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.
Querying local SQLite index...
commit-docs-updater
by 6529-CollectionsMaintain user-facing Markdown documentation in `/docs` using one commit as discovery input, while actively curating global docs information architecture. Organize docs into clear area-based folders, maintain navigable indexes, and keep content focused on current user-visible behavior only.
sonar-guardrails
by 6529-CollectionsUse before and after TypeScript edits to avoid predictable Sonar issues in this repository.
6529-autonomous-manager
by 6529-CollectionsOwn scoped 6529 frontend workstreams end to end. Use when Codex is asked to act as a manager, workstream owner, PR owner, review-feedback owner, release/staging/prod coordinator, ops/skills package owner, or autonomous implementation lead for the 6529seize frontend repository.
wcag-22-aa
by 6529-CollectionsAudit, implement, or review 6529 frontend accessibility work against WCAG 2.2 AA. Use when changing user-facing React UI, forms, dialogs, navigation, cards, tables, focus behavior, keyboard interactions, accessible names, color contrast, or PR feedback about accessibility.
react-doctor
by 6529-CollectionsRun the repo's React Doctor diff check after React, Next.js, JSX, TSX, hook, routing, or UI state changes. Use when reviewing React work, finishing a feature, fixing bugs, or checking changed files for security, performance, correctness, and architecture issues.
sonar-guardrails
by 6529-CollectionsReview TypeScript and JavaScript edits for predictable Sonar quality issues in this repository. Use before and after changing tests, mocks, parsing logic, helper functions, branching logic, or code likely to trigger Sonar complexity and correctness rules.
i18n-localization
by 6529-CollectionsImplement, audit, or review progressive 6529 frontend internationalization and localization work. Use when extracting user-facing copy, adding message dictionaries, locale-aware date or number formatting, translated accessible names, locale fallbacks, or PR feedback about i18n/l10n.
commit-docs-updater
by 6529-CollectionsMaintain user-facing Markdown documentation in `ops/docs` using one commit as discovery input, while actively curating global docs information architecture. Organize docs into clear area-based folders, maintain navigable indexes, and keep content focused on current user-visible behavior only.
write-prs
by 6529-CollectionsWrite, open, iterate, merge, and optionally deploy pull requests with clear PR descriptions, safe validation notes, review-bot follow-up, signed commits, staging or production deployment gates, and E2E verification. Use when preparing PR bodies, creating PRs, responding to CodeRabbit or Claude review bots, deciding whether a PR is ready, merging, or carrying a PR through staging/prod rollout.
api-skill
by 6529-CollectionsBuild or modify API endpoints in this repository by driving changes from openapi.yaml, regenerating API models and generated route wiring, implementing thin handlers, and wiring validation/auth/timing correctly. Use when creating new APIs, changing existing APIs, or updating API request/response models.
database-skill
by 6529-CollectionsImplement database-related changes in this repository, including schema changes via entities, repository/query patterns, transactions, and data migrations. Use when working on migrations, DB schema updates, or app logic that touches the database.
community-metrics
by 6529-CollectionsCreate new community metrics by adding enum values, recording functions, wiring, backfill migrations, and API integration. Use when adding new community metrics, creating metrics, or tracking community activity.
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.