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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browser-use
by jxxghpUse this skill when the user asks the agent to open, browse, inspect, extract content from, click through, fill forms on, screenshot, or verify a web page with a browser. Also use it for MoviePilot scenarios that need browser interaction, such as checking a site page, confirming a JavaScript-rendered result, testing login state, capturing visible errors, or updating and validating tracker site cookies.
database-operation
by jxxghpUse this skill when you need to execute SQL against the MoviePilot database. This skill guides you through connecting to the database and executing SQL statements. The database type (SQLite or PostgreSQL) and connection details are provided in the system prompt <system_info>. Applicable scenarios include: 1) The user asks about data statistics, counts, or aggregations that existing tools don't cover; 2) The user wants to inspect, modify, or fix raw database records; 3) The user asks to clean up data, update records, or perform database maintenance; 4) The user asks questions like "how many downloads", "show me site stats", "delete old records", etc.
feedback-issue
by jxxghpUse this skill ONLY when the user EXPLICITLY requests filing an upstream issue for MoviePilot core, frontend, or an installed plugin, for example "反馈 issue", "提 issue", "报 bug", "给 MP 提 issue", "让上游修一下", "提交错误报告", "提需求", "功能请求", or English "file an issue / report a bug / open an upstream issue / feature request". A bare problem report is not enough: diagnose locally first. This skill uses its own scripts under `scripts/`; it does not add or call dedicated Agent tools for collect / prepare / submit.
generate-identifiers
by jxxghpUse this skill when a user provides a torrent name or file name and wants to fix recognition issues, or asks to add/manage custom identifiers (自定义识别词). This skill generates identifier rules based on the WordsMatcher preprocessing logic, checks for duplicates against existing rules, and saves them via MCP tools. Because custom identifiers are global, generated rules must default to conservative, sample-specific regex patterns instead of broad matches unless the user explicitly wants global cleanup. Applicable scenarios include: 1) A torrent or file name is incorrectly recognized (wrong title, season, episode, etc.); 2) The user wants to block unwanted keywords from torrent names; 3) The user needs episode offset rules for series with non-standard numbering; 4) The user wants to force recognition of a specific media by TMDB/Douban ID; 5) The user wants TV recognition to use a specific TMDB episode group.
moviepilot-api
by jxxghpUse this skill when you need to call MoviePilot REST API endpoints directly. Covers all 245 API endpoints across 27 categories including media search, downloads, subscriptions, library management, site management, system administration, plugins, workflows, and more. Use this skill whenever the user asks to interact with MoviePilot via its HTTP API, or when the moviepilot-cli skill cannot cover a specific operation.
moviepilot-update
by jxxghpUse this skill when you need to check MoviePilot versions, restart MoviePilot, or trigger a MoviePilot upgrade. Prefer the built-in system APIs instead of docker commands or manual file replacement. If auto-update on restart is already enabled, just restart. If it is disabled, call the upgrade API so MoviePilot performs a one-shot upgrade and restart.
moviepilot-cli
by jxxghpUse this skill for any request involving movies, TV shows, or anime, including searching, downloads, subscriptions, library management. Also use this skill whenever the user explicitly mentions MoviePilot.
transfer-failed-retry
by jxxghpUse this skill when you need to retry failed file transfers/organizations. Given one or more failed transfer history record IDs, this skill guides you through querying the failure details, deleting the old records, and re-identifying and re-organizing the files. Supports batch processing of multiple files from the same media (e.g., multiple episodes of a TV show). This skill is automatically triggered when the system detects transfer failures and the AI agent retry feature is enabled.
command-dispatch
by jxxghpUse this skill when the user's intent is to execute a system or plugin function. Applicable scenarios include: 1) The user sends a slash command starting with / (e.g. /cookiecloud, /sites, /subscribes, etc.); 2) The user describes an action in natural language that can be fulfilled by a system or plugin command (e.g. "sync sites", "show subscriptions", "refresh subscriptions", "check downloads", etc.). This skill helps you identify the user's intent, find the matching command, extract necessary parameters, and execute the corresponding command.
create-moviepilot-skill
by jxxghpUse this skill when the user asks to create, scaffold, update, or review a MoviePilot agent skill. This includes adding a new built-in skill under the repository `skills/` directory, editing an existing built-in skill, writing `SKILL.md` frontmatter and workflow instructions, choosing `allowed-tools`, adding helper scripts when needed, and bumping the built-in skill `version` so changes can sync into `config/agent/skills`.
create-moviepilot-plugin
by jxxghpUse this skill when the user asks to create, modify, debug, validate, or scaffold a MoviePilot local plugin. Covers MoviePilot V2 plugin development, _PluginBase implementations, package.v2.json/package.json market metadata, plugins.v2/plugins source layout, PLUGIN_LOCAL_REPO_PATHS local plugin sources, plugin APIs, Vuetify JSON forms/pages/dashboards, Vue module federation remote components, get_render_mode, get_sidebar_nav, plugin sidebar pages, commands, services, workflow actions, agent tools, and local install/reload flows. Also use for Chinese requests mentioning 编写插件、本地插件源, 插件开发, V2插件, 插件市场, 本地安装插件, 插件热加载, 前端联邦, 侧栏入口, Vue插件页面.
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.