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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buildkite-agent-release
by buildkitePrepare for a Buildkite Agent Release.
buildkite-agent-metrics-release
by buildkitePrepare a release for buildkite-agent-metrics.
improve-review-bot
by buildkiteAnalyze feedback on bk-docsbot suggestions to identify rejection patterns and draft prompt improvements that increase accuracy. Run this periodically to close the feedback loop.
cleanroom
by buildkiteUse when an agent has the Buildkite Cleanroom CLI installed and should run commands, tests, builds, shells, local services, or other work inside Cleanroom; author or validate cleanroom.yaml policy; or diagnose Cleanroom daemon, backend, sandbox, workspace-copy, network, exposure, or agent-in-sandbox behavior.
buildkite-api
by buildkiteThis skill should be used when the user asks to "call the Buildkite API", "use the REST API", "write a GraphQL query", "set up webhooks", "automate Buildkite", "integrate with Buildkite programmatically", "write a script that calls Buildkite", "handle webhook events", "paginate API results", or "authenticate with the Buildkite API". Also use when the user mentions api.buildkite.com, graphql.buildkite.com, Buildkite REST endpoints, GraphQL mutations, webhook payloads, API tokens, or asks about programmatic access to Buildkite data.
buildkite-cli
by buildkiteThis skill should be used when the user asks to "trigger a build", "check build status", "watch a build", "view build logs", "retry a build", "cancel a build", "list builds", "download artifacts", "upload artifacts", "manage secrets", "create a pipeline", "list pipelines", or "interact with Buildkite from the command line". Also use when the user mentions bk commands, bk build, bk job, bk pipeline, bk secret, bk artifact, bk cluster, bk package, bk auth, bk configure, bk use, bk init, bk api, or asks about Buildkite CLI installation, terminal-based Buildkite workflows, or command-line CI/CD operations.
buildkite-migration
by buildkiteThis skill should be used when the user asks to "migrate to Buildkite", "convert pipelines from Jenkins", "convert GitHub Actions workflows", "convert CircleCI config", "convert Bitbucket Pipelines", "convert GitLab CI", "migrate CI/CD to Buildkite", "switch from Jenkins to Buildkite", "move from GitHub Actions", "plan a CI migration", "convert my CI config", "bk pipeline convert", or "what's the Buildkite equivalent of". Also use when the user mentions migration planning, CI conversion, pipeline conversion, converting workflows, or asks about translating CI/CD configuration from another provider to Buildkite.
buildkite-pipelines
by buildkiteThis skill should be used when the user asks to "write a pipeline", "add caching", "make this build faster", "show test failures in the build page", "add annotations", "only run tests when code changes", "set up dynamic pipelines", "add retry", "parallel steps", "matrix build", "add plugins", or "work with artifacts in pipeline YAML". Also use when the user mentions .buildkite/ directory, pipeline.yml, buildkite-agent pipeline upload, step types (command, wait, block, trigger, group, input), if_changed, notify, concurrency, or asks about Buildkite CI configuration.
buildkite-preflight
by buildkiteRuns Buildkite CI builds against changes in the local working tree. Use when asked to run preflight or run CI.
buildkite-agent-runtime
by buildkiteThis skill should be used when the user asks to "add an annotation", "upload artifacts from a step", "share data between steps", "upload pipeline dynamically", "request an OIDC token inside a step", "acquire a distributed lock", "get or update a step attribute", "redact a secret from logs", "retrieve a cluster secret at runtime", or "debug environment variables in hooks". Also use when the user mentions buildkite-agent annotate, buildkite-agent artifact upload/download, buildkite-agent meta-data set/get, buildkite-agent pipeline upload, buildkite-agent oidc request-token, buildkite-agent step, buildkite-agent lock, buildkite-agent env, buildkite-agent secret get, buildkite-agent redactor add, buildkite-agent tool sign/verify, or any buildkite-agent subcommand used inside a running job step.
bk-convert
by buildkiteConverts a CI pipeline from another vendor to Buildkite, following established best practices and translation rules
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.