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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jnPiyush
Showing 12 of 25 skills
jnPiyush

yaml-pipelines

by jnPiyush
star 13

Build YAML-based CI/CD pipelines across Azure Pipelines and GitLab CI with progressive disclosure. Use when creating Azure DevOps YAML pipelines, configuring GitLab CI/CD, designing multi-stage pipelines, implementing pipeline templates, or managing pipeline secrets and variables.

navigation main article SKILL.md
schedule Updated 2 months ago
jnPiyush

voice-agents

by jnPiyush
star 13

Build low-latency voice agents using speech-to-speech (S2S) realtime APIs and cascaded STT->LLM->TTS pipelines. Covers OpenAI Realtime / GPT Realtime, Azure Voice Live, Gemini Live, Deepgram Voice Agent, ElevenLabs Conversational AI; turn-taking, barge-in, latency budgets, tool use during speech, and telephony (Twilio, LiveKit, Pipecat).

navigation main article SKILL.md
schedule Updated 1 month ago
jnPiyush

synthetic-data-generation

by jnPiyush
star 13

Generate synthetic data for fine-tuning, eval-set bootstrapping, RAG corpus augmentation, and rare-case coverage. Covers Self-Instruct, Evol-Instruct, persona-based generation, distillation from larger models, dataset curation (filtering, dedup, decontamination), and provenance / dataset cards.

navigation main article SKILL.md
schedule Updated 1 month ago
jnPiyush

dataverse-plugins

by jnPiyush
star 13

Build Microsoft Dataverse server-side extensions in C# (.NET) -- plugins implementing IPlugin and custom workflow activities -- and register them via SdkMessageProcessingStep so an agent can add transactional business logic that runs inside the Dataverse event pipeline. Covers the execution context, pipeline stages, registration metadata, and pro-code-vs-low-code boundaries.

navigation main article SKILL.md
schedule Updated 24 days ago
jnPiyush

diagram-as-code

by jnPiyush
star 13

Author, review, and maintain diagrams as code across Mermaid, PlantUML, Structurizr DSL, Graphviz DOT, and draw.io XML. Covers swimlane/cross-functional workflows, C4 architecture, sequence, state, ER, dependency, and network diagrams. Use when any agent needs to create or update a diagram in a PRD, ADR, spec, UX flow, or architecture doc.

navigation main article SKILL.md
schedule Updated 2 months ago
jnPiyush

tax

by jnPiyush
star 13

Tax advisory skill for consulting engagements. Use when preparing tax position analyses, transfer pricing assessments, Pillar Two readiness evaluations, tax function transformation roadmaps, or stakeholder materials for tax directors, CFOs, and treasury leaders.

navigation main article SKILL.md
schedule Updated 3 months ago
jnPiyush

karpathy-guidelines

by jnPiyush
star 13

Behavioral guidelines to reduce common LLM coding mistakes. Use when writing, reviewing, or refactoring code to avoid overcomplication, make surgical changes, surface assumptions, and define verifiable success criteria. Adapted from Andrej Karpathy's observations on LLM coding pitfalls.

navigation main article SKILL.md
schedule Updated 25 days ago
jnPiyush

oil-and-gas

by jnPiyush
star 13

Oil and gas advisory skill for consulting engagements. Use when preparing operations benchmarking, energy transition readiness assessments, production economics analysis, digital oilfield strategy, or stakeholder materials for E&P executives, midstream operators, and sustainability leaders.

navigation main article SKILL.md
schedule Updated 3 months ago
jnPiyush

azure

by jnPiyush
star 13

Build scalable, secure, and reliable applications on Microsoft Azure cloud services. Use when deploying to Azure, configuring Azure compute/storage/database services, setting up Azure networking, implementing Azure security, or managing Azure costs and monitoring.

navigation main article SKILL.md
schedule Updated 3 months ago
jnPiyush

bicep

by jnPiyush
star 13

Deploy Azure infrastructure declaratively using Bicep and ARM templates. Use when writing .bicep or .bicepparam files, creating reusable modules, defining user-defined types, securing parameters, or validating deployments with what-if and PSRule.

navigation main article SKILL.md
schedule Updated 3 months ago
jnPiyush

terraform

by jnPiyush
star 13

Provision cloud infrastructure safely and consistently using Terraform and Infrastructure as Code patterns. Use when writing .tf or .tfvars files, creating reusable modules, managing remote state, securing infrastructure, or running Terratest integration tests.

navigation main article SKILL.md
schedule Updated 3 months ago
jnPiyush

audit-assurance

by jnPiyush
star 13

Audit and assurance advisory skill for consulting engagements. Use when preparing audit readiness assessments, control environment evaluations, SOC reporting guidance, ESG assurance readiness, or stakeholder materials for audit partners, audit committees, CFOs, and internal audit directors.

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.