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  • 1
    Plannotator

    Plannotator

    Annotate and review coding agent plans visually, share with your team

    ...Plannotator integrates with diff views so reviewers can annotate changes line-by-line in git diffs, provide structured feedback, and navigate plans visually rather than through raw text alone. Users can attach and annotate images, save approved plan versions, and automatically export feedback into systems like Obsidian or Bear Notes for documentation purposes.
    Downloads: 11 This Week
    Last Update:
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  • 2
    graphify

    graphify

    AI coding assistant skill (Claude Code, Codex, OpenCode, OpenClaw)

    ...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.
    Downloads: 15 This Week
    Last Update:
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  • 3
    AsmJit

    AsmJit

    Low-latency machine code generation

    AsmJit is a low-level code generation library designed for dynamically creating machine code at runtime, enabling just-in-time (JIT) compilation for performance-critical applications. It provides a high-level API that abstracts away the complexity of writing raw assembly while still allowing fine-grained control over instruction generation. The library supports multiple architectures, including x86 and x64, making it versatile for cross-platform development. It is commonly used in applications such as emulators, compilers, and high-performance computing systems where runtime optimization is essential. asmjit emphasizes low latency and efficiency, ensuring that generated code executes quickly without significant overhead. ...
    Downloads: 6 This Week
    Last Update:
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  • 4
    Brokk

    Brokk

    Brokk brings code intelligence to AI

    Brokk is a code intelligence assistant framework designed to let large language models (LLMs) understand code semantically (not just as raw text) so that they can work effectively on large codebases that don’t fit wholly in a prompt context. It helps bridge the gap between LLMs and real-world engineering code by offering tooling to index, analyze, query, and augment code context, so that AI can meaningfully reason about existing code, suggest edits, and navigate across projects. ...
    Downloads: 6 This Week
    Last Update:
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