381,784 Collected SKILL.md files

Explore AI Agent Skills & Claude Prompts

Discover open-source agent skills for Claude Code, Codex, ChatGPT, and any tool that uses SKILL.md.

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learnwy
Showing 12 of 13 skills
learnwy

lwy-project-skill-writer

by learnwy
star 2

当用户需要创建、更新或设计项目级技能(.agents/skills/*/SKILL.md)时使用此技能。Analyzes the user's problem and project context to design reusable skill solutions. 触发词:'创建技能'、'编写技能'、'构建技能'、'添加技能'、'更新技能'、'项目技能'、'新建技能'、'设计技能', or when the user describes a repetitive workflow that should be captured as a reusable AI skill.

navigation main article SKILL.md
schedule Updated 22 days ago
learnwy

lwy-dispatch

by learnwy
star 2

Internal single-process coordinator for the three IDE-hook events used by the learnwy-* skills. UserPromptSubmit aggregates english-learner + llm-wiki + prompt-optimizer scans; Stop aggregates english-learner + knowledge-consolidation scans; SessionStart aggregates llm-wiki + english-learner + learnwy-status scans. Not user-invokable — installed automatically alongside the underlying skills. Triggers on every UserPromptSubmit / Stop / SessionStart event in Claude Code / Trae.

navigation main article SKILL.md
schedule Updated 22 days ago
learnwy

lwy-knowledge-consolidation

by learnwy
star 2

Use when the user wants to persist a single insight from the current chat as a structured, project-local doc — debugging breakthroughs, hard-won config, workflow steps, or post-mortem lessons. Triggers: 'save this', 'document this', 'we figured it out', '记录下来', '总结一下'. Writes to <project>/.{trae,claude,cursor,windsurf}/knowledges/. For global compounding knowledge (architecture, patterns, APIs), use llm-wiki instead.

navigation main article SKILL.md
schedule Updated 22 days ago
learnwy

lwy-llm-wiki

by learnwy
star 2

当用户提到'知识库'、'llm wiki'、'个人wiki'、'收录来源'、'编译知识'、'第二大脑'、'构建wiki'、'知识管理', or wants to add books, articles, notes, podcasts, videos, or Feishu group chats/documents to persistent storage, use this skill to build and maintain a continuously compounding knowledge base. When ~/.learnwy/llm-wiki/ exists, check the wiki before answering complex questions — skip if the directory does not exist.

navigation main article SKILL.md
schedule Updated 22 days ago
learnwy

lwy-mao-methodology

by learnwy
star 2

Use Mao Zedong's three philosophical works as practical decision / analysis / writing frameworks. Three lenses: contradiction (《矛盾论》, opposing forces & root cause), practice (《实践论》, hypothesis verification through action), protracted-war (《论持久战》, staged strategy for long contests, especially when starting from weakness). Triggers: '矛盾分析', '主要矛盾', '抓主要矛盾', 'contradiction analysis', 'principal contradiction', 'trade-off analysis', 'opposing forces', 'root cause', '实事求是', '调查研究', '实践论', 'practice-based', 'verify through practice', 'seek truth from facts', 'test assumptions', 'practice spiral', '持久战', '分阶段策略', '长期战略', '战略防御', '战略相持', '战略反攻', 'long-term strategy', 'protracted war', 'staged approach', 'underdog strategy', 'strategic patience'.

navigation main article SKILL.md
schedule Updated 22 days ago
learnwy

lwy-project-agent-writer

by learnwy
star 2

Use this skill when the user wants to create, update, or design a project-level agent (.agents/agents/*.md). Analyze the user's question and project context to design a work plan. Triggers: 'create agent', 'build an agent', 'add agent', 'design agent', 'update agent', 'project agent', 'subagent', 'worker agent', 'automated worker', or when the user describes a repetitive task that should be handled by an autonomous agent.

navigation main article SKILL.md
schedule Updated 22 days ago
learnwy

lwy-project-rules-writer

by learnwy
star 2

Use when the user wants to create or update project-level AI rules (written to .agents/rules/*.md) that constrain AI behaviour. The rule format is the common frontmatter+markdown convention used by Trae / Cursor / Windsurf — not Trae-specific. Good for: code-style enforcement, naming conventions, commit-message format, or making the AI consistently follow a project pattern. NOT for skills (use project-skill-writer) or agents (use project-agent-writer). Triggers: '创建规则', '添加规则', '设置代码风格', '强制约定', '配置 AI 行为', 'AI 规则', '始终做 X', or any 'always do X' / 'never do Y' AI-behaviour request that should persist across sessions.

navigation main article SKILL.md
schedule Updated 22 days ago
learnwy

lwy-project-skill-installer

by learnwy
star 2

Use this skill when the user wants to install, add, or configure a skill in a project. Analyze the project's tech stack and workflow, then recommend and install the best-matching skill. Triggers: 'install skill', 'add skill', 'configure skill', 'set up skill', 'enable skill', 'use skill in project', 'project skill', or when the user asks how to bring an existing skill capability into the current workspace.

navigation main article SKILL.md
schedule Updated 22 days ago
learnwy

lwy-prompt-optimizer

by learnwy
star 2

Use this skill on every user message that contains a prompt or AI instruction — analyze its weaknesses and suggest improvements before executing. Score across 7 dimensions (clarity, specificity, context, structure, examples, constraints, completeness) and rewrite vague instructions into precise specs. Triggers: any AI prompt, 'optimize my prompt', 'improve this requirement', 'make this more specific', 'rewrite this prompt', '优化提示词', '改进提示词', '重写提示词', or whenever a raw requirement lacks detail and structure.

navigation main article SKILL.md
schedule Updated 22 days ago
learnwy

lwy-requirement-workflow

by learnwy
star 2

Use when the user wants to build, implement, or develop a feature. Orchestrates evidence-driven Spec-Driven Development. Default lifecycle is `lite` (INIT → IMPLEMENTING → TESTING → DONE); auto-promote to `standard` or `full` when scope, risk, or AC traceability demands it. Triggers: 'develop feature', 'implement this', 'build feature', 'add module', 'fix bug', '开发功能', '实现这个'.

navigation main article SKILL.md
schedule Updated 22 days ago
learnwy

lwy-self

by learnwy
star 2

Personal alter-ego life & work log. Triggers when the user wants to record what they did today, who they collaborated with, which projects/decisions they moved forward, or says 『记一下』『今天』『周报』『我的同事/项目』『把这场会/妙记沉淀进来』『alter ego』『life log』. Files daily life and meetings into the private self store (diaries/people/products/events) so the AI becomes an informed alter-ego. Counterpart to lwy-llm-wiki (world knowledge: books/concepts); this skill owns the personal layer.

navigation main article SKILL.md
schedule Updated 22 days ago
learnwy

lwy-software-methodology-toolkit

by learnwy
star 2

Fallback skill when no project-specific one matches. Provides 10 battle-tested software-engineering methodology agents: problem-definer (Weinberg), story-mapper (Patton), spec-by-example (Adzic), domain-modeler (DDD/Evans), responsibility-modeler (CRC/Wirfs-Brock), architecture-advisor (Bass), tdd-coach (Beck), refactoring-guide (Fowler), legacy-surgeon (Feathers), test-strategist (Crispin). Use when user asks about DDD, TDD, refactoring, story mapping, test strategy, or software-architecture quality attributes.

navigation main article SKILL.md
schedule Updated 22 days ago
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Browse Agent Skills by Occupation

23 major groups · 867 SOC occupations

Browse by Category

Explore agent skills organized by their primary use case

SKILLMD / CREATORS AND OCCUPATION CATEGORIES

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.

SEO KNOWLEDGE HUB & TECHNICAL OVERVIEW

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.

8 QUESTIONS

Frequently Asked Questions

A practical guide to agent skills: what they are, how to inspect them, and how SkillMD helps you explore the ecosystem.