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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literature-discovery
by MoxyWolfLLCMulti-source literature discovery across academic and non-academic sources. Can be the FIRST step in a research project — give it a topic and it creates the library from scratch. Searches OpenAlex, Semantic Scholar, arXiv, and the general web (blogs, whitepapers, NIST docs, vendor publications, industry reports). Use this skill whenever the user says "research this topic," "find papers on," "discover literature," "I want to research," "find sources about," "what's been written about," "build me a bibliography," "start researching," "find more papers," "expand my bibliography," "what am I missing," "find related work," "literature search," "fill research gaps," or any request to search for literature — academic or otherwise — on a topic. This is the recommended ENTRY POINT for new research projects. Also trigger when gap analysis results suggest missing coverage areas, or when the user gives a topic without specifying what to do with it.
discourse-sweep
by MoxyWolfLLCThis skill should be used when running the 30-day discourse sweep step of the 4D Blog Engine — Phase 3 (Discernment). It fires platform-targeted queries across reddit, X, Hacker News, Substack, dev.to, github, linkedin.com/pulse, Facebook, Quora, podcasts (Apify), and academic sources (research-pipeline/literature-discovery), then ranks the findings via combined_score = relevance×0.6 + recency×0.4, dedupes by 70% title-overlap, applies cross-source clustering, and writes a discourse.md to the piece's 03-discernment/ folder. Triggers: "/4d-blog-engine:blog-discern", "run the 30-day sweep", "sweep the discourse on", "what's the world saying about <topic>", "research the last 30 days for <topic>". This is a specialist skill — invoked by the 4d-blog-engine orchestrator, not directly by the user in normal usage.
session-end
by MoxyWolfLLCThis skill should be used when the user says "session-end", "end session", "wrap session", "save handoff", "/session-end", "we're done", "sign off", or any request to wrap up a Cowork session and persist what was done plus what's next for the following session. It scans the conversation for what landed, what's still open, and the commit/push state of the active repo(s), asks who authored this handoff and whether it's a baton-pass to a teammate, then writes a canonical-named handoff document (with `author` and optional `for` frontmatter fields auto-populated) to the project's `00 – Project Hub/cowork-session-handoff.md`. Supports `--author=<name>`, `--handoff-to=<name>`, and `--solo` flags to skip the prompts. Step 5c keeps each writable GitHub repo's README.md current against the canonical 16-section structure. The companion `/session-start` skill reads the handoff file to brief next-session Claude.
sorkin-dob-weekly-blog
by MoxyWolfLLCTransform weekly STIG+CMMC research into narrative-driven blog posts using Aaron Sorkin's Desire-Obstacle-Battle storytelling framework with MoxyWolf brand voice. Use when Dorian provides weekly research structured in acts with bracketed citations that needs conversion to publication-ready blog content for STIGViewer's technical audience. Creates visceral, human-authentic prose that engages readers emotionally while maintaining technical precision.
4d-blog-engine
by MoxyWolfLLCThis skill should be used when the user asks to "write a blog post from this document", "derive a blog from this whitepaper / report / transcript / meeting notes", "run the 4D pipeline on this", "write a LinkedIn article + teaser from this", "make a Twitter thread from this blog", "write a Facebook post from my blog", "run the release-owner gate on my draft", or any request to turn a base document into a publication-ready blog post (and optional multi-platform social derivatives) under the 4D AI Fluency Framework. This skill is the orchestrator — it routes to the four phase commands (blog-delegate, blog-describe, blog-discern, blog-diligence), the social derivative command (blog-social), and the lifecycle commands. It is also the central place that detects the active Cowork project and computes the per-piece working directory. Trigger aggressively for anything touching deriving a blog from a base doc, the 4D framework, the Release Owner Gate, or producing multi-platform social derivatives. Do NOT use this ski
tax-season-organizer
by MoxyWolfLLCPrepares tax-season materials for small business owners — framed as deliverables for their accountant, not tax advice. Two modes: (1) quarterly estimated tax calculation — pulls YTD net income from QuickBooks and calculates the federal income tax + self-employment tax liability and quarterly payment due; (2) year-end 1099 prep — scans QuickBooks, Stripe for contractors paid over $600, builds a 1099-NEC candidate list with missing W-9 flags, and produces a plain-English summary a CPA can work from directly. Trigger this skill whenever the user mentions: quarterly taxes, estimated tax payment, how much to set aside for taxes, 1099s, 1099-NEC, year-end tax prep, contractor payments, W-9s, or any phrase suggesting they are preparing for a tax deadline or handing materials to an accountant. Also trigger proactively when a user asks about net profit or YTD income in a context that suggests they are worried about their tax bill.
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.