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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Showing 12 of 143 skills
mohitagw15856

hiring-rubric

by mohitagw15856
star 973

Generate a structured interview scorecard and interview guide for any role. Use when asked to create a hiring rubric, interview scorecard, structured interview guide, or assessment criteria for a job. Produces a scorecard with competencies, behavioural questions, and scoring guidance.

navigation main article SKILL.md
schedule Updated 17 days ago
mohitagw15856

job-description-writer

by mohitagw15856
star 973

Write a clear, inclusive, and structured job description for any role. Use when asked to write a job description, job posting, JD, or job advert. Produces a complete JD with role summary, responsibilities, requirements, and inclusive language review.

navigation main article SKILL.md
schedule Updated 17 days ago
mohitagw15856

job-story-mapper

by mohitagw15856
star 973

Write Jobs-to-be-Done (JTBD) job stories and map customer jobs across functional, social, and emotional dimensions. Use when defining user needs, writing job stories, conducting JTBD research, or reframing features around customer outcomes. Produces a job story map with opportunity scoring, pain intensity ratings, and product opportunity analysis.

navigation main article SKILL.md
schedule Updated 17 days ago
mohitagw15856

job-application

by mohitagw15856
star 973

Tailors a CV and cover letter to a specific job description. Use when asked to write a cover letter, tailor a CV or resume, optimise for ATS, match a job description, or prepare a job application. Produces an ATS-optimised tailored CV summary and a personalised cover letter aligned to the role's requirements.

navigation main article SKILL.md
schedule Updated 17 days ago
mohitagw15856

nda-analyser

by mohitagw15856
star 973

Analyses a Non-Disclosure Agreement clause by clause and flags unusual terms, one-sided provisions, and negotiation points. Use when reviewing an NDA, mutual NDA, confidentiality agreement, or non-disclosure deed before signing or countering. Produces a plain English verdict, clause-by-clause risk analysis, and a prioritised negotiation checklist — always with a disclaimer that qualified legal advice is required before signing.

navigation main article SKILL.md
schedule Updated 17 days ago
mohitagw15856

qbr-deck

by mohitagw15856
star 973

Build a Quarterly Business Review (QBR) deck structure and narrative for a customer account. Use when asked to prepare a QBR, business review meeting, executive review, or quarterly check-in with a customer. Produces a slide-by-slide QBR structure with talking points, metrics review, value narrative, and mutual next steps.

navigation main article SKILL.md
schedule Updated 17 days ago
mohitagw15856

vendor-evaluation

by mohitagw15856
star 973

Create a structured vendor evaluation framework for any procurement decision. Use when asked to evaluate vendors, compare suppliers, run an RFP scoring process, or assess a software or service provider. Produces a weighted scorecard, evaluation criteria, and recommendation framework.

navigation main article SKILL.md
schedule Updated 17 days ago
mohitagw15856

ux-research-plan

by mohitagw15856
star 973

Create a structured UX research plan for any product question or feature. Use when asked to write a research plan, design a user study, create a discussion guide, write screener questions, or plan usability testing. Produces a full research plan with objectives, methodology, screener, discussion guide, and synthesis framework.

navigation main article SKILL.md
schedule Updated 17 days ago
mohitagw15856

legal-brief

by mohitagw15856
star 973

Draft a structured legal brief, case summary, or legal argument outline. Use when asked to write a legal brief, case note, legal memo, argument outline, or position paper. Produces a structured document using IRAC format (Issue, Rule, Application, Conclusion).

navigation main article SKILL.md
schedule Updated 17 days ago
mohitagw15856

literature-review

by mohitagw15856
star 973

Structure and write a literature review for any research topic. Use when asked to write a literature review, systematic review summary, narrative review, or research background section. Produces a structured review with thematic organisation, critical analysis, and gap identification.

navigation main article SKILL.md
schedule Updated 17 days ago
mohitagw15856

go-to-market

by mohitagw15856
star 973

Create go-to-market assets for any product or feature. Use when asked for a GTM plan, positioning statement, product launch plan, messaging pillars, use cases, or feature/benefit list. Generates a full GTM pack: positioning statement, messaging pillars, feature-to-benefit mapping, and role-specific use cases.

navigation main article SKILL.md
schedule Updated 17 days ago
mohitagw15856

go-to-market-planner

by mohitagw15856
star 973

Build a go-to-market plan for any product launch, feature release, or new market entry. Use when planning a product launch, writing a GTM strategy, defining launch tiers, or coordinating cross-functional launch activities. Produces a tiered GTM plan with messaging, cross-functional activity tracker, success metrics, and launch day checklist.

navigation main article SKILL.md
schedule Updated 17 days ago
Page 1 of 12

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.