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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generate-charter
by KirKruglovGenerates a project charter from brief, stakeholder answers, and constraints. The charter is the first artifact of the Initiation phase. Once approved, it unlocks dependent tasks: generate-risk-register, generate-project-plan, generate-estimate. Accepts both structured briefs and free-form notes.
kpi-digest-builder
by KirKruglovAggregate numeric KPIs from local files (.md, .txt, .csv) into a weekly snapshot with delta vs. previous week. Use when preparing weekly reports. Triggers: 'build kpi digest', 'weekly kpi snapshot', 'собери KPI дайджест', 'еженедельный снапшот KPI'.
cowork-session-planner
by KirKruglovGenerate a pre-session brief for Cowork: current status, session goal, and prioritised work plan from local project files — before your first real message. Use when starting a session, returning after a break, or needing focus. Triggers: 'session brief', 'prepare my session', 'start my cowork session', 'бриф сессии', 'подготовь сессию', 'что делать в этой сессии'.
meeting-prep-briefer
by KirKruglovGenerate a structured briefing document for each meeting of the day from local workspace files and a daily schedule — participants, context, and open questions in one brief. No integrations required. Triggers: 'meeting brief', 'prep my meetings', 'prepare for today's meetings', 'briefing for my calls today', 'бриф по встречам', 'подготовь встречи', 'бриф на встречи дня', 'что нужно знать перед встречами'.
morning-standup-brief-generator
by KirKruglovCompile local notes, tasks, and project files into a structured standup brief — no connectors required. Use when preparing for morning standup, daily sync, or team check-in. Triggers: 'morning standup brief', 'daily brief', 'prepare me for standup', 'подготовь меня к стендапу', 'дейли бриф', 'утренний бриф'.
generate-meeting-protocol
by KirKruglovGenerates a meeting protocol from free-form notes. Extracts decisions, action items, and plan changes. If project plan is available — links changes to WP-xxx/Mx IDs. Phase 3 artifact, but usable in any phase. Independent skill with no upstream dependencies.
research-folder-synthesizer
by KirKruglovSynthesize a folder of mixed local files (articles, notes, excerpts) into a structured thematic report with key findings and gaps. Use when consolidating research before writing a report, PRD, or strategy doc. Triggers: 'synthesize my research folder', 'research synthesis', 'turn my notes into a report', 'синтезируй папку с исследованиями', 'синтез ресёрча', 'сведи файлы в отчёт'.
routines-setup-assistant
by KirKruglovInterview-style setup for Claude Cowork Scheduled Tasks. Turns your recurring tasks into ready-to-paste automation prompts. Use when automating weekly reports, digests, or reviews. Triggers: 'set up routines', 'automate my recurring tasks', 'настрой рутины', 'помоги создать scheduled tasks'.
session-handoff-composer
by KirKruglovCompose a structured handoff document when your chat session fills up. Extracts decisions, in-progress tasks, open questions, and next steps into a ready-to-paste block for a new session. Triggers: 'compose handoff', 'session handoff', 'составь хэндофф', 'подготовь handoff-документ'.
weekly-digest-synthesizer
by KirKruglovCompile weekly status digests from multiple .md/.txt files. Extracts project updates, action items, and blockers into a structured report. Use when aggregating team status notes into a weekly summary. Triggers: 'compile weekly digest', 'weekly digest', 'составь дайджест', 'скомпилируй статусы'.
workspace-health-monitor
by KirKruglovAudits a manager's workspace files (meeting notes, plans, tasks, logs) to detect orphaned files, forgotten action items, duplicates, and plan-to-reality drift. Use when you want to clean up your workspace, run a weekly hygiene check, find forgotten commitments buried in notes, or spot conflicting information across project documents. Triggers RU: «аудит воркспейса», «проверь рабочую папку», «найди забытые задачи», «почисти workspace», «что я забыл сделать». Triggers EN: workspace audit, workspace health check, find forgotten tasks, orphaned files, weekly cleanup.
changelog-narrator
by KirKruglovCompare two document versions and produce a structured changelog — no git needed. Use for PRDs, SOPs, contracts, strategy docs. Triggers: 'compare these two documents', 'what changed between versions', 'generate a changelog', 'сравни две версии документа', 'что изменилось', 'сделай changelog'.
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.