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 10 of 10 skills
Pupfish-LLC

qlik-load-script

by Pupfish-LLC
star 2

Script syntax reference, QVD optimization, incremental load patterns (insert-only, insert/update, insert/update/delete, dual-timestamp for SCD2), master calendar generation, variable definitions, error handling, logging patterns, null handling patterns, diagnostic and validation patterns, subroutine integration, and platform gotchas (SET vs LET, dollar-sign expansion timing, SET variable comma limitation). Load when writing or reviewing Qlik load scripts.

navigation main article SKILL.md
schedule Updated 3 months ago
Pupfish-LLC

qlik-data-modeling

by Pupfish-LLC
star 2

Star schema patterns, key resolution strategies, synthetic key prevention, QVD layer design, multi-app architecture patterns, source architecture consumption strategies, and associative engine behavior for Qlik Sense data modeling. Load when designing or reviewing data models.

navigation main article SKILL.md
schedule Updated 3 months ago
Pupfish-LLC

qlik-deploy

by Pupfish-LLC
star 2

Deployment procedures for Qlik Sense Cloud and client-managed environments. Covers app import, data connection setup, task scheduling, security configuration, and environment-specific considerations. Invoke manually with /qlik-deploy when preparing deployment artifacts or runbooks.

navigation main article SKILL.md
schedule Updated 3 months ago
Pupfish-LLC

qlik-expressions

by Pupfish-LLC
star 2

Set analysis syntax and patterns, aggregation functions, TOTAL qualifier usage, Aggr() patterns, conditional expressions, null handling in expressions, dollar-sign expansion, expression performance optimization, and common anti-patterns for Qlik Sense expression development. Load when writing or reviewing Qlik expressions.

navigation main article SKILL.md
schedule Updated 3 months ago
Pupfish-LLC

qlik-naming-conventions

by Pupfish-LLC
star 2

Field naming, variable naming, table naming, expression naming, and file naming standards for Qlik Sense development. Includes cross-layer naming strategy for tracing field names from source through every ETL layer to UI display name. Includes prefix/suffix conventions, reserved words, and correct vs. incorrect examples. Load when writing or reviewing any Qlik artifact.

navigation main article SKILL.md
schedule Updated 3 months ago
Pupfish-LLC

qlik-performance

by Pupfish-LLC
star 2

Memory optimization, script load optimization, expression calculation optimization, calculation conditions, data reduction techniques, and profiling/diagnostic approaches for Qlik Sense. Load when optimizing or reviewing performance-sensitive artifacts.

navigation main article SKILL.md
schedule Updated 3 months ago
Pupfish-LLC

qlik-project-scaffold

by Pupfish-LLC
star 2

Initialize a new Qlik project with the standard directory structure, placeholder files, and CLAUDE.md configuration. Creates inputs/ and artifacts/ directories, .pipeline-state.json, and initial artifact placeholders. Invoke manually with /qlik-project-scaffold to set up a new project.

navigation main article SKILL.md
schedule Updated 3 months ago
Pupfish-LLC

qlik-review-checklist

by Pupfish-LLC
star 2

Complete QA checklist used by the qa-reviewer agent for validating Qlik development artifacts. Covers data model integrity, naming convention compliance, script quality, expression correctness, security gaps, cross-artifact consistency, blocked dependency audit, and data quality validation. Also available for manual invocation outside the pipeline via /qlik-review-checklist. Load when performing any QA review pass.

navigation main article SKILL.md
schedule Updated 3 months ago
Pupfish-LLC

qlik-security

by Pupfish-LLC
star 2

Section access patterns, row-level security, data reduction, OMIT field usage, hybrid security models, and Cloud vs. client-managed security implementation differences for Qlik Sense. Load when designing or reviewing security configurations.

navigation main article SKILL.md
schedule Updated 3 months ago
Pupfish-LLC

qlik-visualization

by Pupfish-LLC
star 2

Chart type selection guide, layout patterns, color and formatting standards, filter design, responsive design patterns, accessibility best practices, and reference app reverse-engineering patterns for Qlik Sense visualization design. Load when designing or reviewing visualizations and sheet layouts.

navigation main article SKILL.md
schedule Updated 3 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.