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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youtube-thumbnail-generate
by naveedharriGenerate on-brand YouTube thumbnails for Ben van Sprundel using Higgsfield in one shot. Use when the user says create a thumbnail, make a YT thumbnail, thumbnail for video, generate ben thumbnail, variation of last thumbnail, or shares a video concept and asks for a thumbnail. Auto-infers mode from the inputs (variation, new-with-ben, ben-plus-other, no-face), defaults to 3 variants, and asks at most one question. Uses reference images as the identity anchor (a current photo of Ben from refs/, plus optional past thumbnails or style anchors). No Soul training is required. Reads the locked style spec at Context/youtube-thumbnail-style.md if present. Real logos are never rendered. The thumbnail fills its frame edge-to-edge; the user composites the actual logo on top in post.
youtube-brief
by naveedharriCreate a detailed video brief for a new YouTube video through a structured, collaborative process. This is a STEP-BY-STEP, interactive process — never output a complete brief immediately. Each step requires suggestions, user decision, then progression to the next step. USE THIS SKILL WHEN: - User wants to plan a YouTube video - User has a video idea and wants to flesh it out into a brief - User says "video brief", "brief a video", "plan a video" - User mentions "video planning", "video concept", "YouTube brief" - User says "let's plan the next video", "video idea", "brief this" - User wants to define what a video should cover before scripting TRIGGERS: "video brief", "YouTube brief", "plan a video", "video planning", "brief this video", "flesh out this idea", "video concept", "plan the next video", "video idea", "create a brief"
youtube-excalidraw
by naveedharriCreate excalidraw visuals specifically designed for YouTube videos — diagrams, process flows, intro slides, and visual aids that will appear on screen during filming. Optimized for 16:9 video format and readability at YouTube resolution. USE THIS SKILL WHEN: - User wants to create visuals for a YouTube video - User says "make the video diagrams", "excalidraw for the video" - User mentions "video visuals", "on-screen graphics", "YouTube excalidraw" - User has a video outline with visual needs identified TRIGGERS: "video visuals", "YouTube excalidraw", "video diagrams", "on-screen graphics", "excalidraw for video", "video slides", "presentation for video"
youtube-ideation
by naveedharriGenerate and evaluate YouTube video ideas based on Ben's content strategy, audience interests, and competitive landscape. This is an interactive brainstorming process that produces ranked, validated video ideas ready for the brief creation phase. USE THIS SKILL WHEN: - User wants video topic ideas - User says "what should I film next", "video ideas", "content calendar" - User mentions "YouTube ideation", "brainstorm topics", "content ideas" - User wants to plan multiple videos ahead of time TRIGGERS: "video ideas", "content ideas", "what to film", "YouTube ideation", "brainstorm topics", "content calendar", "next video", "what should I film"
youtube-outline
by naveedharriCreate a structured video outline from a video brief. Plans the flow of the video including section structure, demos and examples placement, excalidraw visual needs, and timing estimates. This bridges the brief and the script. USE THIS SKILL WHEN: - User has a video brief and wants to structure the video - User says "outline this video", "video outline", "structure the video" - User mentions "video structure", "section planning", "outline" - User wants to plan what goes where in the video TRIGGERS: "video outline", "outline", "structure the video", "plan the sections", "video structure", "outline this", "section flow"
youtube-packaging
by naveedharriCreate optimized YouTube packaging — titles and thumbnail concepts — for maximum click-through rate. Extends the title-generation skill with thumbnail planning, A/B testing suggestions, and packaging strategy aligned with the video brief. USE THIS SKILL WHEN: - User wants title + thumbnail for a video - User says "package this video", "thumbnail ideas", "title and thumbnail" - User mentions "YouTube packaging", "CTR optimization", "video packaging" - User has a video brief and wants to define the packaging TRIGGERS: "packaging", "title and thumbnail", "thumbnail", "CTR", "YouTube packaging", "package this video", "video packaging"
youtube-scripting
by naveedharriCreate a video script or structured bullet points for filming, based on the video outline. Supports full scripts, teleprompter-ready text, or talking-point bullet lists depending on Ben's preference for each video. USE THIS SKILL WHEN: - User wants to write the script for a video - User says "script this", "write the script", "talking points" - User mentions "video script", "filming notes", "teleprompter" - User has an outline and wants to prepare for filming TRIGGERS: "script", "video script", "write the script", "talking points", "filming notes", "scripting", "teleprompter", "bullet points for filming"
agentic-os-setup
by naveedharriSet up an agentic OS — either inside an Obsidian vault (bundled command-center dashboard, 5 auto-installed plugins, button bar wired to Claude prompts) OR as a standalone Next.js web dashboard with live MCP integrations (Circle, Fireflies, YouTube/VidIQ, Unipile LinkedIn DMs, Apify Twitter, Reddit), Anthropic Agent SDK refreshes, and optional Railway deploy. Use when the user says "set up agentic OS", "install command center", "bootstrap a personal AI dashboard", "build a vault dashboard", "spin up an MCP-powered dashboard", "deploy an AI ops dashboard", "give me my own version of the dashboard", "set up my second brain dashboard", or asks to personalize a dashboard previously created with this skill. Skill asks one routing question first — Obsidian or standalone — then runs the matching full flow.
agentic-os-standalone
by naveedharriSet up an agentic OS as a standalone Next.js web dashboard — wired to the Claude Agent SDK plus up to 7 live MCP integrations (Circle community, Fireflies meetings, YouTube/VidIQ, Unipile LinkedIn DMs, Apify Twitter/X, Reddit), per-profile views, a button-bar of actions, snapshot-style data refreshes, and an optional Railway deploy with HTTP basic auth and a persistent volume. A real web app — runs locally or live. Use when the user says "set up a standalone agentic OS", "build an MCP-powered web dashboard", "spin up my AI ops dashboard", "deploy an AI dashboard to Railway", "give me a web version of the dashboard", or asks to personalize a web dashboard previously created with this skill.
os-optimizer
by naveedharriFramework-driven audit and optimizer for any markdown vault. Applies 9 frameworks (F1 Anthropic CLAUDE.md, F2 Karpathy Wiki, F3 Caveman, F4 Chroma Context Rot, F5 Anthropic Memory, F6 Progressive Disclosure, G7 Hygiene, F8 Reflection / Anthropic Dreams, F9 Architecture & Discoverability). F9 walks the actual co-worker-Claude discovery chain (root CLAUDE.md → routing → folder Plot.md → file), audits routing-table truthfulness against folder reality, generates/refreshes per-folder Plot.md indexes, detects navigation orphans, proposes architectural reorganizations grounded in the user's Context/. Every finding ships a concrete fix — nothing is flag-only, nothing is fix-later; user picks apply-now (walk per item) or save-to-plan per finding. Creates visible per-stage tasks via TaskCreate so the user watches the run unfold. TRIGGERS: os optimizer, optimize vault, vault audit, second brain audit, clean up vault, framework audit, discoverability check, architecture audit, reorg vault. Run from vault root.
generate-visual
by naveedharriGenerate on-screen visuals for Ben van Sprundel's YouTube videos using Higgsfield. Same brand system as the thumbnails (charcoal + coral, dot-grid, flat-stylized icons, bold uppercase text), but optimized for in-video slides shown during a tutorial. Use when the user says generate a visual, make a slide, on-screen graphic, video visual, explain this concept visually, progressive disclosure, step-by-step reveal, or shares a concept and asks for a slide to show during their video. Two modes: single (one slide from one prompt) and progressive-disclosure (N sequential frames where each builds on the previous by adding one element at a time, locking background/composition across the entire sequence). Saves per-video to Projects/youtube/{video-slug}/visuals/.
os-operator
by naveedharriBuild and schedule a personalized Operator prompt that runs the user's second brain on a recurring cadence. The skill is invoked from inside the vault folder locally — it reads `Context/` and `CLAUDE.md` first to infer org, team, brand voice, and paths, then asks ONLY the gaps it can't determine (cadence, connectors, DM recipient, budgets, signature). Fills `references/operator-prompt-template.md`, writes the rendered prompt locally, then invokes the `schedule` skill to wire up the recurring trigger automatically. Template is a generic version of a battle-tested vault Operator spec — cadence awareness, freshness, daily-as-state, idle-timeout protection, principles, hard rules, failure handling, report schema. Use when the user says "set up the operator", "build my operator prompt", "operate my second brain", "schedule my OS", "os operator", "vault operator", or runs /os-operator.
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.