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.
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xlsx-processing-openai
by lawve-aiToolkit for comprehensive Spreadsheet reading, creation, editing, and analysis with visual quality control. Use to work with spreadsheets (.xlsx, .xlsm, .csv, .tsv) for: (1) Creating new spreadsheets with formulas and formatting, (2) Reading or analyzing tabular data, (3) Modifying existing spreadsheets while preserving formulas, (4) Building financial models with proper formatting, (5) Data visualization with in-sheet charts, or any other spreadsheet tasks.
xlsx-processing-manus
by lawve-aiProfessional Excel spreadsheet creation with a focus on aesthetics and data analysis. Use when creating spreadsheets for organizing, analyzing, and presenting structured data in a clear and professional format.
xlsx-processing-anthropic
by lawve-aiUse this skill any time a spreadsheet file is the primary input or output. This means any task where the user wants to: open, read, edit, or fix an existing .xlsx, .xlsm, .csv, or .tsv file (e.g., adding columns, computing formulas, formatting, charting, cleaning messy data); create a new spreadsheet from scratch or from other data sources; or convert between tabular file formats. Trigger especially when the user references a spreadsheet file by name or path — even casually (like "the xlsx in my downloads") — and wants something done to it or produced from it. Also trigger for cleaning or restructuring messy tabular data files (malformed rows, misplaced headers, junk data) into proper spreadsheets. The deliverable must be a spreadsheet file. Do NOT trigger when the primary deliverable is a Word document, HTML report, standalone Python script, database pipeline, or Google Sheets API integration, even if tabular data is involved.
vendor-due-diligence-patrick-munro
by lawve-aiFramework for assessing IT service providers, technology vendors, and third-party partners. Creates structured risk assessments across financial, operational, compliance, security, and reputational dimensions with regulatory checklists (GDPR, DORA, NIS2, SOX). Use when: (1) Evaluating new vendors or technology providers, (2) Conducting third-party risk assessments for procurement, (3) Performing critical vendor due diligence for regulatory compliance, (4) Creating vendor onboarding documentation, (5) Establishing ongoing vendor monitoring processes, (6) Assessing vendor concentration risk, or (7) Generating executive-level vendor risk reports.
skill-creator-anthropic
by lawve-aiGuide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Claude's capabilities with specialized knowledge, workflows, or tool integrations.
statute-analysis-rafal-fryc
by lawve-aiGuide for reading, interpreting, and applying statutes, regulations, and rules in legal and compliance contexts. Use when the user asks about (1) how to read and interpret statutes, regulations, or rules, (2) statutory interpretation methods and canons of construction, (3) understanding legislative intent, (4) applying statutes to specific legal situations, (5) extracting requirements from legal text, (6) distinguishing between different types of legal requirements, or (7) cross-jurisdictional compliance analysis.
tabular-review-lawvable
by lawve-aiGuide to analyze multiple documents (PDF, DOCX) against user-defined columns and produce a structured Excel output with citations. Use when the user wants to: (1) Extract specific information from multiple documents into a table, (2) Compare clauses or provisions across contracts, (3) Create a document review matrix with source citations. Triggers on: 'tabular review', 'document matrix', 'extract from documents', 'compare across documents', 'review multiple contracts'.
tech-contract-negotiation-patrick-munro
by lawve-aiGuide to negotiating technology services agreements, professional services contracts, and commercial B2B transactions. Provides three-position frameworks (provider-favorable, balanced, client-favorable), deal-size tactics, objection handling templates, and concession roadmaps. Use when: (1) Developing negotiation strategies for SaaS, cloud, or managed services agreements, (2) Preparing position papers and fallback positions, (3) Responding to counterparty objections and demands, (4) Creating concession roadmaps that protect critical interests, (5) Assessing tactics based on deal value and leverage, or (6) Structuring balanced outcomes for liability, IP, payment, SLA, or warranty provisions.
vscode-extension-builder-lawvable
by lawve-aiBuild VS Code extensions from scratch or convert existing JS/React/Vue apps. Supports commands, webviews (React/Vue), custom editors, tree views, and AI agent integration via file-bridge IPC. Use when user wants to create a VS Code extension, convert a web app to an extension, add webviews or custom UIs to VS Code, implement tree views, build custom file editors, integrate with AI agents, or package/publish extensions (.vsix).
assignation-refere-communication-associe-selim-brihi
by lawve-aiRédaction d'assignations en référé devant le tribunal de commerce ou des activités économiques pour le droit de communication d'un associé. Utiliser ce skill quand l'utilisateur demande de rédiger, préparer ou créer une assignation en référé fondée sur l'article L. 238-1 du code de commerce pour obtenir la communication forcée de documents sociaux (comptes annuels, rapports de gestion, PV d'assemblées, etc.) lorsqu'un dirigeant refuse ou fait obstruction à la communication de ces documents à un associé.
assignation-refere-recouvrement-creance-selim-brihi
by lawve-aiRédaction d'assignations en référé devant le tribunal de commerce ou des activités économiques pour le recouvrement de créances commerciales. Utiliser ce skill quand l'utilisateur demande de rédiger, préparer ou créer une assignation en référé pour obtenir le paiement d'une créance impayée (factures, prestations de services, ventes de marchandises, etc.) lorsque le débiteur n'a pas honoré ses obligations de paiement et qu'il n'existe pas de contestation sérieuse.
canned-responses-anthropic
by lawve-aiGenerate templated responses for common legal inquiries and identify when situations require individualized attention. Use when responding to routine legal questions — data subject requests, vendor inquiries, NDA requests, discovery holds — or when managing response templates.
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.