Open Source Python Agent Skills
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Python Agent Skills
View 105 business solutionsBrowse free open source Python Agent Skills and projects below. Use the toggles on the left to filter open source Python Agent Skills by OS, license, language, programming language, and project status.
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Ship Agents FasterGemini Enterprise Agent Platform lets you rapidly build, scale, govern and optimize production-ready agents grounded in your organization's data. The platform enables developers to build custom or pre-built agents for virtually any use case. New customers get $300 in free credits.
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MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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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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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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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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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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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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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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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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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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AgentHandover
AgentHandover observes, learns and teaches agents with skills
AgentHandover is a Mac-focused system that observes how a user works and converts repeated workflows into reusable, self-improving skills for AI agents. It is designed for tools such as Claude Code, OpenClaw, Codex, Hermes, Cursor, Windsurf, and other MCP-compatible environments. Instead of asking users to manually write long prompts or static automation instructions, it records real actions, infers decision logic, and produces skills that include steps, strategy, guardrails, selection criteria, and writing style. The project supports both focused recording for specific tasks and passive discovery for workflows that appear repeatedly over time. It stores learned knowledge locally and uses feedback from later executions to improve confidence, add decision branches, and demote stale or failing skills. Its main value is helping agents learn how a person actually works, so recurring tasks can be handed off with more context, consistency, and trust. -
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Claw Compactor
14-stage Fusion Pipeline for LLM token compression
Claw Compactor is a utility designed to optimize and manage the context limitations inherent in AI agent systems, particularly those built on OpenClaw-like architectures. It addresses the challenge of finite context windows in language models by compressing or summarizing historical interactions while preserving essential information. The system works by transforming older conversation data into condensed representations that maintain continuity without exceeding token limits. This approach allows long-running agent sessions to continue operating efficiently without losing critical context. It is especially useful in autonomous workflows where agents accumulate large volumes of interaction history over time. The project aligns with broader strategies in AI systems that balance memory retention with computational constraints. Overall, claw-compactor functions as an infrastructure component that enhances scalability and stability in persistent AI agent environments. -
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Aden Hive
Outcome driven agent development framework that evolves
Hive is an open-source agent development framework that helps developers build autonomous, reliable, self-improving AI agents by letting them describe goals in ordinary natural language instead of hand-coding detailed workflows. Rather than manually defining execution graphs, Hive’s coding agent generates the agent graph, connection code, and test cases based on your high-level objectives, enabling outcome-driven agent creation that fits real business processes. Once deployed, agents can capture failure data, evolve automatically to meet their success criteria, and redeploy without constant manual intervention, delivering continual improvement over time. The framework also includes human-in-the-loop nodes, credential management, cost and budget controls, and real-time observability so teams can monitor execution and intervene as needed. Hive is designed for production environments and supports a wide range of large language models, local models, and business system connectivity. -
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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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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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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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pg-aiguide
MCP server and Claude plugin for Postgres skills and documentation
pg-aiguide is a tool designed to enhance AI-assisted development with PostgreSQL by providing structured knowledge and skills directly to coding agents. It acts as a bridge between database documentation and AI tools, enabling more accurate generation of SQL queries and database interactions. The system integrates with Claude Code through an MCP server, allowing agents to access curated PostgreSQL knowledge in real time. It focuses on improving developer productivity by reducing errors and providing context-aware suggestions. The project also includes documentation and examples that help users understand best practices in database design and querying. It is particularly useful for teams working heavily with PostgreSQL who want to leverage AI tools effectively. Overall, pg-aiguide enhances database-related AI workflows by providing structured, domain-specific knowledge. -
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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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geo-seo-claude
GEO-first SEO skill for Claude Code
geo-seo-claude is an AI-powered tool designed to automate the creation of geographically optimized SEO content using large language models, helping businesses improve their visibility in local search results. It leverages AI to generate location-specific content tailored to different regions, allowing users to scale SEO efforts across multiple cities or markets without manual content creation. The system focuses on producing structured and keyword-optimized pages that align with search engine ranking factors, including localized relevance and semantic context. It is particularly useful for agencies, marketers, and businesses that need to manage large volumes of localized landing pages efficiently. Geo SEO Claude can integrate with existing content pipelines, enabling automated generation and deployment of SEO assets. It also supports customization of content templates, allowing users to maintain brand consistency while scaling output. -
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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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Continuous Claude v3
Context management for Claude Code. Hooks maintain state via ledgers
Continuous Claude v3 is a persistent, multi-agent development environment built around the Claude Code CLI that aims to overcome the limitations of standard LLM context windows. Rather than relying on a single session’s context, Continuous Claude uses mechanisms like ledgers, YAML handoffs, and a memory system to preserve and recall state across multiple sessions, ensuring that learned insights and plans are not lost when context compaction occurs. The project orchestrates many specialized agents and skills—109 skills and 32 agents—so that complex coding tasks can be broken down, analyzed, and executed collaboratively by different components. It also includes a layered code analysis pipeline to reduce token usage and maintain relevant context efficiently. This continuous learning environment enables workflows such as bug fixing, refactoring, planning, and exploratory investigation while minimizing the need to re-explain context manually. -
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Skill Scanner
Security Scanner for Agent Skills
This repository is a public security-focused scanning tool intended to analyze and assess AI agent skills for potential issues, quality concerns, and vulnerabilities. It acts as a scanner that inspects Agent Skills packages to flag structural problems, inconsistencies, or security flaws before they are deployed or integrated into agent workflows. Because agent skills can contain executable instructions and logic, scanning them for risky patterns is essential to prevent inadvertent exploitation when used by intelligent systems. The tool supports maintainers and community contributors in automating quality checks and enforcing conventions across skill sets in a standardized way. While still evolving with contributions and issue discussions, it shows the community’s interest in building safer AI ecosystems around reusable capabilities. The scanner also serves as a foundation for more sophisticated vetting frameworks that might be incorporated into CI/CD pipelines. -
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AI Marketing Skills
Open-source AI marketing skills for Claude Code
AI Marketing Skills is a comprehensive open-source framework designed to transform AI agents into fully operational marketing and sales systems by equipping them with structured, reusable “skills” that automate real business workflows. Instead of simple prompts, the project provides complete operational modules that include scripts, scoring systems, and decision-making logic, allowing AI tools like Claude Code to execute complex marketing tasks end-to-end. The system is organized into multiple domains such as growth experimentation, sales pipeline generation, content production, outbound marketing, SEO optimization, and financial analysis, effectively covering the entire revenue lifecycle of a business. Each skill functions as an executable capability that can be invoked on demand, enabling users to perform tasks like running A/B tests, generating high-quality content, or analyzing conversion funnels with minimal manual effort. -
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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. -
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OpenClaw Medical Skills
The largest open-source medical AI skills library for OpenClaw
OpenClaw-Medical-Skills is an open-source library that provides a large collection of specialized medical capabilities designed for the OpenClaw AI agent ecosystem. The project organizes domain-specific “skills” that enable autonomous agents to perform tasks related to biomedical research, healthcare analysis, and clinical data interpretation. Each skill is packaged as a modular component that can be integrated into an OpenClaw-based AI assistant, allowing the agent to perform expert-level reasoning and workflows in medical contexts. Instead of relying on general-purpose language model responses, the repository equips AI agents with structured instructions and tools tailored to medical knowledge and datasets. This modular design allows developers and researchers to build AI systems that can access specialized medical reasoning processes, retrieve relevant biomedical information, and generate structured outputs suitable for analysis or downstream processing. -
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Pika Skills
A collection of open-source skills for AI coding agents
Pika Skills is an open-source framework designed to extend the capabilities of AI coding agents by introducing modular, reusable “skills” that can be dynamically invoked during development workflows. Each skill acts as a self-contained unit composed of structured instructions, executable scripts, and dependency definitions, enabling agents to autonomously perform complex tasks without requiring manual configuration or orchestration. The system is tightly integrated with the Pika Developer API, allowing developers to plug advanced functionalities such as automation, integrations, or real-time interactions directly into their AI-assisted coding environments. What makes this project particularly powerful is its declarative approach, where the agent reads a standardized instruction file to determine when and how to activate a skill, effectively turning documentation into executable intelligence. -
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AWS Agent Skills
AWS Skills for Agents
AWS Agent Skills is a repository that curates AWS-focused agent skills — capability modules that give AI assistants like Claude Code and Codex deep, practical knowledge across key Amazon Web Services domains. Instead of streaming giant documentation sets or relying on episodic web search, this project compresses AWS best practices, usage patterns, edge cases, and real-world engineering guides into pre-structured skill definitions that are token-efficient and tailored for reasoning. The skills cover critical AWS services such as IAM, Lambda, DynamoDB, S3, API Gateway, EKS, and many more, letting agents offer actionable advice on infrastructure as code, debugging, security configurations, and architectural workflows. Skills are kept up to date with weekly documentation checks, ensuring they reflect current AWS patterns and service changes.
