Agent Desktop Ffi
C-ABI cross-language binding library for direct invocation of desktop automation functions
Install & Use
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Help me install this AI Skill: Agent Desktop Ffi. It is used for: C-ABI cross-language binding library for direct invocation of desktop automation functions Full Skill content: https://321skill.com/skills/agent-desktop-ffi-x-3/raw/index.md Read that page and install it.
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This Skill addresses the inefficiency of having to spawn subprocesses via the CLI when calling desktop automation functions from various programming languages. In practice, developers often need to capture desktop window snapshots, perform click operations, or read element attributes in languages like Python, Node.js, Go, Swift, C++, and Ruby. However, each CLI invocation incurs significant process startup overhead and makes it difficult to maintain state within the same session.
Usage is straightforward: you only need to build a cdylib dynamic library in your project (cargo build --profile release-ffi -p agent-desktop-ffi) and then load the libagent_desktop_ffi.dylib (or .so/.dll) file via your language's FFI mechanism. After that, you can directly call ad_init for ABI handshake, use ad_adapter_create_with_session to create an adapter, obtain a desktop element snapshot via ad_snapshot and parse the reference IDs from the JSON, and finally execute actions like clicks or inputs with ad_execute_by_ref, freeing memory with ad_free_string. The entire observe-act workflow is identical to the CLI but eliminates the overhead of process creation and destruction.
It is ideal for teams or individuals needing to integrate desktop automation capabilities across languages. This is especially useful for developers already building AI Agents or automation tools in languages like Python (ctypes), Node.js (ffi-napi), Go (cgo), Swift, or Ruby (fiddle), allowing them to directly manipulate desktop UI elements without switching languages. It is also suitable for scenarios requiring high-frequency desktop operations (e.g., UI testing, automated operations and maintenance), as FFI calls are an order of magnitude faster than CLI.
It is recommended to use the release-ffi profile during build for performance optimization and to always call ad_init(AD_ABI_VERSION_MAJOR) after initially loading the dynamic library for version validation, preventing crashes due to ABI incompatibility. Note that this library currently only supports the PlatformAdapter functionality of agent-desktop, and some platforms (e.g., Windows) require additional configuration for DLL search paths. Refer to the pre-built archive locations in the build-and-link.md documentation for guidance.
Key Features
Unlike the agent-desktop CLI, this Skill loads the dynamic library directly via FFI, avoiding the overhead of spawning a subprocess per call. It supports direct invocation of C-ABI functions from multiple languages such as Python, Node.js, Go, and Swift, whereas the CLI can only interact via standard input/output and cannot maintain session state within the same process.
Limitations
Requires pre-compilation of the cdylib dynamic library (.dylib/.so/.dll) and the calling language must support FFI (e.g., ctypes, ffi-napi, cgo). Different build configurations are needed for Windows, Linux, and macOS platforms. Recompilation is required if the ABI is incompatible during version upgrades.
FAQ
How do I install agent-desktop-ffi?
Build it using the Rust toolchain: `cargo build --profile release-ffi -p agent-desktop-ffi`. The output dynamic library is located in the `target/release-ffi/` directory.
Which programming languages are supported?
All languages capable of calling the C-ABI are supported, including Python (ctypes), Node.js (ffi-napi), Go (cgo), Swift, C++, Ruby (fiddle), etc. Example code is available for each language.
Installation guide for AI assistants
If your AI coding assistant (Claude Code, Cursor, TRAE etc.) can see this page, send it this message to auto-install:
Visit https://321skill.com/skills/agent-desktop-ffi-x-3/raw/index.md to read the original Skill definition (Markdown format) for Agent Desktop Ffi, and install it according to the instructions.
Raw Markdown URL for AI: /skills/agent-desktop-ffi-x-3/raw/index.md