Add a custom model to the Voyager SDK model zoo for Axelera AI hardware. Use when the user wants to integrate a new PyTorch, ONNX, timm, or Ultralytics model.
General Axelera AI Voyager SDK and Metis hardware router for broad repository orientation, task planning, or multi-step work spanning several skills that is not a specific launch, run, deploy, debug, benchmark, app, test, build, or model-zoo task. Route…
Benchmark model performance on Axelera AI Metis hardware with the Voyager SDK. Use when the user wants to measure FPS, throughput, latency, or compare model variants. Use to quantify a working pipeline. Prefer voyager-debug when performance is a suspected…
Build GStreamer operators, trackers, and C/C++ examples for Axelera AI hardware. Use when the user wants to compile native Voyager SDK components.
Generate a Keep a Changelog fragment for the current PR in the Axelera Voyager / Voyager SDK development workflow. Provide a PR number or let the skill derive it from gh pr view.
Systematically debug and fix issues with Axelera AI Voyager SDK pipelines, models, inference, installation, or hardware. Use when the user brings an existing error, log, crash, accuracy issue, or regression, or when the Voyager SDK install is missing, broken,…
Compile and deploy a model pipeline for Axelera AI hardware using the Voyager SDK, especially custom or non-prebuilt models. Use when the user explicitly asks for compilation, quantization, or calibration, or wants to deploy or optimize a model for Axelera…
Get help with Voyager SDK for Axelera AI hardware. Use when the user asks questions about Voyager SDK, Axelera hardware, pipelines, InferenceStream API, or model zoo. Explanation-only answers; no code changes or pipeline runs.