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 27 skills
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streamlit-development

by sfc-gh-dflippo
star 32

Developing, testing, and deploying Streamlit data applications on Snowflake. Use this skill when you're building interactive data apps, setting up local development environments, testing with pytest or Playwright, or deploying apps to Snowflake using Streamlit in Snowflake.

navigation main article SKILL.md
schedule Updated 5 months ago
sfc-gh-dflippo

task-master

by sfc-gh-dflippo
star 32

AI-powered task management for structured, specification-driven development. Use this skill when you need to manage complex projects with PRDs, break down tasks into subtasks, track dependencies, and maintain organized development workflows across features and branches.

navigation main article SKILL.md
schedule Updated 4 months ago
sfc-gh-dflippo

snowflake-cli

by sfc-gh-dflippo
star 32

Executing SQL, managing Snowflake objects, deploying applications, and orchestrating data pipelines using the Snowflake CLI (snow) command. Use this skill when you need to run SQL scripts, deploy Streamlit apps, execute Snowpark procedures, manage stages, automate Snowflake operations from CI/CD pipelines, or work with variables and templating.

navigation main article SKILL.md
schedule Updated 5 months ago
sfc-gh-dflippo

snowflake-connections

by sfc-gh-dflippo
star 32

Configuring Snowflake connections using connections.toml (for Snowflake CLI, Streamlit, Snowpark) or profiles.yml (for dbt) with multiple authentication methods (SSO, key pair, username/password, OAuth), managing multiple environments, and overriding settings with environment variables. Use this skill when setting up Snowflake CLI, Streamlit apps, dbt, or any tool requiring Snowflake authentication and connection management.

navigation main article SKILL.md
schedule Updated 6 months ago
sfc-gh-dflippo

dbt-modeling

by sfc-gh-dflippo
star 32

Writing dbt models with proper CTE patterns, SQL structure, and layer-specific templates. Use this skill when writing or refactoring dbt models, implementing CTE patterns, creating staging/intermediate/mart models, or ensuring proper SQL structure and dependencies.

navigation main article SKILL.md
schedule Updated 6 months ago
sfc-gh-dflippo

dbt-architecture

by sfc-gh-dflippo
star 32

dbt project structure using medallion architecture (bronze/silver/gold layers). Use this skill when planning project organization, establishing folder structure, defining naming conventions, implementing layer-based configuration, or ensuring proper model dependencies and architectural patterns.

navigation main article SKILL.md
schedule Updated 5 months ago
sfc-gh-dflippo

dbt-artifacts

by sfc-gh-dflippo
star 32

Monitor dbt execution using the dbt Artifacts package. Use this skill when you need to track test and model execution history, analyze run patterns over time, monitor data quality metrics, or enable programmatic access to dbt execution metadata across any dbt version or platform.

navigation main article SKILL.md
schedule Updated 5 months ago
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dbt-commands

by sfc-gh-dflippo
star 32

dbt command-line operations, model selection syntax, Jinja patterns, troubleshooting, and debugging. Use this skill when running dbt commands, selecting specific models, debugging compilation errors, using Jinja macros, or troubleshooting dbt execution issues.

navigation main article SKILL.md
schedule Updated 5 months ago
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dbt-core

by sfc-gh-dflippo
star 32

Managing dbt-core locally - installation, configuration, project setup, package management, troubleshooting, and development workflow. Use this skill for all aspects of local dbt-core development including non-interactive scripts for environment setup with conda or venv, and comprehensive configuration templates for profiles.yml and dbt_project.yml.

navigation main article SKILL.md
schedule Updated 6 months ago
sfc-gh-dflippo

dbt-materializations

by sfc-gh-dflippo
star 32

Choosing and implementing dbt materializations (ephemeral, view, table, incremental, snapshots, Python models). Use this skill when deciding on materialization strategy, implementing incremental models, setting up snapshots for SCD Type 2 tracking, or creating Python models for machine learning workloads.

navigation main article SKILL.md
schedule Updated 4 months ago
sfc-gh-dflippo

dbt-migration-bigquery

by sfc-gh-dflippo
star 32

Convert Google BigQuery DDL to dbt models compatible with Snowflake. This skill should be used when converting views, tables, or stored procedures from BigQuery to dbt code, generating schema.yml files with tests and documentation, or migrating BigQuery SQL to follow dbt best practices.

navigation main article SKILL.md
schedule Updated 4 months ago
sfc-gh-dflippo

dbt-migration-db2

by sfc-gh-dflippo
star 32

Convert IBM DB2 DDL to dbt models compatible with Snowflake. This skill should be used when converting views, tables, or stored procedures from DB2 to dbt code, generating schema.yml files with tests and documentation, or migrating DB2 SQL to follow dbt best practices.

navigation main article SKILL.md
schedule Updated 4 months 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.