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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route-planning
by cxcscmuUse a distance matrix CSV to find travel time and distance between cities for self-driving trips.
aviation-weather
by bighardpersonFetch aviation weather data (METAR, TAF, PIREPs) from aviationweather.gov. Use for flight planning, weather briefings, checking airport conditions, or any pilot-related weather queries. Triggers on "METAR", "TAF", "flight weather", "airport weather", "aviation weather", "pilot report", "PIREP", or specific ICAO codes.
pilot-alert
by TeoSlayerConfigurable alerting on event patterns with webhook and message delivery. Use this skill when: 1. You need to trigger alerts based on event patterns or thresholds 2. You need to notify external services (Slack, Discord, PagerDuty) of events 3. You need to escalate critical events to on-call agents 4. You need to aggregate and deduplicate alerts Do NOT use this skill when: - You need simple event forwarding (use pilot-event-bus instead) - You need persistent logging (use pilot-event-log instead) - You need all events without filtering (subscribe directly)
pilot-auto-trust
by TeoSlayerAutomatic trust management with configurable policies for Pilot Protocol agents. Use this skill when: 1. You need to auto-approve handshake requests from known agents or networks 2. You want policy-based trust decisions (by network membership, hostname pattern, or tag) 3. You need to batch-process pending trust requests Do NOT use this skill when: - You need manual review of every trust request - You're dealing with unknown or potentially malicious agents - You need fine-grained per-agent trust policies
pilot-directory
by TeoSlayerLocal directory of known agents with cached metadata. Use this skill when: 1. Maintaining a persistent directory of frequently contacted agents 2. Caching agent metadata for offline reference 3. Building a local address book of trusted or favorite agents Do NOT use this skill when: - You need real-time network discovery (use pilot-discover instead) - You need to visualize relationships (use pilot-network-map instead) - You need to establish new trust (use pilot-trust instead)
pilot-health
by TeoSlayerNetwork health monitoring with latency and reachability checks. Use this skill when: 1. Diagnosing connectivity issues or high latency 2. Monitoring network health and performance metrics 3. Running continuous health checks for uptime monitoring Do NOT use this skill when: - You need to discover new agents (use pilot-discover instead) - You need to visualize topology (use pilot-network-map instead) - You need to establish connections (use pilot-connect instead)
pilot-role-assign
by TeoSlayerAssign and manage hierarchical roles within a swarm for coordinated task distribution. Use this skill when: 1. Agents need different responsibilities (leader, worker, coordinator) 2. You want capability-based role assignment (GPU workers, CPU workers) 3. You need dynamic role reassignment on failures or scaling events Do NOT use this skill when: - All agents are homogeneous (no role differentiation needed) - Roles are static and configured at startup (use tags)
pilot-sync
by TeoSlayerBidirectional file synchronization between agents over the Pilot Protocol network. Use this skill when: 1. You need to keep directories synchronized between two agents 2. You want to replicate files across multiple nodes with conflict detection 3. You need to maintain consistent file state across distributed agents Do NOT use this skill when: - You only need one-way file transfer (use pilot-share instead) - You need real-time streaming data (use pilot-stream-data instead) - Files are larger than 100MB without chunking support (use pilot-chunk-transfer)
search-cities
by jinchang1223List cities for a given state using the bundled background data. Use this skill to validate state inputs or expand destination choices before flight/restaurant/attraction/driving/accommodation lookups.
nzta-traffic
by GeorgeDoors888Query real-time NZ state highway traffic conditions from the Waka Kotahi NZTA Traffic and Travel API. Use when checking road events, incidents, closures, roadworks, traffic cameras, or travel conditions on New Zealand highways. Covers all 14 NZ regions (Northland to Southland). No API key required. Use for queries like "how's the traffic", "any road closures", "check SH1 conditions", or "traffic cameras near Wellington".
aviation-fuel-management
by WinbdaCreate aviation fuel management and optimization plans. TRIGGERS - Use when user needs help with aviation-fuel-management related tasks.
charter-operations-plan
by WinbdaPlan charter aviation operations. TRIGGERS - Use when user needs help with charter-operations-plan related tasks.
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.