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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unifly
by hyperb1issThis skill should be used when the user asks to "manage UniFi devices", "configure UniFi networks", "create a VLAN", "provision an SSID", "create firewall rules", "reorder firewall policies", "create a NAT rule", "set up port forwarding", "configure masquerade NAT", "add DNS records", "manage traffic matching lists", "create DHCP reservations", "list DHCP reservations", "block a client", "kick a client", "find a client by IP or name", "adopt a device", "restart a UniFi device", "cycle a PoE port", "upgrade device firmware", "run a speed test", "stream UniFi events", "watch real-time events", "query UniFi stats", "analyze DPI traffic", "enable DPI", "generate hotspot vouchers", "show network topology", "audit firewall policies", "create a backup", "call the raw UniFi API", "check network health", or any task involving UniFi network infrastructure management via the unifly CLI. Also triggers on mentions of unifly, UniFi, Ubiquiti, UDM, UCG, USG, USW, UAP, UXG, UNVR, U6, U7, or UniFi controller operations.
git-iris
by hyperb1issUse this skill when generating commit messages, pull request descriptions, release notes, changelogs, or code reviews in a repository where git-iris is available. Activates on requests like "commit this", "write a commit message", "draft a PR", "generate release notes", "write a changelog", or "review my changes" when git-iris is on PATH.
sibyl
by hyperb1issPersistent memory and task coordination for this project. Invoke for any prompt about past work, project state, in-progress tasks, prior decisions, gotchas, or capturing a non-obvious learning. Also covers semantic search across project knowledge and external docs.
agent-activity-audit
by hyperb1issAudit recent agent transcripts (Claude Code and Codex) to learn how a tool, system, or skill is actually being used in the wild. Surfaces failure modes, friction, success patterns, and concrete improvement candidates from real session data. Use this when you want to improve a developer-facing system that agents interact with regularly.
android-fastboot
by hyperb1issUse for fastboot operations, flashing partitions, bootloader unlocking, recovery mode, or partition management. Triggers on "fastboot", "flash boot.img", "unlock bootloader", "recovery mode", "TWRP", "Magisk", "partition", "sideload", "A/B slots". WARNING - These operations can brick devices if done incorrectly.
lineageos
by hyperb1issUse when working with LineageOS custom ROM development, including syncing sources, building, device trees, repopick, Gerrit contributions, or LineageOS-specific features. Triggers on "LineageOS", "lineage-sdk", "breakfast", "brunch", "repopick", "vendor/lineage", "lineage.dependencies", "mka bacon".
android
by hyperb1issUse when working with Android devices via ADB - connecting devices, running shell commands, installing apps, debugging, taking screenshots, UI automation, viewing logs, analyzing crashes, or exploring system internals. Triggers on "adb", "logcat", "install apk", "debug android", "android device", "shell command", "screenshot", "dumpsys", "crash", "ANR".
android-build
by hyperb1issUse when building Android apps (Gradle CLI) or ROMs (AOSP, LineageOS). Triggers on "gradle build", "assemble", "AOSP", "LineageOS", "lunch", "mka", "breakfast", "brunch", "compile android", "device tree", "kernel build".
dream
by hyperb1issUse this skill to review recent conversations and consolidate learnings into Sibyl. Activates on mentions of dream, dreaming, consolidate memory, review conversations, what did we learn, sleep cycle, reflect on sessions, consolidate knowledge, memory maintenance, nightly review, digest sessions, or dream mode.
git
by hyperb1issUse this skill for complex git operations including rebases, merge conflict resolution, cherry-picking, branch management, or repository archaeology. Activates on mentions of git rebase, merge conflict, cherry-pick, git history, branch cleanup, git bisect, worktree, force push, or complex git operations.
implement
by hyperb1issUse this skill when writing code, building features, fixing bugs, refactoring, or any multi-step implementation work. Activates on mentions of implement, build this, code this, start coding, fix this bug, refactor, make changes, develop this feature, implementation plan, coding task, write the code, or start building.
orchestrate
by hyperb1issUse this skill when orchestrating multi-agent work at scale - research swarms, parallel feature builds, wave-based dispatch, build-review-fix pipelines, or any task requiring 3+ agents. Activates on mentions of swarm, parallel agents, multi-agent, orchestrate, fan-out, wave dispatch, research army, unleash, dispatch agents, or parallel work.
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.