Add or update xLLM unit tests in the repository. Use when Codex needs to create a new C++/CUDA/NPU/MLU unit test, place a test under tests/, wire it into CMake with cctest, update an existing test target, choose platform gates, or validate test naming and dependencies against current xLLM test conventions.
Review code changes for quality, security, performance, and correctness following project-specific standards. Use when reviewing pull requests, examining git diffs, or when the user asks for a code review. This skill should be used proactively — when the user asks for a review without specifying commits, automatically…
Use when the user wants to add, modify, debug, or review an xLLM TileLang Ascend kernel or specialization, including Python kernel definitions, generated Ascend-C source, runtime wrapper dispatch, TileLang CMake wiring, and NPU tests.
Implement or debug Agent Client Protocol (ACP) support in Rust for siGit Code. Use when working on ACP JSON-RPC over stdio, the agent-client-protocol crate, session/prompt/fork handlers, config options (model picker), slash commands, streaming notifications, or editor integration.
Build or maintain AI-assisted coding features in Rust using Onde Inference. Use when working on ChatEngine integration, model loading, streaming inference, history management, sampling config, or local coding-agent architecture.
Build, launch, and drive the sigit AI coding agent — run the ACP server, screenshot the interactive TUI, smoke-test the CLI. Use when asked to run sigit, start the agent, screenshot the chat UI, or verify a change to the binary.
Integrate an external model or pipeline into TeleFuser while preserving upstream behavior and reusing TeleFuser's existing pipeline, stage, model-loading, configuration, example, CLI, and service interfaces. Use for new model support, new pipeline integration, or porting an upstream inference implementation.
Optimize an existing TeleFuser pipeline using measured bottlenecks and current repository-supported ops, parallelism, caching, quantization, compilation, or offload mechanisms. Use for latency, throughput, GPU memory, OOM, multi-GPU, or inference-performance work after a correct baseline exists.
Profile a TeleFuser pipeline progressively from stage timing to isolated kernel analysis and optional Nsight Compute diagnosis. Use when investigating latency, throughput, memory, output cadence, slow stages, or GPU kernel bottlenecks before optimization.