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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jg-baseball-vendors
by 710425bryanVendor management workflow for jg-base-ball-community-app. Use when adding or changing 廠商名單、採購廠商、交易類別、`/vendors`、`vendors`、`vendor_trade_categories`、`src/services/vendorsApi.ts`、`src/stores/vendors.ts`、`src/components/vendors/*`、或 vendors storage/permission behavior.
jg-baseball-training
by 710425bryanTraining registration and player points workflow for jg-base-ball-community-app. Use when changing 特訓報名、球員點數、/training、training_session_settings、training_registrations、player_point_transactions、training_no_show_blocks、特訓點名、禁報、或 attendance_events.training_session_id 串接。
jg-baseball-training-locations
by 710425bryanTraining venue and player assignment workflow for jg-base-ball-community-app. Use when changing 場地與人員配置、/training-locations、training_venues、training_location_sessions、training_location_assignments、個人首頁本週訓練場地、或 send-training-location-notifications。
jg-baseball-training-dates
by 710425bryanMonthly training date settings workflow for jg-base-ball-community-app. Use when changing 訓練日期設定、/training-dates、training_month_date_settings、get_training_month_dates、save_training_month_dates、個人首頁本月訓練日期、或 send-training-date-notifications。
jg-baseball-roster-users-team-groups
by 710425bryanPlayer roster, users, profile binding, team groups, roster cache, sensitive member fields, and account access workflow for jg-base-ball-community-app. Use when changing PlayersView, UsersView, TeamGroupSettingsDialog, playerRoster store, teamGroups store, playerRosterApi, teamGroupsApi, profileAccess, team_members, team_members_safe, profiles, linked_team_member_ids, joined_date, team_group, app roles shown in roster/user flows, or sensitive fields national_id, guardian_phone, contact_line_id.
jg-baseball-push-notifications
by 710425bryanPush notification workflow for jg-base-ball-community-app. Use when adding or modifying web push delivery, recipient targeting, subscription handling, or event dedupe. Trigger on requests about 推播、手機通知、web push、`src/utils/pushNotifications.ts`、`supabase/functions/send-push-notification`、`push_dispatch_events`、`eventKey`、`web_push_subscriptions`、或通知權限控制。
jg-baseball-finance-payments
by 710425bryanFinance, fees, payment submissions, player balances, match fees, remittance ingestion, and finance reminder workflow for jg-base-ball-community-app. Use when changing /fees, /my-payments, src/components/fees/*, src/services/myPayments.ts, src/services/playerBalances.ts, src/services/matchFees.ts, feeManagementReminders, monthly_fees, quarterly_fees, profile_payment_submissions, match_fee_items, match_payment_submissions, player_balance_transactions, record-fee-remittance, or Google Form remittance scripts.
jg-baseball-player-sync
by 710425bryanPlayer roster sync workflow for jg-base-ball-community-app. Use when changing Google Form or Google Sheet player sync, roster imports, deduplication, fee flag handling, or member upsert behavior. Trigger on requests about 球員同步、Google 表單、Google Sheet、名單匯入、`src/utils/playerSync.ts`、`team_members`、`is_primary_payer`、`is_half_price`、或 sync dedupe 規則。
jg-baseball-performance-data
by 710425bryan棒球能力與體能測驗數據 workflow for jg-base-ball-community-app. Use when changing `/baseball-ability`, `/physical-tests`, performance data tables/RPC/RLS, trend views, manual CRUD forms, or permissions `baseball_ability` / `physical_tests`.
jg-baseball-match-records-media
by 710425bryanMatch records, schedule detail, lineup, media, live controller, audio transcription, lineup photo parsing, weather, geocoding, and match reminder workflow for jg-base-ball-community-app. Use when changing /calendar, /match-records, /my-records match detail behavior, matchesApi, match-records components, MatchFormDialog, MatchDetailDialog, MatchLineupTab, MatchAudioRecorder, MatchLiveController, parse-lineup, transcribe-match-audio, resolve-location, weatherApi, matches-photos storage, match reminders, or match media utilities.
jg-baseball-auth-permissions
by 710425bryanRole-based auth and permission workflow for jg-base-ball-community-app. Use when adding or changing protected routes, page visibility, action buttons, role checks, login behavior, router meta, or sensitive data access. Trigger on requests about 權限、角色、登入、路由守衛、`src/router/index.ts`、`src/stores/auth.ts`、`src/stores/permissions.ts`、`app_role_permissions`、或 feature/action 控制。
jg-baseball-match-calendar-sync
by 710425bryanMatch calendar sync workflow for jg-base-ball-community-app. Use when changing Google Calendar or iCal parsing, match import or update rules, sync planning, or `google_calendar_event_id` fallback behavior. Trigger on requests about 賽事同步、Google 行事曆、iCal、比賽匯入、`src/utils/googleCalendarParser.ts`、`src/services/matchesApi.ts`、`google_calendar_event_id`、或 MatchRecords sync UI。
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.