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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skillshare-update-docs
by runkidsUpdate website docs to match recent code changes, cross-validating every flag against source. Use this skill whenever the user asks to: update documentation, sync docs with code, document a new flag or command, fix stale docs, or update the README. This skill covers all website/docs/ categories (commands, reference, understand, how-to, troubleshooting, getting-started) plus the built-in skill description and README. If you just implemented a feature and need to update docs, this is the skill to use. Never manually edit website docs without cross-validating flags against Go source first.
skillshare-implement-feature
by runkidsImplement a feature from a spec file or description using TDD workflow. Use this skill whenever the user asks to: add a new CLI command, implement a feature from a spec, build new functionality, add a flag, create a new internal package, or write Go code for skillshare. This skill enforces test-first development, proper handler split conventions, oplog instrumentation, and dual-mode (global/project) patterns. If the request involves writing Go code and tests, use this skill — even if the user doesn't explicitly say "implement".
skillshare
by runkidsManages and syncs AI CLI skills and agents across 50+ tools from a single source. Use this skill whenever the user mentions "skillshare", runs skillshare commands, manages skills or agents (install, update, uninstall, sync, commit, audit, analyze, check, diff, search), or troubleshoots skill/agent configuration (orphaned symlinks, broken targets, sync issues). Covers both global (~/.config/skillshare/) and project (.skillshare/) modes. Also use when: adding new AI tool targets (Claude, Cursor, Windsurf, etc.), setting target include/exclude filters or copy vs symlink mode, using backup/restore or trash recovery, piping skillshare output to scripts (--json), setting up CI/CD audit pipelines, building/sharing skill hubs (hub index, hub add), or working with agents (single .md files synced to agent-capable targets like Claude, Cursor, Augment, OpenCode) via positional `agents` filter or `--kind agent`, plus `.agentignore` and `enable`/`disable` for per-agent toggles.
skillshare-changelog
by runkidsGenerate CHANGELOG.md entry from recent commits in conventional format. Also syncs the website changelog page. Use this skill whenever the user asks to: generate a changelog, document what changed between tags, or create a new CHANGELOG entry. If you see requests like "write the changelog for v0.17", "what changed since last release", this is the skill to use. Do NOT manually edit CHANGELOG.md without this skill — it ensures proper formatting, user-perspective writing, and website changelog sync. For full release workflows (tests, changelog, release notes, version bump, announcements), use /release instead.
skillshare-cli-e2e-test
by runkidsRun isolated E2E tests in devcontainer from ai_docs/tests runbooks. Use this skill whenever the user asks to: run an E2E test, execute a test runbook, validate a feature end-to-end, create a new runbook, or test CLI behavior in isolation. If you need to run a multi-step CLI validation sequence (init → install → sync → verify), this is the skill — it handles ssenv isolation, flag verification, and structured reporting. Prefer this over ad-hoc docker exec sequences for any test that follows a runbook or needs reproducible isolation.
skillshare-codebase-audit
by runkidsCross-validate CLI flags, docs, tests, and targets for consistency across the codebase. Use this skill whenever the user asks to: audit the codebase, check for consistency issues, find undocumented flags, verify test coverage, validate targets.yaml, check handler split conventions, or verify oplog instrumentation. This is a read-only audit — it reports issues but never modifies files. Use after large refactors, before releases, or whenever you suspect docs/code/tests have drifted out of sync.
skillshare-devcontainer
by runkidsRun CLI commands, tests, and debugging inside the skillshare devcontainer. Use this skill whenever you need to: execute skillshare CLI commands for verification, run Go tests (unit or integration), reproduce bugs, test new features, start the web UI, or perform any operation that requires a Linux environment. All CLI execution MUST happen inside the devcontainer — never run skillshare commands on the host. If you are about to use Bash to run `ss`, `skillshare`, `go test`, or `make test`, stop and use this skill first to ensure correct container execution.
skillshare-release
by runkidsEnd-to-end release workflow for skillshare. Runs tests, generates changelog (via /changelog), optionally writes local RELEASE_NOTES, updates version numbers, commits, and drafts announcements. Use when the user says "release", "prepare release", "cut a release", "release v0.19", or any request to publish a new version. For changelog-only tasks, use /changelog instead.
skillshare-ui-website-style
by runkidsSkillshare frontend design system for the React dashboard (ui/) and Docusaurus website (website/). Use this skill whenever you: build or modify a dashboard page or component in ui/src/, style or layout website pages or custom CSS in website/, create new React components for the dashboard, add pages to the dashboard, fix visual bugs in either frontend, or need to know which design tokens, components, or patterns to use. This skill covers color tokens, typography, component API, page structure, accessibility, keyboard shortcuts, animations, and anti-patterns for both frontends. Even if the user just says "fix the styling" or "add a card", use this skill to ensure consistency.
mdproof-cli-e2e-test
by runkidsWrite and run E2E test runbooks that exercise the mdproof CLI itself. Use this skill whenever you need to: verify a new feature works end-to-end, validate a bug fix via a reproducible markdown runbook, test CLI flags (--dry-run, --fail-fast, --steps, --report json, --output), regression-test assertion types (substring, regex, exit_code, jq, snapshot), or confirm that parser/executor changes didn't break real-world runbook files. This skill produces .md files in runbooks/ that mdproof can run against itself — the tool testing itself. If you're about to write or run an E2E test for mdproof, use this skill first.
mdproof-devcontainer
by runkidsRun CLI commands, tests, and debugging inside the mdproof devcontainer. Use this skill whenever you need to: execute mdproof CLI commands, run Go tests (unit or integration), reproduce bugs, test new features, run E2E runbooks, or perform any operation that requires a Linux container environment. mdproof refuses to execute outside Docker by design — the devcontainer is the correct place to run and test it. If you are about to use Bash to run `mdproof`, `go test`, or `make test`, stop and use this skill first to ensure correct container execution.
mdproof-implement-feature
by runkidsImplement a feature from a spec file or description using TDD workflow. Use this skill whenever the user asks to: add a new CLI flag, implement a feature, build new functionality, create a new internal package, add an assertion type, extend the parser, or write Go code for mdproof. This skill enforces test-first development and proper package structure. If the request involves writing Go code and tests, use this skill — even if the user doesn't explicitly say "implement".
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.