Loader Auto-loads essential Finance Guru system configuration and user profile at session start. Ensures complete context availability for all financial operations.
fin-guru-learner-profile
by AojdevStudioBuild and manage learner profiles for Finance Guru teaching and onboarding. Progressive profiling with ADHD-aware assessment and personalized learning paths.
margin-management
by AojdevStudioUpdate Margin Dashboard with Fidelity balance data and calculate margin-living strategy metrics. Monitors margin balance, interest costs, coverage ratios, and scaling thresholds. Triggers safety alerts for large draws and provides time-based scaling recommendations. Use when updating margin, balances, coverage ratio, or margin strategy analysis.
portfoliosyncing
by AojdevStudioImport and sync broker CSV portfolio data to Google Sheets DataHub. Supports Fidelity (automated) with multi-broker planned. USE WHEN user mentions import broker data OR sync portfolio OR update positions OR CSV import OR portfolio-sync OR ingest positions OR bring in positions OR downloaded from Fidelity OR working with Portfolio_Positions CSVs. Handles file ingestion from Downloads, position updates, SPAXX/margin validation, safety checks, and formula protection.
retirement-syncing
by AojdevStudioSync retirement account data from Vanguard and Fidelity CSV exports to Google Sheets DataHub. Handles multiple accounts, aggregates holdings by ticker, and updates quantities in retirement section (rows 46-62). Triggers on sync retirement, update retirement, vanguard sync, 401k update, IRA sync, or working with notebooks/retirement-accounts/ files.
formula-protection
by AojdevStudioPrevent accidental modification of sacred spreadsheet formulas in Google Sheets Portfolio Tracker. Blocks edits to GOOGLEFINANCE formulas, calculated columns, and total rows. Allows only IFERROR wrappers, fixing broken references, and expanding ranges. Triggers on update formula, modify column, fix errors, or any attempt to edit formula-based cells.
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.