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...
prompt-wizard
by dtsongInteractive wizard to craft effective prompts using Claude Code best practices
pqc-readiness
by dtsongUse when assessing a system's readiness for post-quantum cryptography migration, inventorying classical crypto usage, mapping NIST-standardized PQC replacements, and planning phased migration timelines. Covers key exchange, digital signatures, and hybrid mode needs. Do not use for classical crypto implementation review (use crypto-review) or protocol state machine analysis (use protocol-analysis).
formal-spec
by dtsongUse when writing formal specifications in TLA+ to verify system properties, defining state variables, configuring TLC model checker, and documenting assumptions and limitations. Covers safety and liveness properties for protocols and concurrent systems. Do not use for security claim enumeration without specification intent (use invariant-analysis).
soc-integration
by dtsongUse when planning SoC integration including bus fabric architecture, memory map allocation, IP qualification, interrupt routing, and design-for-test strategy. Covers AMBA/AXI protocols, register map design, DFT insertion, and production test planning. Do not use for RTL design flow (use chip-design-flow) or block-level verification (use verification-methodology).
embedded-architecture
by dtsongUse when designing firmware architecture for embedded or IoT devices. Covers RTOS selection, memory layout, power state machine, task decomposition, and watchdog recovery design. Do not use for wireless protocol selection (use protocol-design) or fleet-scale device management (use fleet-management).
protocol-design
by dtsongUse when selecting and designing communication protocol stacks for IoT or embedded systems. Covers physical layer selection, transport and application protocols, security layers, message format design, and error resilience. Do not use for firmware architecture (use embedded-architecture) or fleet-scale operations (use fleet-management).
caching-strategy
by dtsongUse when designing or auditing a caching architecture. Covers multi-layer cache hierarchy, key schema, TTL policies, invalidation flows, and warming strategies. Do not use for runtime performance profiling (use performance-audit) or capacity planning (use load-modeling).
kernel-hardening
by dtsongUse when auditing kernel security configuration for memory protection, syscall surface reduction, control flow integrity, and integrity mechanisms against local and remote attack vectors. Covers CIS/KSPP benchmarks, KASLR, SMAP/SMEP, seccomp, and secure boot chain. Do not use for isolation boundary analysis (use isolation-review) or HW/SW interface review (use hw-sw-boundary).
a11y-audit
by dtsongUse when auditing accessibility compliance of a feature or codebase. Covers WCAG 2.2 AA conformance, screen reader compatibility, keyboard navigation, focus management, color contrast, reduced motion, and ARIA usage. Do not use for general UX review (use journey-mapping) or component interaction specs (use interaction-design).
cost-analysis
by dtsongUse when modeling infrastructure costs, projecting scaling expenses, or identifying optimization opportunities across cloud providers and third-party services. Covers per-unit cost estimation, growth milestone projections, and budget alerting setup. Do not use for deployment strategy design (use deployment-plan) or monitoring architecture (use observability-design).
hw-security-signoff
by dtsongUse when a hardware design needs security sign-off before tape-out. Defines the builder-to-auditor handoff contract between Foundry (constructive design) and Forge (security review). Covers security review prerequisites, artifact checklist, sign-off criteria, and conditional approval workflow. Do not use for RTL security review itself (use rtl-security-review) or design flow guidance (use foundry/chip-design-flow).
chip-design-flow
by dtsongUse when guiding RTL-to-GDSII chip design flow including RTL coding style, synthesis constraints, place-and-route strategy, timing closure, and tape-out checklist. Do not use for verification methodology (use verification-methodology) or SoC integration (use soc-integration).
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.