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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tanstack-ai
by JeromyJSmithProvider-agnostic, type-safe AI SDK for streaming, tool calling, structured output, and multimodal content.
embodied-navigation
by JeromyJSmithTransfer embodied movement principles (Vipassana equanimous scanning, Systema adaptive fluidity, contemporary dance tensegrity, EightOS confluence) to navigate work, relationships, projects, strategy, and everyday situations. Uses InfraNodus MCP tools to map situations as networks and apply body-informed intelligence to their structure. Trigger when someone is stuck, in conflict, negotiating, blocked, fixated, overwhelmed, or facing rigidity — or asks for "embodied advice", "fluid approach", "organic strategy", "adaptive strategy", "how would the body handle this". Also trigger on phrases like "I'm stuck", "standoff", "tense situation", "can't move forward". Apply proactively when situations exhibit excessive force, single-point fixation, or neglect of peripheral dynamics.
cognitive-variability
by JeromyJSmithGuide conversations through dynamic shifts between zoom levels (scale) and connecting/exploring (intent) to unlock creative breakthroughs and prevent rigid thinking. Helps enhance and develop biased, focused, diversified, dispersed states. Receives signals from writing assistant's pattern detection to diagnose cognitive states. Identifies structural gaps between idea clusters as spaces for innovation. Tracks temporal dwelling patterns and manages energy across personality modes. Uses playfulness for difficult transitions from chaos to clarity. Reads emotional feedback—inspiration signals continuation, exhaustion/frustration trigger transitions. Prevents obsessive loops through sustainable cycling through topical clusters and latent nodes. Maximum creative potential lives in gaps and dissipative states. Apply for complex analysis, when a user is stuck, breakthroughs, decision paralysis, group facilitation, breaking repetitive patterns, or when grammatical patterns reveal cognitive issues.
rhetorical-analyst
by JeromyJSmithAnalyze arguments, debate tactics, and rhetorical moves across three dimensions: persuasion, rhetoric, and logic. Use when the user wants to analyze a debate, comment thread, speech, article, or any argumentative text — identifying moves, scoring effectiveness, exposing hidden assumptions, tracking logical gaps, and checking for asymmetric standards. When InfraNodus MCP tools are available, ALWAYS begin with generate_topical_clusters, generate_content_gaps, and optimize_text_structure before linear reading. Also use to stress-test arguments or understand why something feels persuasive but wrong. Trigger on: "analyze this argument", "what's wrong with this reasoning", "is this a good point", "what rhetorical moves are being used", "why is this persuasive", "break down this debate", or when a user shares text asking what's going on rhetorically.
graphify-introduction
by JeromyJSmithLATTICE codebase graph introduction — communities, hotspots, dependency paths for VW_iTwin_Bridge
graphify-introduction
by JeromyJSmithLATTICE codebase graph introduction — communities, hotspots, dependency paths for VW_iTwin_Bridge
vipassana-llm
by JeromyJSmithApply Vipassana meditation principles to LLM processing — equanimous scanning, non-reactive observation, impermanence awareness (anicca), and breaking the sankhara chain of conditioned reactions. Trigger on "meditate on", "observe without reacting", "see clearly", "practice vipassana", "scan equanimously", "what's really going on here", "non-reactive analysis", "observe without judgment". Also trigger when the user wants bare attention rather than jumping to conclusions, wants to dissolve fixation loops, or asks Codex to apply contemplative processing. Apply proactively when conversations show reactive thinking, craving for particular outcomes, or aversion to uncomfortable truths. Synergizes with cognitive-variability, embodied-navigation, and shifting-perspective skills.
marimo-pair
by JeromyJSmithWork inside a running marimo notebook's kernel — execute code, create cells, and build a notebook as an artifact. Use when the user wants to start a marimo notebook or work in an active marimo session.
livekit-voice
by JeromyJSmithLiveKit voice agent setup — room management, token generation, voice pipelines with STT/TTS, and real-time audio streaming.
modern-python
by JeromyJSmithConfigures Python projects with modern tooling (uv, ruff, ty). Use when creating projects, writing standalone scripts, or migrating from pip/Poetry/mypy/black.
1brc-electron
by JeromyJSmithReference codebase for 1brc Electron. Use this skill when you need to understand the structure, implementation patterns, or code details of the 1brc Electron project.
let-fate-decide
by JeromyJSmithDraws 4 Tarot cards to inject entropy into planning when prompts are vague, ambiguous, or casually delegated. Interprets the spread to guide next steps. Use when the user says 'let fate decide', 'YOLO', 'whatever', 'idk', or other nonchalant phrases, makes Yu-Gi-Oh references, or when you are about to arbitrarily pick between multiple reasonable approaches. Prefer over ask-questions-if-underspecified when the user's tone is casual or playful rather than precision-seeking.
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.