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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ilspy-decompile
by davidfowlUnderstand implementation details of .NET code by decompiling assemblies. Use when the user wants to see how a .NET API works internally, inspect NuGet package source, view framework implementation, or understand compiled .NET binaries.
aspire-deployment
by davidfowl**WORKFLOW SKILL** — Deploy Aspire apps from AppHost models to Docker Compose, Kubernetes, Azure, or AWS. WHEN: "deploy Aspire app", "publish Aspire artifacts", "deploy to Azure Container Apps", "generate Kubernetes artifacts", "tear down Aspire deployment". INVOKES: aspire CLI, Aspire docs, target cloud/container CLIs. FOR SINGLE OPERATIONS: use generic Azure, Kubernetes, Docker, or AWS tools only when no Aspire AppHost exists.
aspire
by davidfowlUse when working with an Aspire distributed application: operate an AppHost or resources through the Aspire CLI; start, stop, restart, or wait for resources; inspect app state, logs, traces, docs, or health; add integrations; manage secrets/config; publish/deploy or run pipeline steps; initialize an existing app; recover TypeScript `.modules`; find frontend URLs for Playwright; expose custom dashboard/resource commands; or understand Aspire AppHost APIs in C# or TypeScript. Use even if the user says AppHost, resources, dashboard, bootstrap, Playwright URL, or local distributed app workflow without naming Aspire. Do not use for non-Aspire .NET apps, container-only repos without an AppHost, or ordinary build/test tasks.
aspire-monitoring
by davidfowl**ANALYSIS SKILL** - Observe Aspire apps: logs, traces, metrics, resource state, telemetry export, browser telemetry, and the standalone dashboard. Routes between local Aspire CLI, AKS workload diagnostics, and deployed Azure resource health. USE FOR: aspire logs, aspire otel logs, aspire otel traces, aspire otel spans, aspire describe, aspire ps, aspire export, aspire dashboard run, --include-hidden, browser logs in dashboard, WithBrowserLogs, App Insights query, AKS pod logs, container app logs. DO NOT USE FOR: start/stop/wait (use aspire-orchestration), deploy/publish/destroy (use aspire-deployment), AppHost code edits like WithBrowserLogs() (use aspireify), Azure provisioning (use azure-prepare). INVOKES: aspire CLI, azure-diagnostics (deployed Azure), kubectl + Container Insights. FOR SINGLE OPERATIONS: Run the aspire CLI command directly for quick log or describe lookups.
aspire-deployment
by davidfowl**WORKFLOW SKILL** — Deploy Aspire apps from AppHost models to Docker Compose, Kubernetes, Azure, or AWS. WHEN: "deploy Aspire app", "publish Aspire artifacts", "deploy to Azure Container Apps", "generate Kubernetes artifacts", "tear down Aspire deployment". INVOKES: aspire CLI, Aspire docs, target cloud/container CLIs. FOR SINGLE OPERATIONS: use generic Azure, Kubernetes, Docker, or AWS tools only when no Aspire AppHost exists.
aspire-init
by davidfowl**WORKFLOW SKILL** - First-run flow for adding Aspire to a repo. Picks `aspire new` (greenfield) or `aspire init` (existing repo), drops the AppHost skeleton, then hands off to `aspireify` for resource wiring. USE FOR: aspire init, aspire new, aspire-starter, aspire-ts-starter, aspire-py-starter, add Aspire to existing repo, scaffold Aspire app, bootstrap Aspire, no AppHost detected, install aspireify, generated .aspire/modules. DO NOT USE FOR: AppHost wiring on an existing AppHost (use aspireify), start/stop/wait (use aspire-orchestration), deploy/publish (use aspire-deployment), logs/traces (use aspire-monitoring), repo that already has an AppHost. INVOKES: aspire CLI (init, new, doctor), aspireify (handoff after skeleton drop). FOR SINGLE OPERATIONS: Run `aspire init` or `aspire new TEMPLATE` directly.
aspireify
by davidfowl**WORKFLOW SKILL** - Wire an Aspire AppHost after `aspire init` drops a skeleton. Scans the repo, proposes a resource graph, edits the AppHost (C#, file-based C#, or TypeScript), wires `Aspire.ServiceDefaults` + OTel, validates with `aspire start`, then self-deactivates. USE FOR: wire AppHost, scaffold resource graph, add Postgres/Redis/Rabbit/Mongo to Aspire, connect frontend to API, after `aspire init` what next, AddNextJsApp, AddViteApp, WithBrowserLogs, file-based apphost.cs, apphost.ts, unified withEnvironment, refuse .aspire/modules edit, migrate .env files, migrate user secrets. DO NOT USE FOR: skeleton drop (use aspire-init), start/stop/wait/restart (use aspire-orchestration), publish/deploy/destroy (use aspire-deployment), logs/traces (use aspire-monitoring). INVOKES: aspire CLI (add, start, wait, describe, docs api search, stop), AppHost source edits, ServiceDefaults wiring. FOR SINGLE OPERATIONS: Run `aspire add PACKAGE` directly for a one-off integration.
aspire
by davidfowl**WORKFLOW SKILL** - Top-level router for Aspire 13.4 distributed apps. Detects the AppHost, enforces safety guardrails, and routes to the right sub-skill. USE FOR: Aspire AppHost detected, aspire CLI, distributed app, cloud-native .NET, aspire start, aspire stop, aspire resource, aspire deploy, aspire destroy, aspire publish, aspire init, aspire new, aspire add, aspire integration list/search, aspire wait, aspire describe, aspire ps, aspire dashboard run, aspire doctor, aspire update, aspire logs, aspire otel, --include-hidden, aspireify, WithBrowserLogs, custom dashboard/resource commands, .aspire/modules recovery, Playwright URL discovery. DO NOT USE FOR: non-Aspire .NET projects (use dotnet directly), Azure provisioning without Aspire (use azure-prepare), container-only repos with no AppHost, ordinary build/test tasks. INVOKES: aspire-init, aspireify, aspire-orchestration, aspire-deployment, aspire-monitoring. FOR SINGLE OPERATIONS: Route directly to the matching sub-skill.
aspire-orchestration
by davidfowl**WORKFLOW SKILL** — Manage Aspire AppHost lifecycle and recover from file locks, port conflicts, and orphaned processes. WHEN: "start my Aspire app", "aspire start", "aspire stop", "aspire wait", "restart the API service", "file lock error", "MSB3491", "CS2012", "port already in use", "upgrade Aspire CLI", "aspire update --self", "proxies missing in aspire ps", "--include-hidden", "aspire integration list", "aspire integration search", "default watch", "hot reload". INVOKES: aspire CLI (start, stop, wait, ps, resource, integration, add, init, doctor, update, restore). FOR SINGLE OPERATIONS: Run the aspire CLI command directly.
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.