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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plant-care-plan
by zocomputerCreates a comprehensive care guide for your specific plant
make-fire
by pjt222Start and maintain a fire using friction, spark, and solar methods. Covers site selection, material grading (tinder/kindling/fuel), fire lay construction (teepee, log cabin, platform), ignition techniques (ferro rod, flint & steel, bow drill), flame nurturing, and Leave No Trace extinguishing. Use when needing warmth, light, or a signal in a wilderness setting, when boiling water for purification, when cooking foraged food, or in an emergency survival situation requiring heat or morale support.
maintain-hand-tools
by pjt222Maintain the 8 essential garden hand tools through sharpening, handle care, rust prevention, and seasonal storage. Covers bypass secateurs, hori-hori, hand fork, trowel, pruning saw, sharpening stone, watering can, and soil rake. Use after each garden session for quick cleaning, monthly during the growing season for sharpening and oiling, at end of season for winter storage preparation, before spring for pre-season readiness checks, or whenever a tool feels dull, stiff, or shows rust.
cultivate-bonsai
by pjt222Bonsai-Baeume von der Artenauswahl bis zur langfristigen saisonalen Pflege kultivieren. Umfasst Arteneignung, Struktur- und Erhaltungsschnitt, Drahttechnik, Umtopfprotokoll, Substratmischungsvorbereitung, saisonale Pflegeplaene und kontemplative Sitzpraxis. Verwenden beim Auswaehlen einer Art fuer einen ersten oder naechsten Bonsai, beim Durchfuehren von Struktur- oder Erhaltungsschnitt, beim Umtopfen wenn Wurzeln kreisen oder das Wachstum stagniert, beim Drahten von Aesten zur Formgebung, beim Entwickeln eines saisonalen Pflegekalenders oder beim Aufbauen einer kontemplativen Praxis mit einem lebenden Baum.
maintain-hand-tools
by pjt222Die 8 essentiellen Gartenhandwerkzeuge durch Schaerfen, Griffpflege, Rostvorbeugung und saisonale Lagerung warten. Umfasst Bypass-Gartenschere, Hori-Hori, Handgabel, Pflanzkelle, Astsaege, Schleifstein, Giesskanne und Bodenrechen. Anwenden nach jeder Gartensitzung fuer schnelle Reinigung, monatlich waehrend der Wachstumssaison zum Schaerfen und Oelen, am Saisonende zur Winterlagerungsvorbereitung, vor dem Fruehling zur Bereitschaftspruefung oder wann immer ein Werkzeug stumpf oder rostig wirkt.
make-fire
by pjt222Feuer entzünden und aufrechterhalten mit Streichhölzern, Feuerstahl oder Reibungsmethoden. Umfasst Standortwahl und -vorbereitung, Materialsammlung (Zunder, Anzündholz, Brennholz), Aufbau des Feuerbetts, Zündmethoden, Pflege der Flamme, Aufbau eines stabilen Feuers und sicheres Löschen. Verwenden, wenn Wärme, Kochen, Wasseraufbereitung, Signalgebung oder psychologischer Komfort in einer Wildnissituation benötigt werden.
read-garden
by pjt222Einen Garten mittels eines strukturierten sensorischen Protokolls beobachten und bewerten, adaptiert von Coordinate Remote Viewing. Umfasst Vor-Eingangs-Klaerung (Meditate-Checkpoint), Stufe-I-Gesamteindruck, Stufe-II-Sinnesschicht (Blatt, Stiel, Wurzel, Boden), Stufe-III-Mustererkennung mit AOL-Management und Gartengesundheits- Triagematrix (Heal-Checkpoint). Anwenden vor jeder Intervention, wenn Pflanzen Stresssymptome zeigen, bei saisonalen Uebergaengen, bei der Bewertung eines neuen Gartenstandorts, waehrend regelmaessiger Gesundheitsueberwachung oder nach extremen Wetterereignissen wie Frost oder Hitzewellen.
maintain-hand-tools
by pjt222Maintain the 8 essential garden hand tools through sharpening, handle care, rust prevention, and seasonal storage. Covers bypass secateurs, hori-hori, hand fork, trowel, pruning saw, sharpening stone, watering can, and soil rake. Use after each garden session for quick cleaning, monthly during the growing season for sharpening and oiling, at end of season for winter storage preparation, before spring for pre-season readiness checks, or whenever a tool feels dull, stiff, or shows rust.
read-garden
by pjt222Observe and assess a garden using a structured sensory protocol adapted from Coordinate Remote Viewing. Covers pre-entry clearing (meditate checkpoint), Stage I gestalt impression, Stage II sensory layer (leaf, stem, root, soil), Stage III pattern recognition with AOL management, and garden health triage matrix (heal checkpoint). Use before any intervention, when plants show stress symptoms, at seasonal transitions, when evaluating a new garden site, during regular health monitoring, or after extreme weather events such as frost or heat waves.
maintain-hand-tools
by pjt222Maintain the 8 essential garden hand tools through sharpening, handle care, rust prevention, and seasonal storage. Covers bypass secateurs, hori-hori, hand fork, trowel, pruning saw, sharpening stone, watering can, and soil rake. Use after each garden session for quick cleaning, monthly during the growing season for sharpening and oiling, at end of season for winter storage preparation, before spring for pre-season readiness checks, or whenever a tool feels dull, stiff, or shows rust.
prepare-soil
by pjt222Assess and improve garden soil through testing, amendment, composting, and biodynamic preparations. Covers jar test, spade test, earthworm count, amendment by soil type (clay, sandy, depleted, compacted), composting methods (hot, cold, vermicomposting), no-till practices, cover cropping, and biodynamic preparations 500-508. Use when starting a new garden bed, when plants underperform despite adequate water and light, when transitioning to organic or biodynamic practice, when soil has become compacted or depleted, or when building a composting system.
read-garden
by pjt222座標遠隔視聴（CRV）から適応した構造化感覚プロトコルを用いて庭を観察・ 評価する。入園前のクリアリング（meditate チェックポイント）、ステージI ゲシュタルト印象、ステージII感覚レイヤー（葉、茎、根、土壌）、ステージIII AOL管理付きパターン認識、庭の健康トリアージマトリックス（heal チェック ポイント）を網羅。あらゆる介入の前、植物がストレス症状を示す場合、季節の 移行時、新しい庭のサイト評価時、定期的な健康モニタリング中、霜や熱波などの 極端な天候イベント後に使用。
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.