4 projects for "low code" with 2 filters applied:

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  • 1
    Refly

    Refly

    The first open-source agent skills builder

    Refly is an AI-native workflow platform that democratizes automated workflow and skills creation for both technical and non-technical users by offering a visual, natural-language-driven interface. Instead of requiring code, Refly lets creators define tasks and business logic through simple “vibes,” which are compiled into structured, reusable agent skills that can be executed on engines like Claude Code, Cursor, or other supported runtimes. With a focus on making automation accessible, it provides a visual canvas and low-code components that feel similar to drag-and-drop builders but backed by powerful AI orchestration, memory handling, and integrations with external services. ...
    Downloads: 0 This Week
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  • 2
    OpenAI Realtime Agents

    OpenAI Realtime Agents

    This is a simple demonstration of more advanced, agentic patterns

    ...It also supports a “Chat-Supervisor” pattern where a lightweight realtime chat agent handles user interactions and delegates more complex reasoning or tool usage to a stronger textual model (e.g. GPT-4). Because realtime agents are still a beta feature, the code and API surface are subject to changes and may evolve.
    Downloads: 1 This Week
    Last Update:
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  • 3
    Softaworks Agent Skills

    Softaworks Agent Skills

    A curated collection of skills for AI coding agents

    ...The toolkit’s modular design follows the Agent Skills format, making it easy for users to install only what’s needed via CLI installers or plugin marketplaces. Because the set spans from low-level utilities like dependency updaters to higher-level planning and communication aids, it can streamline many aspects of a developer’s day-to-day work.
    Downloads: 0 This Week
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  • 4
    OSS-Fuzz Gen

    OSS-Fuzz Gen

    LLM powered fuzzing via OSS-Fuzz

    OSS-Fuzz-Gen is a companion project that helps automatically create or improve fuzz targets for open-source codebases, aiming to increase coverage in OSS-Fuzz with minimal maintainer effort. It analyses a library’s APIs, examples, and tests to propose harnesses that exercise parsers, decoders, or protocol handlers—precisely the code where fuzzing pays off. The system integrates with modern LLM-assisted workflows to draft harness code and then iterates based on build errors or low coverage signals. Importantly, it aligns with OSS-Fuzz conventions, generating corpus seeds, build rules, and sanitizer settings so projects can plug in quickly. Reports highlight what functions were targeted, how coverage evolved, and where manual hints could unlock more paths. ...
    Downloads: 0 This Week
    Last Update:
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