Open Source Agent Skills
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Agent Skills
View 104 business solutionsBrowse free open source Agent Skills and projects below. Use the toggles on the left to filter open source Agent Skills by OS, license, language, programming language, and project status.
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OpenMontage
World's first open-source, agentic video production system
OpenMontage is an open-source, agent-driven video production system that transforms AI coding assistants into fully automated multimedia creation pipelines. Instead of focusing on a single capability such as text-to-video generation, it treats video production as a structured, multi-stage workflow that mirrors how a real production team operates, including research, scripting, asset generation, editing, and final rendering. The system orchestrates a large collection of tools and models through coordinated pipelines, enabling an AI agent to autonomously gather information, write scripts, generate visuals, synthesize voiceovers, and assemble a complete video output. One of its defining characteristics is its modular and extensible architecture, which allows users to mix and match different providers, including both cloud APIs and local models, depending on performance, cost, or privacy needs. -
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Humanizer Skill
Claude Code skill that removes signs of AI-generated writing from text
Humanizer Skill is a utility library focused on transforming technical or machine-oriented text into expressions that are more natural, readable, and “human-friendly.” It provides a suite of algorithms that convert timestamps, identifiers, file sizes, code tokens, and structured data into phrases that resemble typical human phrasing rather than compact machine output. For example, date and time values can be expressed as relative terms (“two hours ago”), and file sizes can be shown in intuitive units instead of raw bytes. It also includes functions for transforming camelCase, snake_case, or PascalCase identifiers into spaced and capitalized representations suitable for user interfaces, reports, or documentation. Beyond text formatting, the library can handle pluralization, enumeration formatting (“A, B, and C”), and token expansion so that program-generated content feels more conversational. -
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Claude Skills
Public repository for Agent Skills
Claude Skills is a public repository that showcases and serves as a collection of skills — modular, reusable packages of instructions, scripts, and resources that Claude and other compatible agents can dynamically discover and load to extend their capabilities on specialized tasks. Rather than relying on handcrafted prompts every time, Skills teach an AI agent procedural knowledge and task-specific workflows so it can apply that expertise reliably, whether the task involves document creation, data analysis, design generation, or technical automation. Each Skill lives in its own directory with a SKILL.md file containing metadata and instructions, and can include supplemental scripts or assets that the agent uses to perform complex operations when relevant. -
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Claude Scientific Skills
A set of ready to use Agent Skills for research, science, engineering
Claude Scientific Skills is a large open source collection of ready-to-use scientific capabilities that extend AI coding agents into full research assistants. The project provides more than 170 curated skills covering domains such as genomics, drug discovery, medical imaging, physics, and advanced data analysis. Each skill bundles documentation, examples, and tool integrations so agents can reliably execute complex multi-step scientific workflows. The framework follows the open Agent Skills standard and works with multiple AI development environments including Claude Code, Cursor, and Codex. Its primary goal is to reduce the friction of scientific computing by giving AI agents structured access to specialized libraries, databases, and research pipelines. Overall, the repository acts as a modular capability layer that transforms general AI agents into domain-aware computational scientists. -
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Composio
Composio equip's your AI agents & LLMs
Empower your AI agents with Composio - a platform for managing and integrating tools with LLMs & AI agents using Function Calling. Equip your agent with high-quality tools & integrations without worrying about authentication, accuracy, and reliability in a single line of code. -
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Ponytail
Makes your AI agent think like the laziest senior dev in the room
Ponytail is an AI-agent ruleset and plugin system that pushes coding assistants toward simpler, smaller, and less over-engineered solutions. It is built around the idea that the best code is often the code that does not need to be written. Before generating new code, it encourages the agent to check whether the feature is necessary, whether the standard library already solves it, whether the platform has a native capability, or whether an existing dependency can do the job. The project supports several agent environments, including Claude Code, Codex, GitHub Copilot CLI, OpenCode, Gemini CLI, and other instruction-based editors through copied rules files. It includes commands for changing intensity, reviewing diffs, auditing repositories, and tracking deferred shortcuts. It is useful for developers who want AI coding tools to act more like pragmatic senior engineers and less like generators of unnecessary abstractions. -
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video-use
Edit videos with Claude Code
Video Use is an open-source AI-powered video editing tool that allows users to transform raw footage into polished videos using natural language commands. Designed to work with Claude Code, it automates the entire editing process—from cutting clips to rendering the final output—without requiring manual timelines or complex software interfaces. The system intelligently analyzes audio transcripts and visual cues to make precise, context-aware editing decisions. It supports a wide range of content types, including interviews, tutorials, montages, and talking-head videos. By combining structured text representations with on-demand visual previews, it minimizes processing overhead while maintaining high-quality results. Overall, Video Use reimagines video editing as an AI-driven, conversational workflow. -
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OpenWork
An open-source alternative to Claude Cowork, powered by opencode
OpenWork is a framework for building decentralized collaborative work environments powered by AI and human contributions. At its core, the project enables contributors to define tasks, workflows, and goals that can be split, shared, and recombined across distributed nodes while agents and humans cooperate to advance progress. It offers structured templates for work items, decision logic for task allocation, and consensus mechanisms that let groups verify and validate results toward shared objectives. This project also includes moderation and reputation layers so that contributor trust and quality can be assessed and integrated into future task assignments. Rather than a single monolithic workflow engine, it emphasizes openness — providing APIs and interfaces so communities can build custom dashboards, integrate specialized agents, or add bespoke evaluation criteria. -
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Palmier Pro
macOS video editor built for AI
Palmier Pro is an open-source video editor for Mac built around AI-assisted video creation. It lets users and coding agents work together directly inside a timeline, blending traditional editing with generative workflows. The app is written from scratch in Swift and takes inspiration from professional editors like Premiere Pro while rethinking the workflow around AI. Users can generate videos and images inside the editor with models such as Seedance, Kling, and Nano Banana Pro. It also exposes an MCP server, so tools like Claude, Codex, and Cursor can interact with the project. The core editor, MCP server, and agent chat are open source, while generative AI processing remains closed source. It is designed specifically for macOS 26 on Apple Silicon. -
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notebooklm-py
Unofficial Python API and agentic skill for Google NotebookLM
notebooklm-py is an unofficial Python API and agent-ready integration layer for Google NotebookLM that exposes NotebookLM functionality through code, the command line, and AI agent workflows. Its goal is to provide programmatic access not just to standard notebook operations, but also to many capabilities that are either limited or unavailable in the web interface, making it especially useful for automation and custom pipelines. The project covers notebook management, source ingestion, conversational querying, research workflows, and sharing controls, while also enabling the generation of a wide range of study and media artifacts. These outputs include audio overviews, videos, slide decks, infographics, quizzes, flashcards, reports, data tables, and mind maps, with configurable formats and export options. -
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Browser Use
Make websites accessible for AI agents
Browser Use is an AI-powered browser automation framework designed to let agents interact with websites just like humans do. It enables developers and AI systems to perform complex online tasks such as form filling, data extraction, and navigation through natural language instructions. Built with Python and compatible with modern LLMs, it integrates seamlessly with tools like ChatBrowserUse, Google Gemini, and Anthropic models. The platform supports both open-source deployment and a fully hosted cloud version for enhanced scalability and performance. Its cloud offering includes advanced capabilities like stealth browsing, CAPTCHA solving, and proxy rotation for reliable automation. Overall, Browser Use transforms web interaction into an intelligent, programmable workflow driven by AI agents. -
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Graphify
AI coding assistant skill (Claude Code, Codex, OpenCode, OpenClaw)
Graphify is a data visualization and transformation tool designed to convert structured or semi-structured data into graph-based representations, enabling better understanding of relationships and dependencies. It focuses on building visual models such as nodes and edges that represent entities and their connections, making complex datasets easier to interpret. The system likely supports dynamic updates, allowing graphs to evolve as data changes or new inputs are introduced. It is particularly useful in domains such as network analysis, knowledge graphs, and system architecture visualization. The architecture emphasizes flexibility, enabling users to customize how data is mapped and displayed. It may also include analytical features to explore patterns, clusters, or anomalies within the graph. Overall, Graphify serves as a bridge between raw data and visual insight. -
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Agent Skills for Context Engineering
A comprehensive collection of Agent Skills for context engineering
Agent Skills for Context Engineering is a curated collection of reusable “agent skills” focused on helping AI agents perform better on long-horizon, multi-step work by managing context deliberately. Rather than being a single application, it packages practical guidance into skill modules that agents can load to improve planning, retrieval, memory usage, and overall reliability in real workflows. The repository emphasizes context engineering as a discipline, covering why agents fail when context gets too large, too noisy, or poorly structured, and how to mitigate those failure modes with repeatable patterns. It is designed to be used across modern agent environments that support skill folders and structured instructions, so teams can standardize how agents operate instead of relying on ad-hoc prompting. -
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Agent Skills
Skills for AI coding agents
Agent Skills by Vercel Labs is a curated collection of modular “skills” designed to extend the capabilities of AI coding agents by packaging human-ready instructions, workflows, and optional scripts that tell an agent how to perform specific development tasks. In this repository, each skill adheres to the Agent Skills specification, meaning they’re defined as folders with a SKILL.md file (containing task descriptions and step-by-step guidance) and can include helper scripts and reference material that the agent can execute or consult when invoked. The goal of the project is to make it easy for AI assistants like Claude Code, OpenCode, Cursor, Codex, and others that support this open ecosystem to automatically apply best practices or perform concrete actions when a relevant user intent is detected. For example, some skills guide the agent in applying React and Next.js performance best practices, auditing UI and accessibility standards. -
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/last30days
Claude Code skill that researches any topic across Reddit + X
/last30days is a specialized Claude Code skill designed to research current trends and practices across Reddit, X, and the wider web from the last 30 days, synthesize that data, and produce copy-paste-ready prompts or summaries that reflect what the community is actually talking about now. Rather than returning generic model responses, it intelligently analyzes social media and community discussions to identify what’s genuinely trending or working in practice across topics ranging from prompt techniques to tool usage or cultural trends. This makes it particularly useful for prompt engineers, content creators, and developers who want up-to-date prompts and insights that align with the most recent consensus and shared best practices in fast-moving fields like AI tooling. -
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Medeo Video Generator
AI-powered video generation skill for OpenClaw
Medeo Video Generator is an AI-driven project designed to enable advanced video processing and generation capabilities within agent-based or automation systems. It provides a “skill” module that can be integrated into AI agents, allowing them to create, edit, and manipulate video content programmatically. The project focuses on bridging the gap between language-based AI systems and multimedia outputs by enabling models to produce structured video content as part of their workflows. It supports tasks such as video generation, editing, and transformation, making it useful for applications in content creation, marketing, and automated media production. The framework is designed to be modular, allowing developers to plug video capabilities into larger AI pipelines or agent systems. It emphasizes ease of integration and scalability, enabling both simple use cases and more complex multimedia workflows. -
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CLI Printing Press
Reads official API docs, studies CLI and MCP servers
CLI Printing Press is a Go-based tool that generates agent-ready command-line interfaces and MCP servers from APIs, websites, OpenAPI specs, or browser-captured HAR files. Instead of only wrapping endpoints, it studies the API, competing tools, useful workflows, authentication behavior, and hidden data opportunities before producing a more opinionated CLI. The generated tools are designed for AI agents first, with SQLite sync, offline search, structured output, compact modes, typed exit codes, and compound insight commands. It supports multiple entry paths, including direct specs, URLs without documentation, and HAR imports from browser developer tools. The project includes validation stages such as scorecards, dogfooding, proof-of-behavior checks, and optional live read-only smoke tests. Overall, CLI Printing Press aims to turn any useful web service into a practical automation surface for both humans and AI agents. -
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davidondrej-skills
Access to david ondrej's personal agent skills
davidondrej/skills is a public collection of reusable Agent Skills from David Ondrej. It packages repeatable workflows into structured instructions that AI coding, research, and workflow agents can load when needed. The repository is organized under a skills/ folder, with each individual skill living in its own folder and beginning with a SKILL.md file. Its categories cover agent orchestration, skill authoring, research and web work, operations and setup, and thinking or documentation workflows. The skills are meant to act as practical building blocks for code improvement, content preparation, idea research, presentation review, transcript work, and agent coordination. It is useful for people building a personal or team agent stack that needs consistent reusable procedures. -
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memsearch
A Markdown-first memory system, a standalone library for any AI agent
memsearch is a markdown-first memory system designed to provide long-term memory capabilities for AI agents through structured storage and semantic retrieval. It enables agents to store, organize, and retrieve information using embeddings and hybrid search techniques, ensuring that relevant context is always available. The system supports advanced features such as reranking and progressive disclosure, which help prioritize the most useful information for a given query. It integrates with vector databases like Milvus, enabling scalable storage and retrieval of large datasets. Memsearch is designed to be agent-friendly, making it easy to plug into existing AI workflows and enhance reasoning capabilities. Its markdown-first approach ensures transparency and portability of stored knowledge. Overall, it provides a robust foundation for building AI systems with persistent and intelligent memory. -
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Claude Codex Settings
My personal Claude Code and OpenAI Codex setup
Claude Codex Settings is a configuration-focused repository that provides curated settings, prompts, and workflow optimizations for improving AI-assisted coding environments. It is designed to help developers fine-tune how Claude and similar models behave within coding workflows, ensuring more consistent and high-quality outputs. The project emphasizes practical usability, offering ready-to-use configurations that can be directly integrated into development environments. It also includes guidelines for structuring prompts, managing context, and optimizing interactions with AI systems. The repository serves as both a toolkit and a reference for improving developer productivity when working with AI assistants. It is particularly useful for users who want to standardize their workflows and reduce variability in results. Overall, Claude Codex Settings acts as a configuration layer that enhances the effectiveness of AI coding tools. -
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Flow-Next
Plan-first AI workflow plugin for Claude Code, OpenAI Codex
Flow-Next is a workflow orchestration tool designed to manage complex processes by structuring tasks into organized and repeatable pipelines. It focuses on improving productivity by allowing users to define workflows that can be executed step by step or in parallel. The system emphasizes modularity, enabling tasks to be broken down into smaller components that can be reused across different workflows. It supports integration with various tools and services, making it adaptable to different environments. The project is designed to handle both simple and complex workflows, providing flexibility for a wide range of use cases. It also includes features for monitoring and managing execution, ensuring that workflows run reliably. Overall, Flow Next provides a structured approach to organizing and automating tasks in modern development environments. -
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CC Workflow Studio
Accelerate Claude Code/GitHub Copilot
CC Workflow Studio is a powerful Visual Studio Code extension that accelerates AI-assisted development by providing a visual workflow editor tailored for AI automation and agent orchestration, particularly with tools like Claude Code, GitHub Copilot, OpenAI Codex, and others. The extension lets developers and creators design complex AI workflows using intuitive drag-and-drop canvases or via conversational AI commands, blending graphical editing with natural language refinement. Workflows can include conditional branching, sub-agent orchestration, and exported output formats that are ready to run in native agent runtimes or as skill definitions, making it seamless to iterate from design to execution. The “Edit with AI” feature lets users refine workflows through natural language feedback, effectively combining the visual editor with powerful language models to reduce manual friction in complex logic construction. -
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Claude Code CLI
A comprehensive guide for setting up Claude Code CLI
Claude Code CLI is a structured resource designed to help developers use AI-assisted tools effectively in iOS application development. It provides guidance on how to integrate AI workflows into the process of building mobile applications using Swift and Apple’s development ecosystem. The project covers best practices for structuring prompts, managing code generation, and refining outputs to match platform-specific requirements. It emphasizes real-world development scenarios, helping users apply AI assistance to tasks such as UI creation, debugging, and feature implementation. The guide also includes examples and patterns that demonstrate how to maintain code quality while leveraging AI tools. It is particularly useful for developers transitioning into AI-assisted workflows within mobile development. Overall, it serves as a practical handbook for combining AI capabilities with iOS engineering practices. -
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Claude Code Skills & Plugins
232+ Claude Code skills & agent plugins for Claude Code, Codex
Claude Skills is a repository that provides a collection of structured skill definitions designed to enhance the capabilities of Claude-based AI systems. Each skill encapsulates a specific capability, such as coding, analysis, or workflow execution, allowing the model to perform tasks more effectively. The project emphasizes modularity, enabling skills to be combined and reused across different contexts. It is designed to integrate seamlessly into AI workflows, providing a plug-and-play approach to extending functionality. The repository also includes examples and templates, making it easier for developers to create their own custom skills. It supports a wide range of use cases, from development to content generation. Overall, Claude Skills acts as a library of reusable expertise modules for AI systems. -
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OpenAI Agent Skills
Skills Catalog for Codex
OpenAI Agent Skills is an open-source repository that serves as a broad catalog of agent skills designed to extend the capabilities of OpenAI Codex and other AI coding agents. It organizes reusable, task-specific workflows, instructions, scripts, and resources into modular skill folders so that an AI agent can reliably perform complex tasks without repeated custom prompting, making agent behavior more predictable and composable. Each skill is defined with clear metadata and instructions organizing how an AI assistant should complete specific tasks ranging from project management to code generation and documentation assistance. The repository supports community contributions, allowing developers to add new skills or update existing ones to keep the catalog relevant and practical for evolving use cases.