Install Holoscan SDK 5.x Python packages in an isolated environment after checking platform and CUDA 13 requirements. Choose the full stack or matching components, then verify dependencies, imports, and a release-matched example pipeline.
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Find and run Holoscan Sensor Bridge example applications that match a connected development kit, board, software version, and sensors. Monitor timed runs, investigate failures, suggest code or environment changes, and summarize the session.
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Check whether a Dynamo deployment is ready for disaggregated serving, where input processing and token generation run separately. Read-only probes inspect transport settings, GPU networking capabilities, and NIXL transfer-test readiness, then report gaps and next steps.
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Configure how Dynamo routes requests to workers, then check model discovery and a chat response. Supports local and Kubernetes setups, including routing based on cached model data, with clear commands, results, and limitations.
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Set up a NVIDIA Holoscan Sensor Bridge demo for the selected development kit. The workflow configures the host, builds and launches the demo container, checks board connectivity and FPGA version, and reports issues encountered.
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Set up Earth2Studio with uv or pip using commands matched to your environment and planned models. The skill guides optional dependency selection, cache configuration, installation checks, and dependency troubleshooting while leaving package installation to the user.
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Find Earth2Studio models, data sources, and examples for weather or climate tasks. Filters options by region, forecast type, and GPU memory, then checks whether data sources supply the variables required by each model using current documentation and source files.
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Build Holoscan SDK 5.x from a selected tag, commit, or development branch using its run wrapper. Check prerequisites, choose build options, preserve existing changes, and verify the result with example tests for SDK development or Early Access features.
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Implement structured telemetry, such as counters and events, from DOCA applications to external consumers. Guides publishing API selection, schema and source setup, build and test workflows, and debugging lifecycle errors or reports that never reach the receiver.
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Upgrade or downgrade FPGA firmware on supported HSB Lattice boards and Leopard Imaging VB1940 cameras connected to an NVIDIA devkit. Identifies the hardware, selects version-specific files and commands, and verifies the installed version after flashing.
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Convert recorded robot workflows from HDF5 into local LeRobot datasets for training or browser inspection. Preserves actions, state, camera recordings, and task labels, then checks episode counts, metadata, videos, and data dimensions.
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Build Earth2Studio wrappers for transformations at a single time point, from calculating wind speed to using pretrained or diffusion models. The workflow covers input and output coordinates, model loading, tests, and supporting documentation.
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Select an existing NVIDIA Dynamo Kubernetes deployment recipe for a model, inference framework, and GPU setup. The skill validates requirements, patches necessary settings, deploys the recipe, and checks the endpoint with an OpenAI-compatible test request.
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Load, configure, run, observe, and stop custom congestion control algorithms on BlueField using doca_spcx_cc. The skill guides comparisons with doca-pcc, evaluation under controlled network contention, and diagnosis of loading errors or unchanged traffic behavior.
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Grade recorded workflow episodes against a written success criterion using a vision model, which interprets sampled camera images. Summarize pass and fail counts, or optionally extract successful episodes into a separate HDF5 dataset.
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Record human-operated robot demonstrations in workflow HDF5 files, a structured data format. The skill guides supported input-device selection, foreground recording, and checks of robot motion, camera observations, saved episodes, and task outcomes.
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Fine-tune GR00T or openpi robot policies using compatible LeRobot data. Check dataset requirements, preview the training configuration, run training, and verify that a saved checkpoint, a file containing the trained model, loads through the inference backend.
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Helps developers offload remote memory operations from HPC, UCX, or MPI applications to a BlueField DPU, a processor for infrastructure tasks. Covers host-side DOCA UROM setup, supported-operation discovery, completion handling, and error investigation.
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Investigate missing DOCA telemetry metrics with doca_telemetry_utils. Discover diagnostic counters, translate counter names to Data IDs and back, and check device support before adding counters to an exporter configuration.
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Consolidate DOCA installation details, device capabilities, and host versus DPU differences into a consistent report. The skill defines structured output formats and manual fallback checks, including how to report unavailable tools and validation limits.
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Diagnose failed Dynamo deployments using Kubernetes status, events, and logs. Gather evidence without changing the cluster, identify the likely failure layer, and return a specific command or patch to try next.
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Generate a SystemVerilog top-level scaffold from a validated HOLOLINK_def.svh file. The output declares HSB signals, instantiates HOLOLINK_top, and leaves integration TODOs, using current IP source or bundled references for supported revisions.
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Replay an episode stored in HDF5, a structured data file, using its original workflow Scene. Check the full recorded motion visually, inspect segment boundaries and camera views, and report agreement or the first mismatch.
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Expand successful workflow recordings stored in HDF5 by copying episodes and adding small variations to recorded actions. Limit changes to a requested node segment and check generated counts, data dimensions, success flags, and preserved segments.
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