Search Results for "execute" - Page 11
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Showing 1617 open source projects for "execute"
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AI Marketing Skills
Open-source AI marketing skills for Claude Code
...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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Super Magic
All-in-one AI productivity platform with agents, workflows, and IM
...It is not a single tool but a complete product ecosystem composed of multiple integrated systems that work together to enhance productivity across different business scenarios. Magic centers around a general-purpose AI agent system called Super Magic, which can autonomously understand tasks, plan actions, execute workflows, and perform error correction. Alongside this, Magic includes a visual workflow engine that enables users to design complex AI processes using a drag-and-drop interface without requiring extensive coding knowledge. It also provides an enterprise-grade instant messaging system that integrates AI conversations with internal communication, allowing teams to collaborate while leveraging intelligent assistants. ... -
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Nanocoder
A beautiful local-first coding agent running in your terminal
...The tool is designed as a privacy-focused alternative to proprietary AI coding assistants, allowing users to run local models or connect to external APIs while keeping full control over their data and development workflow. Built with TypeScript and distributed as a CLI application, nanocoder enables developers to interact with AI agents that can read files, modify code, execute commands, and assist with debugging tasks. The platform supports multiple AI providers through OpenAI-compatible APIs and can also integrate with local model runtimes such as Ollama or LM Studio. Its architecture emphasizes extensibility through custom commands and integration with Model Context Protocol servers that allow the AI agent to access additional tools. -
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WasmEdge
Extensible WebAssembly runtime for cloud native applications
...The runtime offers isolation and protection for operating system resources (e.g., file system, sockets, environment variables, processes) and memory space. The most important use case for WasmEdge is to safely execute user-defined or community-contributed code as plug-ins in a software product (e.g., SaaS, software-defined vehicles, edge nodes, or even blockchain nodes). It enables third-party developers, vendors, suppliers, and community members to extend and customize the software product. -
Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
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Harness
A meta-skill that designs domain-specific agent teams
Harness is a meta-skill framework designed to automate the creation and orchestration of domain-specific AI agent teams within Claude Code environments. Instead of manually defining agents and their behaviors, it generates specialized agents, assigns them roles, and produces the skills they need to execute tasks effectively. The system focuses on scaling agent-based workflows by dynamically assembling teams tailored to specific problems. It enables structured collaboration between agents, allowing them to divide work and operate in coordinated pipelines. Harness also abstracts the complexity of agent design, making it easier for developers to deploy multi-agent systems without extensive configuration. ... -
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Ollama4j
A simple Java library for interacting with Ollama server
...It integrates seamlessly into Java ecosystems through Maven or Gradle dependencies, and it works with standard Java environments starting from JDK 11 and above. Ollama4j also includes support for advanced features such as tool or function calling, enabling models to interact with external systems and execute more complex workflows. -
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k-skill
Skill collection for Koreans - SRT, KTX, KakaoTalk, Hangul
The k-skill project is an AI skill management framework designed to organize, structure, and execute reusable capabilities within AI-driven development environments. It focuses on defining skills as modular, composable units that can be invoked by agents to perform specific tasks such as coding, reasoning, or automation. The system provides a standardized structure for skills, enabling consistency across different workflows and improving interoperability between tools. -
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webR
The statistical language R compiled to WebAssembly via Emscripten
webR is a project that compiles the R statistical programming language into WebAssembly, enabling it to run entirely within web browsers or JavaScript environments without requiring a server-side installation. By using Emscripten to adapt R’s C, C++, and Fortran codebase, webR creates a fully functional runtime that can execute R scripts directly in the browser. The project includes a web-based integrated development environment that uses tools like xterm.js and CodeMirror, allowing users to interact with R through a familiar console and editor interface. It supports installing and running R packages, making it possible to perform data analysis, statistical modeling, and visualization entirely client-side. webR also provides distribution options such as npm packages, CDN hosting, and Docker images for flexible deployment. ... -
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Stlite
n-browser Streamlit
Stlite is a WebAssembly-powered framework that enables Streamlit applications to run entirely in the browser without requiring a Python backend server. It achieves this by using Pyodide, a WebAssembly-based Python runtime, to execute Python code directly within the browser environment. This allows developers to build interactive data applications using familiar Streamlit APIs while eliminating the need for server-side infrastructure. Stlite supports a wide range of Python libraries and enables real-time interactivity, making it suitable for dashboards, data visualization tools, and educational applications. ... -
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quickjs-emscripten
Safely execute untrusted Javascript in your Javascript
quickjs-emscripten is a JavaScript library that compiles the QuickJS engine into WebAssembly using Emscripten, enabling developers to run JavaScript code inside a sandboxed environment within browsers or server-side JavaScript runtimes. It provides a secure and isolated execution context, making it particularly useful for running untrusted or user-generated code safely. The library abstracts the complexity of loading and initializing the WebAssembly module, offering convenient APIs to create... -
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Wasmi
Efficient and versatile WebAssembly interpreter for embedded systems
wasmi is a lightweight WebAssembly interpreter written in Rust that is designed to execute Wasm binaries efficiently in constrained or embedded environments. Unlike JIT-based runtimes, wasmi focuses on interpretation, prioritizing portability, determinism, and low resource usage over maximum raw performance. It is particularly well-suited for blockchain systems, embedded devices, and other contexts where predictable execution and minimal dependencies are critical. -
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wazero
The zero dependency WebAssembly runtime for Go developers
wazero is a zero-dependency WebAssembly runtime written in Go that enables developers to execute WebAssembly modules directly within Go applications without relying on external toolchains or CGO. It fully implements the WebAssembly core specification and supports both interpreter and compiler execution modes, allowing developers to choose between portability and performance. One of its defining characteristics is its pure Go implementation, which simplifies cross-compilation and deployment across different platforms. ... -
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AndroidNativeEmu
Allows you to partly emulate an Android native library
AndroidNativeEmu is a Python-based framework designed to partially emulate Android native libraries, enabling developers and researchers to analyze and execute native code outside of a full Android environment. Instead of emulating an entire operating system, it focuses specifically on the native layer, allowing for targeted testing and reverse engineering of shared libraries (.so files). This makes it particularly useful in security research, malware analysis, and debugging of Android applications. ... -
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AI Agent Deep Dive
AI Agent Source Code Deep Research Report
...The project is organized as a learning resource rather than a standalone framework, making it particularly useful for developers who want to move beyond surface-level prompt engineering into full agent system design. It explores how agents interact with environments, execute tasks, and maintain context over time, highlighting both strengths and limitations of current approaches. The repository likely includes diagrams, annotated code samples, and conceptual walkthroughs that mirror real production systems. -
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Goose AEO
AEO tracking toolkit (CLI + dashboard) built for AI agents like Claude
Goose AEO is an AI agent orchestration framework focused on automating engineering operations and workflows through autonomous agents. It builds on the concept of local AI agents that can execute complex tasks such as writing code, debugging, managing pipelines, and interacting with APIs without continuous human supervision. The system is designed to be extensible and adaptable, allowing developers to integrate different language models and configure multi-agent workflows tailored to specific use cases. It emphasizes automation of repetitive and complex development tasks, enabling users to focus on higher-level problem solving and innovation. ... -
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Godot MCP
MCP server for interfacing with Godot game engine
...It acts as a bridge between AI systems and the Godot editor, providing capabilities such as launching projects, running games in debug mode, and capturing runtime output for analysis. The tool is particularly valuable for AI-assisted game development, as it creates a feedback loop where agents can execute code, observe results, and iteratively improve their outputs. It also includes advanced features for manipulating scenes, managing assets, and editing project structures, making it possible to automate large portions of the development process. By exposing Godot functionality through a standardized MCP interface, it ensures compatibility with various AI clients such as Claude Code or Cursor. -
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Embabel Agent Framework
Agent framework for the JVM. Pronounced Em-BAY-bel
Embabel Agent Framework is a JVM-based framework for building advanced AI agent systems that combine structured programming with large language model interactions to execute complex, goal-oriented workflows. The framework introduces a planning-driven approach where agents dynamically determine sequences of actions required to achieve objectives, rather than relying on fixed pipelines or predefined flows. It models agent behavior through concepts such as goals, actions, and conditions, allowing systems to adapt in real time based on changing inputs and outcomes. ... -
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BehaviorTree.CPP
C++ behavior tree library for robotics and AI decision systems
BehaviorTree.CPP is a C++ library designed to create, manage, and execute behavior trees, a widely used model for decision-making in robotics and artificial intelligence systems. It provides a flexible and modular framework that allows developers to define complex behaviors as reusable tree structures composed of nodes. BehaviorTree.CPP emphasizes performance and real-time execution, making it particularly suitable for robotics applications where responsiveness is critical. -
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Apache Hamilton
Helps data scientists define testable self-documenting dataflows
...The framework enables developers to define data transformations as simple Python functions, where each function represents a node in a dataflow graph and its parameters define dependencies on other nodes. Hamilton automatically analyzes these functions and constructs a directed acyclic graph representing the pipeline, allowing the system to execute transformations in the correct order. This approach encourages modular, testable, and maintainable data pipelines because each transformation is isolated and easily unit tested. The framework also automatically tracks lineage and metadata about how data is produced, which improves debugging, reproducibility, and transparency in data workflows. -
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Deepnote
Deepnote is a drop-in replacement for Jupyter
...Built on top of the Jupyter kernel ecosystem, it maintains compatibility with existing notebook workflows while introducing additional features focused on collaboration and automation. The system supports programming languages such as Python, R, and SQL and allows users to execute and analyze data directly within interactive notebooks. Deepnote emphasizes team-based data science by enabling real-time collaboration similar to shared document editors, allowing multiple users to work simultaneously on the same notebook environment. -
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BrowserNode
Make websites accessible for AI agents. Automate tasks online
...Built as an implementation compatible with the Browser-use ecosystem, Browsernode allows agents to perform actions such as navigating pages, extracting information, filling forms, or interacting with dynamic web interfaces. The system integrates with Playwright to control Chromium-based browsers and execute automation scripts in a reliable environment. Developers can configure the framework to connect to different language model providers so that AI agents can interpret instructions and decide which browser actions to perform. -
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BrowserGym
A Gym environment for web task automation
...It is intended for researchers building web agents rather than for end users looking for a consumer automation product. The project provides a common environment where agents can interact with websites, execute tasks, and be evaluated against standardized benchmarks. One of its main strengths is that it bundles several important benchmarks by default, including MiniWoB, WebArena, VisualWebArena, WorkArena, AssistantBench, WebLINX, and OpenApps. This gives researchers a unified way to compare agent behavior across diverse web environments and task types without stitching together separate evaluation stacks. ... -
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OM1
Modular AI runtime for robots
...The project focuses on creating a modular architecture where language models can coordinate with external tools, APIs, and knowledge sources to accomplish multi-step objectives. Instead of operating as simple conversational systems, OM1 agents can plan actions, retrieve information, and execute tasks across different services. The framework integrates reasoning modules, planning strategies, and tool interfaces that allow agents to operate in dynamic environments. Developers can extend the system by connecting new tools, services, or data sources to the agent architecture. The platform also includes mechanisms for coordinating workflows and managing the state of ongoing tasks. -
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nono
Secure, kernel-enforced sandbox CLI and SDKs for AI agents
nono is an open-source, kernel-enforced capability shell designed to safely run AI agents and other untrusted processes under strict operating system controls. The project addresses a growing security concern: modern coding agents typically execute with full user permissions, which means they can potentially read sensitive files, modify system configurations, or exfiltrate credentials if compromised. nono solves this by applying default-deny sandboxing at the kernel level using technologies such as Landlock on Linux and Seatbelt on macOS, making unauthorized actions structurally impossible rather than merely discouraged. ... -
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Personal AI Infrastructure
Agentic AI Infrastructure for magnifying HUMAN capabilities
...Unlike once-stateless chatbots, this platform captures context, memory, goals, preferences, and feedback to enable an AI that understands you and improves over time, using a full agentic stack rather than simple question-answer loops. PAI blends tools like browsing, code editing, execution, and more into a continuous Observe → Think → Plan → Execute → Verify → Learn cycle, letting the system refine its behavior with each use. Its architecture supports long-term memory, verification of actions, and ongoing self-improvement, blurring the line between “assistant” and persistent, evolving collaborator.
